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G00300331 Hype Cycle for Retail Technologies, 2016 Published: 12 July 2016
Analyst(s): Robert Hetu
Retail CIOs can use this Hype Cycle to advise their businesses on how to cut through market hype when prioritizing retail technology investments to support unified retail and digital business.
Table of Contents
Analysis...... 3 What You Need to Know...... 3 The Hype Cycle...... 3 The Priority Matrix...... 6 Off The Hype Cycle...... 7 On the Rise...... 8 Algorithmic Retailing...... 8 Retail Distributed Order Management...... 9 Digital Workplace...... 11 Customer Engagement Hub...... 12 Project P2P Solutions...... 14 Intelligent Virtual Store Design...... 15 Retail 3D Printing...... 17 At the Peak...... 18 Digital Wallets in Retail...... 18 Cognitive Expert Advisors...... 21 Social Employee Recognition Systems...... 22 Augmented Reality in Retail...... 24 Multichannel Location Analysis...... 26 Master Content Management...... 28 Smart Data Discovery...... 30 Workforce Analytics...... 31 Sliding Into the Trough...... 33
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Real-Time Store Monitoring Platform...... 33 Real-Time Customer Offer Engines...... 35 Social Commerce...... 36 Digital Coupons...... 38 Loyalty Management Systems...... 39 Retail Mobile Payments...... 41 Unified Merchandise Planning...... 43 Climbing the Slope...... 44 Multichannel Master Data Management for Retail...... 44 Retail Mobile Shopping...... 47 Customer-Centric Merchandising & Marketing...... 48 In-Store Self-Service: Customer-Facing Applications...... 50 Algorithmic Merchandise Optimization...... 51 Electronic Shelf Labels...... 53 Java-Based POS Software...... 55 Unified Price, Promotion and Markdown Optimization...... 57 Entering the Plateau...... 58 Mobile POS...... 58 Appendixes...... 60 Hype Cycle Phases, Benefit Ratings and Maturity Levels...... 62 Gartner Recommended Reading...... 63
List of Tables
Table 1. Hype Cycle Phases...... 62 Table 2. Benefit Ratings...... 62 Table 3. Maturity Levels...... 63
List of Figures
Figure 1. Hype Cycle for Retail Technologies, 2016...... 5 Figure 2. Priority Matrix for Retail Technologies, 2016...... 7 Figure 3. Hype Cycle for Retail Technologies, 2015...... 61
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Analysis
What You Need to Know Forces not unlike wind, rain, thunder and lightning have engulfed retailers in a perfect storm. The retail storm exhibits the powerful forces of shifting lifestyles, social upheaval, political instability and a hypercompetitive marketplace driven by technological acceleration.
Regardless of the number of channels a retailer has, customer expectations of consistent and fexible shopping between and across channels mean that all of the retailer's customer-facing processes must be unifed. Retailers of all types must engage in digital business transformation built on a foundation of customer understanding to facilitate a unifed shopping experience. Unifcation will only be transformative when the entire organization is reoriented toward customer centricity. Ultimately, the customer channel is the only channel that matters.
Retail CIOs should use this Hype Cycle to identify technologies that will enable customer-centered digital business transformation that is critical for their organizations to survive the storm and thrive.
The Hype Cycle This Hype Cycle contains technologies that should be considered by large retailers having many channels and operating in all segments and geographies. CIOs and business leaders of these retailers are confronted with a wide variety of technology options that can provide increased operational effciency, improved customer experiences and increased digital business effectiveness. As a result, prioritization of technology investment is critical, and the dynamics of combining technologies, for example, smart machines with algorithms and the Internet of Things (IoT), cannot be overlooked. Many retailers have engaged in store count and staffng reductions and real estate investment trusts (REITS) to improve bottom-line performance and fund new initiatives such as major technology investments to enhance digital readiness. Simultaneously, they are investing in new store prototypes, formats and remodels aimed at improving the customer's physical experience. Yet there is a need to operate in a bimodal mode in the business, as well as in IT, to ensure that the basics of maintaining adequate in-stock levels are not sacrifced while pursuing innovation. Some of the major trends driving retail investment include:
■ Business:
■ Consumers' expectations of retailers' delivery of services and differentiated experiences that enhance their lifestyles
■ Channel migration, unifcation and reorganization of internal structures
■ Hypercompetitive market with low cost of entry for nontraditional players
■ Rising cost of employment, combined with a skills shortage
■ Need for more consistent best practices and automated processes in various business functions
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■ Technology:
■ Smart machines, the IoT and 3D printing
■ Algorithms, analytics and big data
■ Convergence of social and mobile
■ Cloud computing
■ Augmented reality
These trends pervade the 31 technologies included in this year's Hype Cycle. New technologies include algorithmic retailing, retail distributed order management, cognitive expert advisors and customer engagement hubs. Some have been renamed to more accurately refect current conditions: Unifed merchandise planning (was multichannel merchandise planning), algorithmic merchandise optimization (was merchandise and category optimization) and smart data discovery (was advanced analytics with self-service delivery).
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Figure 1. Hype Cycle for Retail Technologies, 2016
expectations Multichannel Location Master Content Management Analysis Smart Data Discovery Augmented Reality in Retail Workforce Analytics Social Employee Recognition Systems Cognitive Expert Advisors Digital Wallets in Retail Retail 3D Printing Intelligent Virtual Store Design Real-Time Store Monitoring Platform
Mobile POS Project P2P Solutions Real-Time Customer Offer Engines Customer Engagement Hub Unified Price, Promotion and Markdown Optimization Digital Workplace Java-Based POS Software Social Commerce Electronic Shelf Labels Retail Distributed Order Management Algorithmic Merchandise Optimization Algorithmic Retailing In-Store Self-Service: Customer-Facing Applications Digital Coupons Loyalty Management Systems Customer-Centric Merchandising & Marketing Retail Mobile Payments Retail Mobile Shopping Unified Merchandise Planning Multichannel Master Data Management for Retail
As of July 2016 Peak of Innovation Trough of Plateau of Inflated Slope of Enlightenment Trigger Disillusionment Productivity Expectations time Plateau will be reached in: obsolete less than 2 years 2 to 5 years 5 to 10 years more than 10 years before plateau
Source: Gartner (July 2016)
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The Priority Matrix Retail CIOs can use the Priority Matrix to proactively advise the business on how to cut through the market hype of various technologies by highlighting the benefts that Hype Cycle technologies contribute in support of the transformation to unifed retail and digital business.
Four beneft ratings are used to describe each technology that is included on any Gartner Hype Cycle: transformational, high, moderate and low. The retail HC is focused on technologies that we believe will be transformative or will yield high impact for large retailers.
Select Transformative Technologies:
■ Smart Data Discovery (two to fve years to plateau) tools put information in the hands of business analysts and users to take advantage of signifcant potential to create business value and competitive advantage.
■ Real-Time Store Monitoring Platform (fve to 10 years to plateau), as a type of IoT platform, has the potential to be a game changer by digitalizing the physical retail shopping experience.
Select High Priority Technologies:
■ Algorithmic Merchandise Optimization (two to fve years to plateau) facilitates the complex management that customer centricity requires, enabling the retailer to do more-detailed planning with fewer resources.
■ In-Store Self-Service: Customer-Facing Applications (two to fve years to plateau) could release store associates to perform more value-adding tasks — such as dealing with inquiries on complex products — which present opportunities for upselling and cross-selling.
■ Social Commerce (two to fve years to plateau) can create new customer segments that are based on consumers' interests in a web environment.
■ Retail Distributed Order Management (fve to 10 years to plateau) is a new addition that is a high priority for making "buy anywhere, fulfll anywhere, return anywhere" a more seamless experience.
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Figure 2. Priority Matrix for Retail Technologies, 2016
benefit years to mainstream adoption less than 2 years 2 to 5 years 5 to 10 years more than 10 years
transformational Smart Data Discovery Algorithmic Retailing Cognitive Expert Advisors Real-Time Store Monitoring Platform Retail 3D Printing
high Algorithmic Merchandise Digital Wallets in Retail Customer Engagement Optimization Hub Master Content Customer-Centric Management Digital Workplace Merchandising & Marketing Multichannel Location Analysis In-Store Self-Service: Customer-Facing Real-Time Customer Offer Applications Engines Intelligent Virtual Store Retail Distributed Order Design Management Java-Based POS Workforce Analytics Software Loyalty Management Systems Multichannel Master Data Management for Retail Retail Mobile Shopping Social Commerce Unified Merchandise Planning Unified Price, Promotion and Markdown Optimization
moderate Mobile POS Digital Coupons Augmented Reality in Retail Electronic Shelf Labels Retail Mobile Payments Social Employee Recognition Systems
low
As of July 2016
Source: Gartner (July 2016)
Off The Hype Cycle Multichannel customer analytics has been dropped from the Hype Cycle and its content included in the newly renamed profle customer-centric merchandising and marketing. Multichannel order fulfllment and multichannel order management have been removed with their content included in the new profle, retail distributed order management.
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On the Rise
Algorithmic Retailing Analysis By: Robert Hetu
Definition: Algorithmic retailing is the industrialized use of complex mathematical algorithms pivotal to driving improved business decisions or process automation for competitive differentiation in the retail marketplace.
Position and Adoption Speed Justification: This technology has been positioned as post-trigger in recognition of the fact that retailers have leveraged algorithms and optimization technologies in diverse business process areas such as supply chain, merchandising and marketing. Algorithmic retailing takes a broader view of use of mathematical algorithms and smart data discovery to make major contributions to the effectiveness of the retailer. Integrating Internet of Things (IoT) use cases with smart machines signifcantly increases data volume, and will require not only algorithms but signifcant change of mindset. As such, it will take fve to 10 years for this profle to progress to the plateau.
User Advice: New technologies create opportunities to advance algorithms, incorporating many more data inputs, steps and even decision-making capability. Complex algorithms were once the domain of scientists and academics, but with the advent of digital technologies and smart machines, retailers will be able to use algorithms to improve business results. In many cases, the action of algorithms on data occurs solely through the involvement of smart machines. Smart machines are an emerging "super class" of technologies that can perform a wide variety of work and add great value to business process. At other times, humans will interact with algorithms that are acting as a support mechanism for business users. Bots (simple computer programs used to perform highly repetitive operations) will be employed to automate routine or repetitive tasks that may have formerly required human intervention. Bots play an important role in supporting the human and machine interactions.
For retail, a common use of algorithms and smart machines is found in replenishment systems. These applications typically operate under user-driven constraints and policies while calculating demand forecasts and commensurate orders. Merchandise optimization technologies such as price or promotion optimization may be used by the business. Determine utilization of optimization technologies and evaluate effectiveness by frst identifying the current footprint of optimization applications. Business units may have built relationships with technology providers independently from IT, so it's important to take an inventory of the current optimization applications available to the users. However, using algorithms effectively will require a new approach to organizational structure and staffng required to support this new business practice. Many retailers have optimization applications in place; however, the business users may distrust or simply ignore the output. This is a chronic symptom of organizational distrust and/or lack of understanding.
Algorithms will be used by retailers to ensure that business activities optimize sales for targeted customer segments across the retailer's business. They will also provide operation effciencies through automation of non-value-added, repetitive and complex data-driven tasks. Different than just optimizing one process or task area, algorithmic retailing will ensure that the retailer's entire
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organization is operating at peak effectiveness. With the advent of IoT use cases, the need to manage the business through algorithms is undeniable.
Use Gartner research to grow your understanding of algorithms and smart machines, and begin to identify initial areas of application such as algorithmic optimization of merchandising activities or in- store task management. Work closely with business leaders to identify organizational impacts and plan for change management to address.
Business Impact: We expect business units such as planning, supply chain, merchandising and marketing to continue leading the usage of algorithmic retailing through the use of optimization technology. Increasingly, customer-facing areas such as in-store and call centers will embrace algorithms to drive customer support activities. Presently, we estimate that up to 50% of retailers have adopted some form of algorithmic optimization application, and expect algorithmic retailing will grow from its current penetration relatively quickly.
Benefit Rating: Transformational
Market Penetration: 1% to 5% of target audience
Maturity: Emerging
Sample Vendors: IBM; Oracle; SAP
Recommended Reading:
"Algorithmic Retail: Merchandising Leads the Way"
"Predicts 2016: Digital Business Uproots Traditional Retail Revenue Generation"
"Explore Algorithmic Business to Drive Differentiation"
"Smart Machines Will Be the Catalyst for One of the Most Disruptive Eras in Retail"
Retail Distributed Order Management Analysis By: Tom Enright; Miriam Burt; Joanne Joliet
Definition: Retail distributed order management (DOM) applications are used to orchestrate and optimize the customer order fulflment process to deliver target service levels in terms of fll rate, accuracy of orders, and on-time, cost-effective delivery.
Position and Adoption Speed Justification: DOM is an emerging, but growing, solution in the retail market and is new on this Hype Cycle. The core components of DOM include:
■ An enterprise view of inventory available for order fulflment.
■ Details of customer orders for fulflment.
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■ A confgurable rule engine that determines and orchestrates how orders can be fulflled from available inventory.
■ The capability to instruct other systems in distribution centers, suppliers or stores to implement the physical fulflment process. This includes pick, pack and dispatch from available inventory as well as capability to manage returns.
Today, many retailers fulfll customer orders either using legacy systems that were not designed to support multichannel or by integrating other systems, such as ERP, warehouse management systems (WMSs) and e-commerce platforms. Cross-channel shopping processes, such as buy online, pick up in-store/click and collect, are becoming more and more popular with consumers. As a result, retailers will need to move toward the use suites of DOM-packaged software to handle the increasing complexity of order management and support future shopping methods offered by retailers. In addition to delivery to consumers' homes, or picking up or returning from store, retailers will have to offer, for example, locker pick-up schemes, or ordering and fulflment in locations in transport areas such as subways or train stations.
Vendors have entered this market through different routes. Some have adapted DOM solutions for other industries to service multichannel fulflment in the retail environment. Others have built DOM software specifcally for the retail industry. The vendors differ in size, from new niche entrants to larger global vendors, with some offering software suites well beyond the boundaries of the scope of DOM. As part of the ongoing roadmap for DOM, we expect vendors to develop related in-store fulflment and picking capabilities. We expect vendors also to support CPG companies who are starting their own direct-to-consumer digital business offerings.
We have positioned retail DOM as post trigger 20%. Although it has slowly been emerging over the past 36 to 48 months, we have seen increased levels of hype in the past 12 to 24 months as retailers are having to seriously engage with the increasing complexity in cross-channel ordering and fulflment processes. Current adoption rates are between 1% and 5% in the retail market, with vendors' primary focus on nonfood retail environments, such as apparel and footwear. We expect retail DOM to take fve to 10 years, likely nearer fve, to reach maturity on the Plateau of Productivity.
User Advice: As retailers increase the methods by which consumers can order and fulfll products to their convenience, they must assess the level of order fulflment complexity. They can do this by mapping the customer and business processes in the various permutations and combinations for customer ordering and customer fulflment.
They should also map out the integration points between DOM and other applications involved in customer ordering and fulflment. For example, synthesis of point of sale (POS) with DOM is a prerequisite to enable "buy anywhere, fulfll anywhere, return anywhere" capability. The mapping can be used to prioritize investments in DOM functionality and also determine the timing for starting the selection process with the shortlisted vendors.
Retailers should also build DOM capabilities to meet future fulflment complexity and include in- store fulflment as a component of their application roadmap.
Business Impact: With DOM, retailers are able to more easily cope with the complexity of cross- channel order management and fulflment. DOM helps retailers improve multichannel order fll rates,
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increase the accuracy of order picks, improve delivery on time, shorten cycle times, reduce the cost of order management, reduce the amount of buffer stock, optimize shipping on delivery and leverage new fulflment strategies.
Benefit Rating: High
Market Penetration: 1% to 5% of target audience
Maturity: Emerging
Sample Vendors: Demandware; IBM (Sterling Commerce); JDA Software; Kibo; Manhattan Associates; Radial; SAP Hybris; Softeon; Symphony EYC
Recommended Reading:
"Market Guide for Retail Distributed Order Management Systems"
"Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
Digital Workplace Analysis By: Kelsie Marian
Definition: A retail digital workplace is an ongoing, deliberate approach toward delivering a more consumerlike computing environment that is capable of facilitating a fexible response to workplace changes and, in turn, improving both employee and customer experiences.
Position and Adoption Speed Justification: A digital workplace is an approach that requires employees to be far more socially engaged, available, willing to accept changing roles and responsibilities, and innovative in their use of technology. This transformation has been driven by the consumerization of retail through technologies such as cloud, mobile, social and big data, and will be further driven by the Internet of Things (IoT). Investment in these technologies will play a key role in the execution of retailer digital business strategies by facilitating connections that will act as a key point of differentiation in the customer experience. As a result, retailers and their employees will be charged with creating and sustaining digitalized cross-channel shopping experiences with more consumerlike technology. Gartner estimates that less than 1% of Tier 1 retailers currently operate digital workplace environments, although several large retailers have initiatives underway.
User Advice: Real-time informational needs are giving rise to next-generation employees and associate-facing solutions — for example, the consolidation of everyday store-associate-facing applications on a mobile device, using a common application framework with access to real-time data such as location-based information from a consumer's mobile device or in-store monitoring devices and beacons. In addition, emerging technologies such as virtual personal assistants (VPAs) can observe employee behavior and predict future behavior and needs, and, eventually with permission, act autonomously on their user's behalf and enable employees to be more productive and create a positive customer experience.
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As a result, customer master data management — along with multichannel content management systems — and real-time data platforms will be necessary to enable the digital workplace environment and quickly make good decisions in and across channels. Although some retailers may be in a position to use real-time data platforms and technologies, it is less likely without good data management and speedy execution to impact the customer experience and entice customer loyalty.
Retail CIOs must now investigate current data and content management processes and solutions to determine organizational readiness for acquiring, maintaining and acting on real-time data in and across channels to support a retail digital workplace.
Business Impact: Retail CIOs are in a unique position to promote the retail digital workplace by strategically responding to a series of interconnected societal trends such as digital lifestyles, changing work models, data intensity, and a willingness to share and collaborate. Done well, the retail digital workplace delivers a more mobile, social, accessible and data-driven work environment that is better able to exploit changing conditions and positively impact the customer experience.
Benefit Rating: High
Market Penetration: Less than 1% of target audience
Maturity: Emerging
Sample Vendors: JDA Software; Kronos; Nead Werx; OneView Commerce; Refexis Systems; WorkJam
Recommended Reading:
"Retail Digital Workplace Transformation Imperatives"
"Retail CIOs Must Employ Cross-Channel Task Management to Optimize the Customer Experience"
"Hype Cycle for Digital Workplace, 2015"
Customer Engagement Hub Analysis By: Kelsie Marian
Definition: The customer engagement hub (CEH) is a process concept that ties multiple technology systems together to optimally engage the customer. A CEH includes inbound and outbound customer communications; allows personalized, contextual engagement with customers across all interaction channels (including social, mobile and in-store); and reaches and connects all departments. This allows for the synchronization of marketing, in-store and customer service processes.
Position and Adoption Speed Justification: Over the next several years, leading retailers will extend their CRM technology goals by tying together disparate systems across the business in a more holistic approach that focuses to better provide a consistent view of the retailer to the customer and pivots around customer needs. For example, large retailers must revisit their existing
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CRM applications, mobile development tools and web technologies to architect a hub to be used by all departments, including marketing, sales, digital commerce, customer services and logistics. The goal of the customer engagement center is to extend and provide customer support and interaction to social media, such as Facebook and Twitter, as well as online community activities. Other departments such as marketing, digital commerce and sales will join with IT leaders to develop plans for the CEH. Without the coordinated planning a CEH provides, it will be diffcult for the retailer to exploit the advantages of digital business capabilities. In 2015, less than 5% of Tier 1 retailers have the technologies and processes in place to provide a consistent customer experience across departments and channels. The need to support the anytime-anywhere customer (including on mobile devices and smart devices, and in social networks) and heightened business awareness is making this a top issue for retailers. The CEH will be part of a broader social CRM suite offering within eight years. The CEH can be used by all departments: marketing, sales, customer service, logistics and others.
User Advice: IT leaders assisting customer care directors, chief marketing offcers and digital commerce leaders (since the CEH can be used by all departments, for all inbound and outbound customer interactions) should conduct an inventory of the key marketing processes that not only drive customer satisfaction, but also foster customer engagement and employee collaboration. Test the ftness of CRM-oriented applications to fulfll the needs of the engaged customer. Look at vendor roadmaps, and assess the vendor's and organization's readiness to evolve customer engagement processes and technologies. Identify areas for improvement before approaching IT for support or funding.
Business Impact: An emerging CEH will foster personalized engagement with customers across all interaction channels, including social, and will reach across all departments in the enterprise. The CEH will support the transition from transactional economics to a more comprehensive view of customer relationship economics. The issue of customer engagement and care will become a more systemic theme across the enterprise as CIOs strive to hit their goal of retaining customers as a way to grow revenue and infuence customer buying behavior; thus, a CEH will be required to support these initiatives. It is not yet clear how this will impact the software market, but software vendors that neglect the shift will lose market share. At this stage, most of the components of a customer engagement hub are not bundled as a suite. It is likely the CEH will remain a system of systems and never evolve into a product. Vendors tend to focus on what can be mass-produced and easily sold, rather than on products that can transform a business but require complex buying centers and change management. This limits the feasibility of a true CEH. However, the issue of siloed customer engagement is gaining the attention of business and IT leaders, as well as software vendors. We anticipate that large CRM software vendors will increase new capabilities to bridge this gap through acquisitions, partnerships with system integrators and their own R&D efforts.
Benefit Rating: High
Market Penetration: 1% to 5% of target audience
Maturity: Emerging
Sample Vendors: Oracle; SAP; Teradata
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Recommended Reading:
"Market Guide for CRM in Tier 1 Retail"
"Improving Loyalty and Retention in Retail Primer for 2016"
Project P2P Solutions Analysis By: Deborah R Wilson
Definition: Project procure-to-pay (P2P) solutions are work-stream-specifc enterprise applications confgured to help organizations track and manage spending for a specifc project, such as a retail store refurbishment, a construction project, a marketing campaign or a research project. Unique features include the ability to manage a project budget, project templates to identify standard purchases associated with a project, elaborate workfows that support project spending gates, and exception reporting to highlight critical path deliverables.
Position and Adoption Speed Justification: Project P2P solutions have emerged to serve the unmet need of organizations to plan and manage projects that revolve around outsourced services and goods. There are few players in this emerging market, and these players are not widely known. Project P2P solutions will progress at a moderately slow pace through the Hype Cycle as vendors learn from early adopters and become more successful at selling, scaling and increasing marketing spending. This is likely to take several years because project P2P functionality is not a universal need — it is a requirement for specifc industries such as retail (for store construction and refurbishment), entertainment (for movie projects, for example), higher education (for managing grants) and general construction (for buildings and public works). We predict that this capability will be delivered as a feature of a general-purpose P2P solution, which will make this technology obsolete before the Plateau of Productivity.
User Advice: Organizations with more than $50 million in annual spending for projects that require expertise in ordering, managing and synchronizing goods and services orders should evaluate project P2P solutions for agility, but also as means to achieve granular control and governance. Organizations seeking project P2P solutions should evaluate software designed to handle their particular type of project (for example, store refurbishment), as well as general-purpose P2P solutions. Some general-purpose tools are sophisticated enough to handle the job.
Business Impact: Like all work-stream-specifc solutions, P2P project solutions can improve effciency and effectiveness by an order of magnitude over general-purpose P2P solutions deployed in a standard way. Implementation is far faster because the solution is purpose-built, and time need not be wasted trying to bend and confgure a regular P2P product. Because these solutions address only a portion of an organization's overall spending, we give them a moderate beneft rating.
Benefit Rating: Moderate
Market Penetration: 1% to 5% of target audience
Maturity: Emerging
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Sample Vendors: Asite; Basware (Verian); Determine; Ivalua; Lumatrak; MyBiz; SAP Ariba; Wax Digital
Recommended Reading:
"Magic Quadrant for Procure-to-Pay Suites for Indirect Procurement"
"2015 Strategic Roadmap for Automating the Procure-to-Pay Process for Indirect Goods and Services"
"Building a Compelling Business Case for Indirect Procure-to-Pay Technology"
Intelligent Virtual Store Design Analysis By: Robert Hetu; Ed Porter
Definition: Intelligent virtual store design uses scientifc space-planning techniques, including system-generated recommendations, to enhance the effectiveness of store-specifc spatial assignment of fxtures, services, categories and merchandise in a physical store. 3D visualization provides the ability to experience the plan from a customer perspective using virtual reality.
Position and Adoption Speed Justification: Changes in customer shopping habits and the resulting trend toward smaller formats require a higher degree of differentiation in store assortments and confgurations across multiple store locations and formats. This need for extensive customization to support customer-centricity will require a signifcantly more advanced scientifc approach than the combination of traditional AutoCAD store design, Excel spreadsheets and a physical layout center that are typically part of the store layout planning processes for remodels, new stores and periodic business reviews.
Scientifc modeling, including advanced analytic capabilities, such as predictive analytics and pattern matching, provides precise recommendations for the placement of categories to maximize sales to customers frequenting each specifc store. Infusing customer behavior and profling dynamics into the consideration set, and the ability to visually consider many additional possibilities, will likely lead to signifcant changes in how product categories and services are deployed. This also provides a tremendous new collaboration opportunity for retailers and suppliers to share information, cost-effectively test new concepts with consumers and ultimately ensure that customers are better served.
This technology will progress rapidly toward the trough as retailers and manufacturers begin to explore alternative methods to facilitate the sell-in of new products, merchandising, and category space allocation and overall store design. We expect further development of these capabilities by existing space-planning providers, as well as partnerships and acquisitions, such as the recent combination of Fifth Dimension and Symphony EYC, and Kantar Retail Virtual Reality's acquisition of Red Dot Square Solutions.
User Advice: Bring the store format, merchandising, marketing and consumer insight functions together to determine how this technology can best be used and deployed in your organization.
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Defne clear business goals and expectations before vendor assessment is undertaken. Consider the roles that your product vendors should play and the consumer and product information needs you will have. In-depth understanding of every store confguration will be required to ensure that the planned spatial allocation is feasible in practice. The location of check-outs, stockrooms, click and collect, and other services must be considered to ensure the best possible experiences for customers at all times. Virtual displays, such as 3D sales foor representations, allow the store- planning users to experience the design and help prevent unwanted results on execution of layout changes in the store. Look for applications that work in conjunction with AutoCAD systems to ensure easy integration with the store design. Seek integration with shelf-space planogram applications and other merchandising applications supporting assortment planning and category management.
Video analytics and in-store monitoring software can also play an important role by providing relative information on shopper behavior in the store. Most vendors are U.S.-based, with several newer frms in Europe and Latin America. Many have project experience in Europe, South America and Asia, in addition to North America. Startup investments will be required to construct the 3D shelf environments for a particular category of products and a particular retail environment if it has not already been constructed by the vendor. Once the initial investment is made, then it is a matter of updating images and running scenarios on a project or retainer basis.
Business Impact: Use of this technology will allow retailers to more quickly and more effectively develop new store layout concepts and to more effectively evolve current prototypes. It will also allow retailers to more effectively customize their store layouts and merchandise assortments to local trade area needs, improving individual store assortments and, therefore, sales and customer satisfaction. Digital business opportunities will further stretch the possible uses for store space and inventory. Use of this technology will assist in testing, validation, and execution speed and accuracy for layout changes, new store planning and remodeling. 3D visualization will provide signifcant savings over the traditional methods of testing new layouts and merchandising ideas. It also creates innovation opportunities for retailers and manufacturers by offering economical alternatives to creating physical virtual store labs.
Benefit Rating: High
Market Penetration: 5% to 20% of target audience
Maturity: Emerging
Sample Vendors: APT; Buzz 3D; Dassault Systèmes; Decision Insight; Fifth Dimension Technologies; InContext Solutions; IVD; JDA Software; Red Dot Square Solutions
Recommended Reading:
"Implementing Customer-Centric Merchandising and Marketing in Retail Primer for 2016"
"Cool Vendors in Retail, 2016"
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Retail 3D Printing Analysis By: Miriam Burt
Definition: Retail 3D printing encompasses the use of a device to create physical objects from digital models to provide custom-designed stock items for the retail supply chain, as well as to provide printing services to consumers.
Position and Adoption Speed Justification: Over the past 12 months, there has been a noticeable increase in retailers in a variety of segments, such as jewelry, home improvement, offce supplies, warehouse clubs and even food, embracing 3D printing in many geographies. Amazon even has a patent fled for 3D printing on-demand using trucks as mobile manufacturing hubs. This furry of activity has caused this profle to move from pre-peak 35% to pre-peak 25%. Advances in 3D scanners, design tools, the commercial and open-source development of additional design software tools, as well as workfow software to manage the 3D production process have contributed to making this technology more accessible and affordable for customization.
As well as selling 3D printers to consumers, many retailers have partnered with 3D printing vendors to implement in-store and online 3D printing and scanning services. In reality, many retailers are still investigating and experimenting with this technology and we have marked this as having adoption levels at between 1% and 5%. We expect it to be nearer to 10 years than fve before it reaches the Plateau of Productivity.
User Advice: Large multichannel retailers must begin exploring the use of this technology by:
■ Experimenting with low-volume manufacturing of high-margin, custom-designed pieces (for example, fashion jewelry, eyeglass frames, handles for cabinets and objects such as fgurines and phone cases).
■ Investigating and evaluating how 3D printing technology can support digitalization of cross- channel processes while deploying this technology to support the customer service basics, such as stock availability. Warranties and after-the-sale service and support are also important.
■ Giving due consideration to how they can collaborate with customers for generation of innovative designs, including the resolution of issues around content creation, intellectual property and monetization models.
■ Conducting analysis and exercises to model the impact on back-end-supporting applications, such as how 3D printing applications will integrate with stock management and replenishment applications to accommodate real-time stock adjustments that arise as a result of printing stock on the spot.
■ Working with legal advisors and compliance offcers to fnd out how to manage the risks of violating or infringing copyright and patent laws, particularly with regard to the intellectual property associated with CAD designs, as well as the risk of catastrophic failure of items that were 3D printed by customers.
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■ Remembering to factor in the operational cost of the associated ecosystem (for example, the procurement and supply chain costs of raw materials and printer parts) when building a business case for 3D printing.
Business Impact: The demand for this type of custom manufacturing refects two increasingly important retail trends that retailers can capitalize on to drive revenue: consumers' expectations of stock availability and their desire for personalized and customized products, services and shopping experiences. 3D printers could also be used to generate cost-effective operational equipment such as sign holders, promotional stands and in-store hardware.
Gartner believes that consumers will use this technology to drive a transformation of the retail industry by encouraging digitalization of the retail business. By this, we mean that consumers are forcing the offine and online channels to work in concert to deliver the key retail business process of ensuring stock availability in new and innovative ways. It could also make the retailer less reliant on their CPG and manufacturing suppliers, particularly for on-time delivery of stock.
Benefit Rating: Transformational
Market Penetration: 1% to 5% of target audience
Maturity: Adolescent
Sample Vendors: 3D Systems; Hasbro; i.materialise; Mattel; Mcor Technologies; Sculpteo; Shapeways; Stratasys
Recommended Reading:
"Survey Analysis: Retailers Need to Rethink Multichannel as Digital Channels Increasingly Drive Store Revenue"
"Top Retail Business and Technology Trends"
At the Peak
Digital Wallets in Retail Analysis By: Miriam Burt; Joanne Joliet
Definition: A digital wallet solution is an electronic vault, where a person's credentials related to payment cards, account details and/or IDs, identifcation cards, loyalty programs and other sensitive data are stored securely and accessed from an interface on an electronic device. The credentials can be stored in the device and/or on a remote server.
Position and Adoption Speed Justification: Digital wallets store money and/or multiple debit and credit card account details as data and have functionality for users to set preferences for transaction payment options, loyalty and fnancial management purposes.
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In the past 12 months, there have been very high levels of hype on digital wallets. Mega retailers' efforts in this area, for example Walmart and Target's payment and wallet initiatives, have accelerated retailers' willingness to seriously investigate digital wallets as a credible way of deepening their relationship with consumers and improving "stickiness" through their loyalty offerings, as well as to encourage adoption of mobile payments. Moreover, retailers, as payers of merchant fees, see digital wallets as a way to optimize the payment ecosystem in their favor. In the example of Chase Pay's tie up with U.S. retailer consortium led Merchant Customer Exchange's (MCX) QR code-based CurrentC wallet offering, Chase can install its credit and debit cards in the wallet and the retailer's acquiring processor, and card network is bypassed through a direct switching model. Chase, which is the consumer banking arm of J.P. Morgan, does not charge network or merchant processing fees, and will also protect the retailer from fraud liability.
Over the past year, there has also been increased vendor activity on standardization of processes — such as tokenization and the provision of white-label mobile wallet platforms — to enable the retailer to integrate mobile payments, loyalty programs, offers, coupons, receipts and other related commerce services by integrating through vendors' APIs and software development kits (SDKs). More social messaging app providers, too, have entered this market. Increasingly, digital wallet solutions for wearable devices are also emerging, for example, wallets integrated to clothing or in smart watches.
The high levels of interest in retailers as well as the feverish activity in the vendor market has seen this Technology Profle accelerate rapidly forward to pre-peak 15%. Customers expect a secure, quick and easy cross-channel payment process with a reasonably wide choice of payment options to suit their convenience. However, a major barrier to adoption is consumers' security concerns, which keep them circumspect on any mobile payment technology, especially Near Field Communication (NFC)-enabled "contactless" payments made through mobile phones. At least one digital wallet rollout in a signifcant retailer has stalled. The Apple Pay wallet does not appear to be able to sustain previous high usage levels. Moreover, a plethora of digital wallet solutions fooding the market at once is confusing customers. For these reasons, adoption in Tier 1 multichannel retailers is still quite slow.
We expect this technology to shift more rapidly toward the peak in the next 12 to 18 months, particularly as digital business gains ground and payments become more and more integrated with IoT and smart machine technology.
User Advice: Retailers:
■ Understand how consumers prefer using their mobile devices when shopping, for example, when researching or buying, or how the shopping process is impacted by the convergence of mobile and social. This will help you to prioritize technology investments.
■ Prioritize security by ensuring that implementations include standard functionality, such as encryption, tokenization and digital certifcation, and that implementations ensure strict and sustainable compliance to industry standards, such as Payment Card Industry Data Security Standard (PCI DSS)/Payment Application Data Security Standard (PA DSS).
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■ Invest in educating customers in the benefts of using alternative forms of payment, as well as providing good training to their associates on operational requirements.
■ Consumers continue to be heavy users of cash in all the major geographies. Offer relevant, cost-effective incentives to move consumers from cash to digital payments made via cards or mobiles.
■ Focus on delivering a smooth and rich customer experience, especially at the start. Retailers must model the business and technology requirements to deliver the end-to-end payment process, including integration of loyalty requirements. In order to offer personalized shopping experiences, they must take into account many variables regarding customer preferences, including their expectation to accumulate and redeem loyalty points in and across the channels.
■ Implement nontransactional services — for example, to allow customers to manage their loyalty accounts on one platform, manage their expenses, as well as store transport or theatre tickets. Therefore, retailers will also need to look at how both digital and paper-based promotions and offers, such as those delivered through mobile and social channels, tie into digital wallet functionality.
■ Investigate how IoT can be integrated with payments to deliver a convenient and secure customer shopping experience.
■ Collaborate with technology providers, card and payment schemes, and banks to optimize merchant fees as well as to make the customer payment process as smooth and hassle-free as possible.
Business Impact: If used in the appropriate retail operational context, digital wallets have the potential to positively impact retail operations metrics. They could deliver good productivity gains and operational effciencies (for example, in increased throughput at the check-out). Digital wallets could also deliver incremental sales revenue through higher conversion rates, as well as better chances of repeat spend as a result of delivering a smooth, fast and secure customer experience, together with personalized offers.
Benefit Rating: High
Market Penetration: 1% to 5% of target audience
Maturity: Emerging
Sample Vendors: Alipay; Apple; Google; Merchant Customer Exchange (MCX); PayPal; Samsung
Recommended Reading:
"Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
"Think Digital Wallet Functionality First — Your Customers Do"
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Cognitive Expert Advisors Analysis By: Kelsie Marian; Kenneth F. Brant; Miriam Burt
Definition: Cognitive expert advisors" (CEAs) replace "smart advisors" this year. CEAs, at a minimum, possess a specialized algorithm plus machine learning and natural-language processing functions tuned specifcally to a purpose-built, curated body of big data to generate insights, discoveries, recommendations and decisions. CEAs must be purposely designed and built, then rigorously trained to produce "expert" advice — they are not effective or "cognitive" without the participation of human subject matter experts in development and operation.
Position and Adoption Speed Justification: This technology profle replaces what was previously published as "smart advisors" because the term "cognitive computing" has been more hyped and commonly accepted in the marketplace. The position is now near the Peak of Infated Expectations because of the prominence of IBM's Watson (a question-answering prototype playing "Jeopardy") in popular culture and the subsequent creation of IBM Cognitive Business Solutions, which has heavily promoted the term cognitive computing in association with its expert advisor offerings. Today, many major vendors have embraced the term "cognitive computing" with respect to their expert advisory platforms. The accuracy and productivity of these systems today is still being tested and proven. Even when initially successful and value is discovered, the systems can be fragile, requiring frequent troubleshooting, retraining and upkeep of the big data in order to produce desirable, actionable results. We believe it will take considerable time for these deployment and maintenance issues to become manageable and accepted by the majority of enterprise users with a dependable service level. The issues are not strictly technological, but involve a considerable amount of vision, risk, leadership and commitment to change management on the part of enterprise champions. Plus, the skill sets and practices to be successful with this class of technology are not the same as those associated with the typical IT project, nor are they found in the typical line of business (LOB) or strategic business unit (SBU) leading the mission.
User Advice: For retailers, high labor costs are intersecting with needs for big data exploration and highly individualized consumer experiences — therefore, retailers should develop a multiyear strategic plan (with proposed business cases, feasibility studies and vendor evaluations) for smart advisors.
Strategic business unit and/or LOB leaders need to champion these early programs and incubate an exploratory and learning mentality.
Recognize that this is a major shift in the way you will do business, and commit adequate time and resources to the long-term development of smart advisors — do not expect quick success and returns.
Pilot several cognitive expert advisors and assess the best ft against your use cases, including ease and cost to maintain over the long term. Consider both operational improvement and big data exploration benefts; pilots should assess the advisors' ability to reduce costs and improve service levels and also determine their ability to discover new commercial avenues in big data. Make sure to assess employee and customer acceptance and use fndings to justify and prepare for the change management programs that will be necessary in deploying smart machines at scale.
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Business Impact: The potential business impact of cognitive expert advisors is great in retail due to the presence of big data and the growth of dynamic and largely unstructured data. This is compounded by the need for highly individualized business decisions and customer recommendations.
Smart advisors promise:
■ Faster R&D breakthroughs and time to market
■ Greater returns on promotional spending decisions
■ Lower costs of complex customer service
■ Greater availability and reliability of complex customer service
■ Differentiation of complex customer service and brand enhancement
The cost and complexity of developing cognitive expert advisors put them out of the direct reach of the large majority of consumers for the near future. We expect consumer usage will be accessed via enterprises that have deployed smart advisors and made them available to their customers as a premium, brand-enriching service through at least 2017.
Benefit Rating: Transformational
Market Penetration: Less than 1% of target audience
Maturity: Emerging
Sample Vendors: CognitiveScale; IBM Cognitive Business Solutions; IPsoft; Sentient Technologies
Recommended Reading:
"Industry Vision: Reimagining the Retail Store With Smart Machines"
"Cool Vendors in Retail, 2016"
Social Employee Recognition Systems Analysis By: Kelsie Marian
Definition: Social employee recognition systems transform traditional recognition programs with informal feedback and rewards delivered through social networking tools. Solution components typically include private or public feedback, gamifcation concepts such as badges, "likes" and points, and may include the administration and distribution of gift cards, points and other rewards. Usually run as stand-alone programs, they may also be integrated into formal talent management processes and are increasingly becoming part of digital workplace initiatives.
Position and Adoption Speed Justification: Traditional recognition programs have centered on tenure-based programs and involved awarding employees gifts, such as merchandise and gift cards. Over the past few years, we have seen rapid growth in systems that leverage social software
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concepts and mobile accessibility to revolutionize the process of employee recognition. As a result, social employee recognition systems are a new addition to the retail Hype Cycle. An important element of these new tools is the transparency of the recognition process; the tools make it easy for colleagues and managers to provide recognition and thanks for performance, and to nominate people for recognition awards. The increasing element of gamifcation in these systems encourages regular participation, but employee motivation is more complicated than just paying bonuses and engaging in competitions. Data from these systems may also be combined with workplace analytics initiatives in order to gauge and measure employee engagement. Social recognition solutions combine the benefts of intrinsic motivators (for example, achievement, purpose and mastery) reinforced by extrinsic motivators (for example, cash, points and other rewards). Today's tools deliver analytics to measure the activity and impact of recognition programs and are delivered through mobile devices to accelerate and sustain utilization
User Advice: Recognition systems are not an alternative to equitable and effective compensation practices. They should complement, but not replace, bonuses and merit awards. Invest time to understand newer concepts, such as badging and gamifcation, to encourage participation. Do not assume the recognition model you deploy in the U.S. will work in other geographies. Align the recognition program with corporate goals and strategies, and spend time educating managers and employees about the effective use of the program. Ensure that any awards' guidelines are clearly defned, and that you deploy the program consistently and modify program details based upon regular review of program metrics, including segmented participation levels and business impacts. Programs jointly designed by employees and managers are more likely to get buy-in, and will improve engagement and participation. Social recognition need not be limited to an individual, as some tools support group recognition at the team or community level.
Executive support and active engagement are critical to the success of such programs. Without the proper upfront planning, training, communication and executive support, launching social-based programs can actually have a negative effect on employee engagement and program objectives. Look to benchmark with organizations that have an organizational culture similar to yours, and be prepared for the cultural changes that will come with the introduction of social technologies. Recognition must be tightly aligned with the organization's business objectives, mission and corporate values, but does not necessarily have to be tightly integrated with formal performance and compensation programs. Carefully examine the global, mobile, integration, reporting and analytics capabilities of prospective vendors. TMS/HCM suite vendors may have more broadly integrated workfows with related talent processes, but specialist vendors typically have deeper capabilities in the actual rewards management as well as added consulting/marketing support resources for ongoing program support.
Business Impact: Social employee recognition systems amplify the reach of recognition events to improve intrinsic motivation for sustained workforce engagement. The engagement connection is critical because the link between employee engagement and business performance is well- documented — such as improved operational effciencies; higher employee engagement, productivity and quality of service; increased customer satisfaction and retention; and increased revenue and proftability (see "Social Employee Recognition Systems Reward the Business With Results"). Misaligned recognition programs can actually have a detrimental effect on employee engagement and business outcomes. Well-designed and actively managed social recognition
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systems can provide daily reinforcement of company values and transform periodic recognition events into a culture of continuous recognition and engagement, driving tangible business outcomes.
Benefit Rating: Moderate
Market Penetration: 1% to 5% of target audience
Maturity: Emerging
Sample Vendors: Achievers; Kudos; WooBoard; WorkJam; Workstars
Recommended Reading:
"Retail Digital Workplace Transformation Imperatives"
"Retail CIOs Must Employ Cross-Channel Task Management to Optimize the Customer Experience"
Augmented Reality in Retail Analysis By: Miriam Burt
Definition: Augmented reality (AR) is the real-time use of information in the form of text, graphics, audio and other virtual enhancements integrated with real-world objects and presented using a head-mounted-type display or projected graphics overlays. It is this "real-world" element that differentiates AR from virtual reality. AR aims to enhance users' interaction with the environment, rather than separating them from it.
Position and Adoption Speed Justification: Strong adoption and quick evolution of mobile technology have fueled retail AR trials and implementations in the past 18 months. In consumer- facing environments, AR is being used, for example, in AR-based product information, AR-based virtual dressing rooms, and AR converged with virtual reality for modeling projects such as kitchen upgrades or replacements. On the business side, AR apps are beginning to be used to access full catalogs of products through smartphones and tablets anywhere and anytime, or to visualize packaging in real time and in a real-world environment so that a model that doesn't as yet exist can be placed in multiple places to see what it looks like. This can be used to iterate and test new designs faster and reduce time to market. Retailers are also beginning to trial AR solutions for better productivity; for example, for optimizing store foor merchandise in compliance with prescribed planograms.
In the past 18 months, a furry of vendor activity on development of tracking, imaging, mapping, modeling software and various developer tools has driven AR hype. Google has also opened up its API for TensorFlow — its machine learning software library for applications such as facial detection and landmark detection — and Apple acquired Emotient, an emotion recognition company, at the beginning of 2016. The convergence of AR with virtual reality (VR) under the "immersive technology" umbrella has also sparked interest.
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These reasons have increased the hype and "heat" in this market, which sees this technology move rapidly upward to pre-peak 5%, peaking next year as digital business facilitates the convergence of this technology profle with social, mobile and VR.
AR will become an important vehicle for digital business as it overlays digital content on real-world views and can be the interface for the Internet of Things; for example, as an immediate and visual medium to display a lot of data clearly and quickly.
However, adoption rates are nearer 5% than 20%, as a huge hurdle for AR is the sourcing, creation, authoring and porting of content. Moreover, current technology is best-suited for purpose-built, specialized solutions, as internal, employee-facing solutions and external, customer-facing solutions are not transposable.
User Advice: To avoid implementing AR as a gimmick, functionality should be reviewed in the light of how AR will support customer expectations in the shopping process as well as improve employee's performance in operational execution. Restrict initial trials to a specifc task or goal. Set benchmarks against unaugmented solutions to understand risks and benefts. Retailers should also investigate how AR can complement their digital business efforts as it converges with other technologies such as social and VR.
Moreover, due diligence should be performed on the integration of AR with crucial "back-end" processes and applications. A key consideration in this regard is the integration of AR with applications driving multichannel master data management, multichannel content management, real-time offer engines, and, very importantly, applications and processes supporting visibility of cross-channel inventory.
Retailers should also remember to tie up their promotions driven by AR experiences to the other channels because customers also expect retailers to deliver a consistent cross-channel shopping experience.
AR can also be used by retailers to drive collaboration with consumer packaged goods (CPG) and manufacturers; for example, to enhance retail execution through collaboration in the visualization of planning of product placement on the shelf.
Very importantly, retailers should investigate how AR can complement their digital business efforts, bearing in mind consumers' privacy concerns regarding wearable devices that have, for example, always-on cameras. For the fashion-conscious, head-mounted gear, for example, may not be appealing in terms of aesthetics.
Business Impact: Retailers can use AR as an extension of the brand experience as well as to enhance internal productivity.
For example, in more immersive environments, such as the store or on tablets, interaction with AR applications could drive conversion from interest to actual sales. As the digital channels push more traffc to the store, in-store AR applications could be used, for example, to give the customer detailed information when purchasing complex products or when trying on apparel in a virtual dressing room. AR can also be deployed to enhance store productivity and in-store design. Outside
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the store, AR can be used to help customers visualize products in situ. It can also be used postsale (for example, easily downloadable AR manuals for do-it-yourself projects) to increase customer satisfaction, improve loyalty and encourage positive customer recommendations to other consumers who have yet to make their purchasing decisions.
Benefit Rating: Moderate
Market Penetration: 5% to 20% of target audience
Maturity: Emerging
Sample Vendors: Apple; Aurasma; Blippar; Google; IBM; Zugara
Recommended Reading:
"Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
"Market Guide for Augmented Reality"
Multichannel Location Analysis Analysis By: Miriam Burt
Definition: Multichannel location analysis involves researching and evaluating optimal locations for developing proftable physical stores and other customer-facing locations in conjunction with market analysis of digital channels such as e-commerce and m-commerce.
This comprises the use of location analysis techniques, including the analog method and gravity- modeling multiple regression analyses, as well as the use of GIS systems and trade market analysis tools to analyze multichannel market trading analysis in geographic areas.
Position and Adoption Speed Justification: The growth of e-commerce and m-commerce, the impact of large online retailers expanding into their categories, as well as changes to store portfolios as retailers enter and exit foreign markets are causing retailers to focus on rationalizing their store portfolios. One sign that retailers understand the signifcance of real estate to the business is the increasingly higher profle given to this area. For example, earlier this year, Macy's added a real estate executive to its board.
Retailers are looking to balance their store portfolio by "rightsizing" store operations, including continuing to build and open new stores. Moreover, customers' increased ability to use technology to shop at their own convenience has forced retailers to experiment with leveraging their stores and other customer-facing locations for fulflment models to suit customers' convenience. This includes initiatives such as "buy online pick up in store" and in drive-throughs. Trials and implementations of locker pickup schemes and pop-up stores are also increasing. Customer orders, pickups and returns can now also be done through locations in high-throughput and high-footfall areas such as train stations, metros and subways.
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A contributor to the current hype is the high level of interest in integration of real estate solutions with the Internet of Things (IoT). Smart building solutions with embedded sensors can optimize management of energy, security maintenance, utilities and room capacity. In addition, rather than relying just on historical or static data, such as valuation price, real-time data from the IoT, such as traffc or crime, can inform smarter site location decisions.
Currently at the peak of the curve, the adoption level is in the 5% to 20% range, though nearer to 5%. As retailers come to grips with the impact of the IoT on real estate, we expect this technology profle to move quite quickly in the next 12 to 18 months.
User Advice: Multichannel retailers need to ensure that planners for store and other customer- facing locations are provided with analytic applications and tools to help them optimize location planning in a timely manner. This will become increasingly important as retailers have to become fexible and agile in a volatile and fast-moving digital business environment fueled by the convergence of cloud, mobile, social, big data and the IoT. Retailers should investigate how the IoT can help them make better decisions regarding site location planning as well as in the construction of sustainable "smart buildings."
While there are many solutions in this area, no one vendor has the capability to entirely support a large Tier 1 multichannel and global retailer's requirements for multichannel location analysis. For example, while the use of GIS has become increasingly common for Tier 1 retailers, such systems need to be augmented by store location modeling and the application of practical retail reasoning, as well as by good "on the ground" local site knowledge.
Multichannel location analysis does not just impact store development teams, but also key operational areas in the context of multichannel strategies (such as marketing, merchandising, store operations and fulflment). Harnessing the expertise of these business areas will help mitigate the inherent risks associated with opening, closing and/or reformatting store locations and other customer-facing physical sites used for store-type operations, such as fulflment. Consider collaborative location planning activities with other brands in the group and also with consumer packaged goods (CPG), manufacturing and transport suppliers to optimize the end-to-end customer shopping experience; for example, partnering with other brands to offer more convenient fulflment in cross-channel processes such as buy online and pick up in the store/click and collect.
Business Impact: In a multichannel and fast-moving digital business context, planning issues are exacerbated because the key determinants of location — such as customer demographical analysis, trade area analysis and competitor analysis — are changing more dynamically than in the past and are becoming increasingly diffcult to predict. Achieving optimal locations to service cross- channel processes has become even more important than just store location analysis. Multichannel location analysis is becoming integral to enabling the retailer to evaluate and implement the best combination of physical stores and other customer-facing locations to enhance the shopping experience.
Location formats in particular store formats and the role and impact of other channels on stores are likely to change fuidly during the next fve to 10 years. One key success factor during this time will
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be having a rigorous methodology and the correct tools and technologies to determine optimum locations.
Benefit Rating: High
Market Penetration: 5% to 20% of target audience
Maturity: Early mainstream
Sample Vendors: Bricsnet; Esri; Experian; IBM; Pitney Bowes; Trade Area Systems
Recommended Reading: "Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
Master Content Management Analysis By: Miriam Burt
Definition: Multichannel (MC) master content management involves content for products, customers, employees and suppliers. Included in this defnition is structured content, such as master and other application data, as well as unstructured content — e.g., documents, images of forms, photographs, XML components, video clips and email messages.
Position and Adoption Speed Justification: The solutions are made up of core components, such as master data; document management; web content management; image processing applications; records management; channel content management, including social content and workfow management; and business process management. Other components can include digital asset management, search and analytics.
The past 12 months have seen continued consolidation in the vendor market, tools that once belonged in the realm of specialist vendors now being part of the large enterprise content management suites. These include enterprise fle synchronization and sharing (EFSS), video content management, although there is a gap in management of structured data. Cloud-based content management solutions for master data management (MDM), for example, to build and manage responsive websites, are emerging in the market. However, many large Tier 1 multichannel retailers express a reluctance to store proprietary customer or product data outside their frewalls, regardless of the use case involved and even in a private cloud scenario.
MC master content management projects are implemented mainly on the back of multichannel MDM projects. During the past 24 months, retailers have been trying to implement projects to improve the consistency of cross-channel content, such as pricing and promotions, as this is one of the key requirements for customers. MC master content management is also important for executing and maintaining relevant, cross-channel personalized offers and communications through email, text, web, call center and mailings. However, retailers are struggling to incorporate new types of unstructured content — for example, social media and picture-related information. There is also a dearth of vendors that can deliver this type of truly comprehensive MC retail content management solution, and retailers have to look to several vendors to fulfll all the core requirements for this type of solution. For these reasons, and the complexities that arise in large multichannel environments,
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the interest that retailers have shown thus far in this solution has yet to be converted into more adoption of full-scale implementation. Adoption remains slow and nearer to 5% than 20%.
With a slow downward movement, this technology is now just past the peak as retailers have become more cognizant of the bigger data management challenges posed by digital business — for example, through the Internet of Things (IoT) generating voluminous and complex data.
User Advice:
■ Before implementing an MC master content management system, perform due diligence on identifying and mapping the "as is" position on all of the sources of structured and unstructured data and information, where they are currently stored and how they are used in the context of the core retail business processes. This will afford opportunities to streamline business processes and help to remove redundancies and duplication in preparation for a phased implementation of an MC content management system.
■ To deliver cross-channel consistency, work on merging the metadata models for structured content (MDM and application data management) and unstructured content (enterprise content management [ECM]), with newly emerging "information stewardship" solutions taking the governing role.
■ Ensure that vendors have the ability in production or in the near-term roadmap to support digital business — in particular, support for mobility, social and the proliferation of data from the coming era of the IoT — as well as beefng up search and content analytics capabilities.
■ Large multichannel retailers should also be aware of the regional and global support and service capabilities that vendors are offering. Management of visual-based content, such as photographic images, is becoming increasingly important in the trend toward the convergence of social and mobile. Unstructured data generated by customers can also be used to foster collaboration for innovation, for example, bringing in content from customer activity in social media into merchandising plans.
Business Impact: Having a combined, consistent view of structured and unstructured content underpins the knowledge needed to make effective multichannel decisions in digital business.
The multichannel shopping experience has become a critical differentiator, with e-commerce, m- commerce and social commerce becoming increasingly important in providing consumers consistent content. Retailers are being driven to create, capture, manage, store and deliver content and documents related to MC customer and business processes to provide a single view of business information across the enterprise. Supported by good MDM and ADM, MC retail content management solutions will enable retailers to increase effciency in their core retail business processes to improve the multichannel customer shopping experience and minimize multichannel operating costs. For example, real-time feedback provided by customers through any channel can enable retailers to analyze structured data (such as store operation and contact center metrics) and to adjust staffng levels "on the fy." This will be very important in digital business, as, in a volatile and unpredictable environment, the decision makers will be relying on real-time access to high- quality data content to make critical business decisions.
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Benefit Rating: High
Market Penetration: 5% to 20% of target audience
Maturity: Adolescent
Sample Vendors: EMC; IBM; Oracle; SAP
Recommended Reading:
"Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
"A Real-Time Store Monitoring Platform Is Critical for Digital Business"
Smart Data Discovery Analysis By: Robert Hetu
Definition: Smart data discovery, including techniques such as predictive analytics, interactive data visualization, pattern matching, machine learning, natural language processing, complex event processing and automated decision support, is provided to business users through self-service interfaces.
Position and Adoption Speed Justification: Smart data discovery capabilities will drive human and machine decision making, helping the retailer compete in the digitalized marketplace. Incorporation of smart data discovery capabilities will improve the real-time business-decision- making process. Retailers that don't have advanced analytics capabilities in their technology toolkit could be toppled by an inability to capitalize on revenue opportunities presented by the Internet of Things. We renamed this profle to acknowledge the broader impact of advanced analytics with self- service delivery across the organization. This action, combined with the fact that many technology providers have approached this subject with a specifc focus on retail, continues to drive this profle past the peak. The speed of development for advanced analytics, combined with the implications of digital business, will cause this profle to progress relatively quickly.
User Advice: Acquire new tools that are much easier for business users than traditional business intelligence applications. Deliver advanced analytics in-process via inclusion in applications or through self-service. View this as a required preparation for the explosion of data from digitalization and the Internet of Things, where technology will be required to support human decision making. All of this is predicated on a high quality master data management (MDM) process to ensure data is accurate and available to the user. Likely places of opportunity reside in marketing, merchandising and store operations.
To ensure success, enlist help from business-unit heads to build a strong business case for investment by looking for opportunities across multiple disciplines to drive true customer-centricity. Invest in advanced analytics providers that specialize in retail, with awareness that some of the most innovative solutions may come from small vendors. Select a set of tools capable of delivering a diverse set of self-service and big data discovery capabilities, and integrate them with the existing
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BI and analytics platform. Extensive training and change management will be required to secure early wins. Use Gartner's business moments to educate the business community about digital business and the Internet of Things and its anticipated dramatic impact on the retail marketplace.
Business Impact: Retailers use smart data discovery tools to put information in the hands of business analysts and users to take advantage of signifcant potential to create business value and competitive advantage. Smart data discovery will transform the retail organization by providing the ability to analyze big data and take appropriate actions to expand business opportunities. The complexity of the retail organization structure and widely dispersed decision-making responsibility makes retail a prime opportunity to expand the use of advanced analytics in daily decision making. Impacts will include improvement of execution of the retail basics, such as having the right product available, knowledgeable sales staff, etc., thereby retaining and growing customer base, revenue and proftability.
Benefit Rating: Transformational
Market Penetration: 5% to 20% of target audience
Maturity: Adolescent
Sample Vendors: Applied Predictive Technologies; Epicor Software; IBM; Manthan; Oracle; Proftect; SAP; SAS; Tableau
Recommended Reading:
"Retailers Find Success Using Self-Service and Advanced Analytics"
"Critical Capabilities for Advanced Analytics Platforms"
"Algorithmic Retailing; Merchandising Leads the Way"
"Predicts 2016: Digital Business Uproots Traditional Retail Revenue Generation"
"Industry Vision: Consumer-Centric Ecosystems for Consumer Goods Manufacturers and Retailers"
Workforce Analytics Analysis By: Kelsie Marian
Definition: Workforce analytics comprises tools and analysis that enable retailers to improve employee performance, measurement and decision support throughout retail operations, thereby improving overall employee engagement and productivity, and positively impacting business outcomes. Applications consist of optimized scheduling, labor compliance, recruiting, training, succession planning, talent and performance management (including productivity, compensation and benefts), and analysis for increasing retention and reducing employee turnover.
Position and Adoption Speed Justification: Workforce analytics in retail uses workforce-related data to make resource planning and business decisions. It combines data such as employee
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engagement (employee surveys), social network data (customer review and satisfaction data), and business performance data (i.e., revenue or sales) to generate meaningful insights about the impact of employee performance and productivity on customer satisfaction and business performance. Additionally, attracting and retaining the right employees involve the analysis of employees who perform above average. While retailers have used transactional metrics such as cost per hire or turnover strategically for some time, the combination of these metrics to include analysis of unstructured data such as social or weather for predictive purposes is relatively new. We expect adoption will continue to grow as retail leaders recognize the impact of more sophisticated, predictive and prescriptive analytics to drive resource planning decisions, along with the ability to analyze and model the potential resource-related costs and risks as they relate to strategic business investments and emerging digital initiatives.
User Advice: Retailers are beginning to realize that employees are an asset in a competitive retail environment and have a direct impact on customer experiences. As a result, combining people- related data with channel performance and business data will assist in uncovering insights where changes should be made or successes replicated strategically across the retail organization. For example:
■ Using technology to identify applicants' social styles and applying predictive techniques to determine which candidates are the best fts for customer service roles.
■ Leveraging data from multiple sources, including schedule optimization tools and task-related information, to improve productivity and effectiveness, i.e., exploring how a customized mix of salary, vacation and professional development services impacts employee retention and customer satisfaction.
■ Using consumer-facing technologies to assist in making employees' lives better, for example, in encouraging corporate wellness as it is in the interest of retailers to have a healthy workforce/cut down on absences. For example, Target is giving its employees Fitbits to raise the corporate wellness levels.
■ Using fndings to inform broader talent management strategies, such as hiring versus internal development, to fll the gaps. For example, associate attrition may be at an acceptable rate for tenured employees, but high for those with less than one year on the job. This may point to gaps in training practices and lead to corrective program investments.
A retailer's workforce analytics strategy must ultimately include advanced predictive and prescriptive analytic capability to link employee engagement and performance to customer service and store performance outcomes, beginning at the recruitment stage and through to training and ongoing development. However, the starting point for any workforce analytics strategy is the business and HR strategy and focus of the enterprise. Different business contexts lead to the need to measure different kinds of workforce metrics. In order to effciently calculate, track and communicate results around those metrics, HR IT organizations should frst focus on systems and analytics capabilities around those topics most critical to the enterprise's success. CIOs and IT leaders need to explore workforce and talent management applications, which include analytical capabilities within their tools for breadth of capability, fexibility to meet new business requirements, and ability to incorporate data from a variety of channels.
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Business Impact: Retail workforce analytics investments, when targeted and specifc to a given business problem, provide highly valuable input in fulflling the retailer's customer value proposition, either in terms of resource-related cost avoidance or future productivity optimization.
Benefit Rating: High
Market Penetration: 1% to 5% of target audience
Maturity: Emerging
Sample Vendors: Ceridian (Dayforce); IBM; Kronos; Oracle; SAP; Workday; Workplace
Recommended Reading:
"Link Employee Engagement to CRM Strategy to Maximize Impact in the Retail Digital Workplace"
"Market Guide for Retail Workforce Management Applications"
Sliding Into the Trough
Real-Time Store Monitoring Platform Analysis By: Miriam Burt
Definition: Real-time store monitoring platforms deliver store activity monitoring on dashboards through a real-time data infrastructure by bringing together signals and alerts from real-time data sources available in the retail store. These can include input from traffc counters, queue management sensors, in-store beacons, point-of-sale transaction logs, IP video, Wi-Fi triangulation, mobile triangulation, remote sensors on in-store devices, pressure sensors and RFID.
Position and Adoption Speed Justification: Real-time store monitoring platforms are evolving to be a type of Internet of Things platform to capture, ingest and analyze data from a variety of data signals originating from inside and outside the store. The data is used to track, monitor, analyze and optimize in-store execution of in-store and cross-channel processes.
Digital video and thermal imaging technology with video analytics, 3D behavior analytics and proximity analytics are being deployed to provide real-time functionality. This includes task management, people counting and tracking, dwell times, queue management, inventory monitoring, and real-time alerting. The solutions are also capable of providing visual reports such as heat maps. Integration with external data sources can enable more targeted execution related to customer demand, for example, by incorporating feeds from social media activity to local weather and news.
In the past 12 months, many retailers have embarked on IoT initiatives to enhance the in-store customer experience. One prominent example is the implementation of location-based in-store beacons for proximity marketing through customers' mobile phones. Retailers' IoT efforts and continued hype on the technology, as well as vendor consolidation in this market — for example, Tyco's acquisition of ShopperTrak — are refected in the post-peak 40% position. We expect this
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type of IoT solution to only get "hotter" in the next 12 months as retailers seek to implement the "digital store."
User Advice: Real-time store monitoring platforms are integral to the role of the store as the hub of execution in digital business. A Gartner multichannel retailer survey conducted in 3Q15 indicates that up to 42.1% of in-store activity is infuenced by activity in the retailer's website. The ensuing push to the store is having a signifcant impact on in-store execution, and these solutions can be used to integrate offine and online by combining real-time data feeds generated inside and outside the store into a single platform in order to provide the enterprise with a single real-time view of what is happening in the store. For example, this solution can be used to alert in-store queue management systems based on input from mobile applications outside the store in a "buy online, pick up from store" scenario.
The store must have the ability to speedily detect and discover data signals in order to deliver real- time insights so that the business can capitalize on the opportunities discovered in the dynamic and volatile digital business environment.
In the past 12 months, retailers have been experimenting by bringing together digital technologies and "things" such as augmented reality, 3D printers, electronic shelf labels, RFID, digital signage, in- store beacons and "smart" technologies such as "smart mirrors" as part of the IoT in the store. When implementing these solutions, multichannel retailers should:
■ Use multichannel customer analytics to prioritize investments in functionality delivered through real-time store monitoring platforms.
■ Integrate these solutions with advanced analytics for better planning and agile execution against customer demand.
■ Develop excellence in the management of the increasing volumes and complexity of data used in the store; data gathering, data storage and real-time analytics to serve the customer will become a core competency for competitive advantage.
■ Remember to factor in the cost of all the elements in the IoT ecosystem, for example, implementation costs of the platforms and integration to applications, as well as upgrades to network bandwidth, and not just the cost of the "things" or sensors.
Business Impact: Real-time store monitoring platforms are essential for multichannel execution in a digital business environment. More specifcally, real-time monitoring with analysis of store operations can lead to the following benefts for multichannel retailers:
■ Increased sales through improvements in stock availability and real-time personalized offers to customers and through supporting clienteling and guided selling in upselling and cross-selling
■ Reduction in costs through improving loss prevention and optimizing task management
■ Improved customer service through, for example, queue management
As retailers transition into digital business and as the IoT takes hold, real-time store monitoring platforms will be a prerequisite for excellent data management in the store. They will also become mission-critical for digital business as retailers move toward servicing customer lifestyles, which will
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span other industries. One example might be enabling customers to lead more healthy lifestyles by collaborating customers, suppliers and the healthcare industry to offer promotions in store on healthy products and services using information gleaned from customers' shopping baskets, as well as their health metrics, through their Fitbits ("things" in the IoT). This technology, therefore, warrants a beneft rating of "transformational."
Benefit Rating: Transformational
Market Penetration: 5% to 20% of target audience
Maturity: Adolescent
Sample Vendors: CountWise; Irisys; Nomi; Refexis; RetailNext; Tyco Retail Solutions
Recommended Reading:
"Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
"A Real-Time Store Monitoring Platform Is Critical for Digital Business"
Real-Time Customer Offer Engines Analysis By: Kelsie Marian
Definition: Real-time customer offer engines provide retailers with the ability to create personalized context-aware promotions for a specifc customer or customer segment. By taking real-time interactions and transactions and using advanced analytics, they determine the "best or most relevant offer" in real time that can be delivered to the customer via any channel.
Position and Adoption Speed Justification: Although investigation and experimentation in this technology have expanded to 20% of Tier 1 retailers, only around 5% of Tier 1 retailers currently use real-time offers online, mobile or in-store. Over the past few years, several large retailers have conducted pilots of real-time offers, in and across various channels, with mixed results, thus pushing this technology further toward the trough. Three trends continue to converge and support increased interest in and adoption of real-time customer offer engines. First, the ability to access context-aware, real-time information on customers is increasing (for example, customers' locations communicated via their mobile phones). Second, advances in database and cloud computing are signifcantly increasing the analytical capability to produce real-time offers. Third, as Gartner research shows, consumers are becoming more receptive to receiving and requesting promotions "in the moment." In a 3Q15 Gartner consumer survey, one-third of consumers reported sharing their location with a retailer's shopping app in exchange for offers or promotions. This fgure is up from 28% in previous years' surveys.
User Advice: Creating a compelling offer requires more than just promotional algorithms. Retailers that are considering real-time offer engines will require good customer data (ideally, across all interaction channels), context-aware data (for example, location, weather and even customer intent)
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and a vehicle by which customers can receive and respond to offers. Real-time customer offer engines should be evaluated not only on their science, but also for their speed and ability to be integrated into any customer process in any channel. Even if the engine is fast, the way it retrieves and delivers an offer can be constrained by the performance of the delivery systems, which defnes the customer experience.
Retailers should not attempt to supply customers with real-time, customized, 1-to-1 ratio offers until they are confdent that they have adequate segmentation and behavioral analysis. The promise to provide meaningful, relationship-building and relevant offers can frustrate or offend consumers if they arrive late or seem irrelevant. Knowing the "right time" to deliver is equally important as the offer itself. Offer execution that is in line with basic customer expectations also plays an important role. For example, it is not enough to send timely and relevant personalized offers — the product must be in stock when the customer redeems the offer.
Business Impact: Real-time customer offer engines are designed to improve sales, margins, satisfaction and frequency of visits in their ability to infuence shoppers to make a purchase closer to or at a point of decision. It is expected that retailers will increasingly transfer promotional activity from traditional media, such as fyers, to more targeted and real-time offers. This will provide a substantial savings in operational costs.
Benefit Rating: High
Market Penetration: 5% to 20% of target audience
Maturity: Adolescent
Sample Vendors: Catalina; FICO; Fujitsu; IBM; Infor; NCR; Oracle; SAP; SAS; Teradata
Recommended Reading:
"Market Guide for CRM in Tier 1 Retail"
"Cool Vendors in Retail, 2016"
"Survey Analysis: Growing Customer Loyalty Through Digital Engagement"
Social Commerce Analysis By: Robert Hetu
Definition: Social commerce for retail uses social networks and social media content to drive measurable, repeatable and scalable sales transactions, using a variety of applications and approaches.
Position and Adoption Speed Justification: Social commerce is evolving and centered currently around user-driven content communities. Retailers continue to struggle with the options for social participation and inability to measure results, moving this profle rapidly toward the Trough of Disillusionment. A research survey of consumers conducted by Gartner in 4Q15 shows that 57% of
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consumers have visited a retailer's social media pages in the past 12 months. Aspects of social media such as user-generated content, product reviews, videos, wikis and blogs, continue to grow in infuence on consumers' buying decisions online and in-store. Developments such as Amazon's use of a Twitter hashtag that allows products to be added directly into an Amazon shopping cart have proven somewhat successful, as the same survey indicates 11% of consumers made a purchase from a social media feed directly through a purchase link.
User Advice: It's important for retailers to master use of social technology for customer-facing sales initiatives. However, these should be targeted and focused on the specifc purpose of driving sales, not just on the number of followers or friends. Therefore, organizations should focus on techniques with proven value, such as sales of top-rated products or friends-/followers-only promotions. Moreover, organizations should experiment with various tools and understand segments within various social media outlets to target customers with purchasing power. For example, while Facebook is still dominant, there is strong evidence that younger consumers are abandoning it for other communities such as Pinterest, Instagram, Tumblr and Snapchat where they interact in real time and seek purchase advice. Although not reaching the levels of Facebook, Pinterest has become a major driver of social engagement. Social commerce can be a driver for innovation, such as the example of Nordstrom using Pinterest for in-store merchandising that aligns with the what's trending as the top pins on the platform.
There is a strong linkage between mobile devices and social commerce. Gartner research shows that integrating with social media is the second-most common use of a mobile device while shopping in store, just after viewing the retailers e-commerce site. As a result, retailers must ensure that all of their social channels, as well as e-commerce and brick and mortar, are portraying the brand in a consistent manner. Social interaction is also becoming more "visual" and not just text- based. One example is the use of Snapchat to communicate in the moment. The shift to visual social media is quite signifcant, so retailers need to be well engaged in visual social media, not only having consistent information, but also refreshed on a regular basis.
Most importantly, be present where your customers can feel empowered and will seek to engage in collaboration. Social media also plays an important role in the facilitation of modern loyalty schemes, but must be coordinated across all channels and touchpoints to avoid customer frustration. Retailers need to ensure that they can respond to customer feedback that is coming through the social channels. Also, they need to ensure that they can respond to customer feedback that is coming through the social channels. However, organizations should not be overzealous with their usage of social commerce because they can cross a line with customers and become "unliked" or blocked by the user because of overuse. Develop plans for wooing back customers that are turned off by overzealous social content. Take into consideration the fact that a consumer may have connections with the retailer through a variety of social touchpoints in addition to more traditional communication vehicles such as email. Overcommunication through multiple touchpoints could be an annoyance, as there is possibility that the user might experience contradictory offers or information. Therefore, prudence should be a guiding principle for organizations.
Business Impact: Social commerce can create new customer segments that are based on consumer's interests in a web environment. This can enable the targeted selling of products that are related to group interests and activities. In addition, social commerce can help drive down the cost
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of sales because it is used in more cost-effective digital channels (marked by considerably less need for human intervention) and can be an extension of brand personality to create greater brand awareness. Gartner research shows that social media content has a direct positive impact on physical retail stores as well as digital channels and, as such, is an important enabler of multichannel retail. The unquestionable convergence of social and mobile offers unique opportunities to respond to consumers in the moment. Organizations should continue to capitalize on these trends since social commerce capabilities differentiate one site from another today. As digitalization increasingly impacts retail, expect social media to form an important part of the retail digital business strategy.
Benefit Rating: High
Market Penetration: 5% to 20% of target audience
Maturity: Emerging
Sample Vendors: Bazaarvoice; Epicor (ShopVisible); Facebook; Infosys; Mixpo (ShopIgniter); Pinterest; Reevoo; RichRelevance; The Hunt; Twitter
Recommended Reading:
"Cool Vendors in Retail, 2016"
"Retail Customers Are Leading Transformational Change With the Nexus of Forces"
"Predicts 2016: Digital Business Uproots Traditional Retail Revenue Generation"
"Survey Analysis: Growing Customer Loyalty Through Digital Engagement"
Digital Coupons Analysis By: Kelsie Marian
Definition: Digital coupons, also known as electronic coupons or e-coupons, are the electronic form of a paper coupon or voucher. They can encompass several formats, including mobile and social coupons.
Position and Adoption Speed Justification: Over the past year, offer relevancy has become a hot topic around digital coupons, as retailers are beginning to realize a signifcant amount of segmentation and analysis is required to provide meaningful offers in the most appropriate combination of channels. As a result, this technology remains in the trough as retailers work to identify the right balance of personalized and mass offers. It is important to note that distribution and redemption of digital coupons by retailers are still maturing, and challenges remain, including the identifcation of customers who wish to receive digital coupons — particularly via mobile messaging as well as linking cross-channel customer behavior to further refne understanding of the customer for highly targeted offers. For these reasons, this technology, which combines various forms of digital coupons, including mobile and social, is expected to reach the Plateau of Productivity in two to fve years from now, rather than in the next 12 months.
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User Advice: Retailers must establish a well-developed promotion plan to coordinate the execution of coupons across channels to the right customers at the right time. Therefore, access to advanced analytic capabilities is necessary to build behavior-based segmentation and target the right customers. Good execution of highly personalized promotions is essential to help build customer trust. One way this can be done is through the use of a real-time offer engine with integration to loyalty programs that help the retailer to recognize and reward customers across all channels.
It is also critical that, once an offer is "pushed" to a customer, a retailer is able to execute on that offer to the customer's convenience. As a result, retailers must consider the impact that digital coupons will have on the operational execution of stock management, in particular, in cross-channel processes, such as buying online and picking up in the store. It is especially important to ensure stock availability in the store, where cross-channel processes are largely fulflled, to satisfy customer demand raised through the redemption of coupons.
Continued experimentation with digital coupons — particularly via mobile devices — continues, and retailers are working to better understand how customers' cross-channel behaviors contribute to campaign success. As more vendors include advanced analytical capabilities via point and click, retailers are beginning to move further out of the trough to the Plateau of Productivity. Moreover, when combined with real-time offer engine technology, these types of coupons could deliver timely offers to well-targeted customers and, thus, increase the likelihood of redemption and conversion. Also consider incorporating coupons from loyalty programs into digital wallets, as this promotes stickiness for wallet use, providing retailers additional mobile data for analysis.
Business Impact: In Gartner's 3Q15 retailer survey, Tier 1 retailers estimated that up to 42.1% of in-store sales activity is infuenced by activity in the e-commerce channel, and 21.3% of in-store sales activity is through mobile commerce channels. The benefts of digital coupons for retailers, other than cost savings derived from not having to print, distribute and track paper offers, center on increasing the frequency of visits to the store and increasing the overall customer transaction value. Sales margins and customer loyalty are all targeted to increase as a result.
Through personalization and customer recognition, these types of coupons can contribute to building customer loyalty and increasing the likelihood of repeat transactions.
Benefit Rating: Moderate
Market Penetration: 5% to 20% of target audience
Maturity: Early mainstream
Sample Vendors: Catalina; CodeBroker; Coupons.com; Facebook; Groupon; LivingSocial; Mobilize Systems; RetailMeNot
Recommended Reading: "Market Guide for CRM in Tier 1 Retail"
Loyalty Management Systems Analysis By: Kelsie Marian
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Definition: Loyalty management systems enable retailers to use loyalty functionality (points and profle management, self-service capability) from one centralized management system to transact with, interact with and reward customers across any and all channels. Providing loyalty capability to point of sale (POS), e-commerce, and mobile and social channels is required to move toward digitalization of the business.
Position and Adoption Speed Justification: Customer loyalty remains a hot topic as well as a challenge for retailers to leverage customer data from multiple touchpoints to increase long-term loyalty. Doing so is a complex process that requires participation and learning across the organization. As a result, the technology has been renamed from "multichannel loyalty systems" to "loyalty management systems" as a multichannel approach to retail becomes more "business as usual" for retailers. Currently, loyalty management systems are in the trough, as retailers continue to work through the challenge of leveraging customer data from both physical and digital channels to improve the relevancy of not only communications but also assortments and product placement. Gartner estimates about 15% to 20% of Tier 1 retailers have the ability to leverage customer loyalty systems to manage and interact and understand customer behavior in and across digital and physical channels with customer-level data.
User Advice: When planning or reviving a multichannel loyalty program, remember that solid execution of basic customer expectations (such as product availability and informed sales associates) goes much further in garnering customer loyalty than program cards and discount offers. For example, leveraging loyalty data in order to determine ways to provide better support for minimizing out of stocks and providing associates with detailed product information faster is crucial for maintaining customer loyalty.
Leverage interactions with customers on digital channels, such as mobile and social, to identify new ways in which loyal customers want to be rewarded — for example, offering access to exclusive content or rewarding customers with recognition, such as the opportunity to participate in an online commercial for the brand.
Ensure that you are investing in supporting multichannel customer processes, including loyalty management. Look for vendors that offer web services/API capabilities that will enable retailers to extend loyalty functionality, such as member bar codes, to any channel-specifc application (for example, mobile apps).
Retailers continue to experiment with new ways to engage customers via loyalty programs, including identifying and leveraging advocates via advocacy marketing, which activates a brand's advocates with scale over the social web. These same advocates, which tend to be a brand's most loyal customers, are highly effective in acting as a brand's "second sales force." Therefore, the observation that advocates are also loyalists is redefning the concept of loyalty: Loyal customers don't just buy more, they bring others with them. Conversely, another approach to increase loyalty is through identifying and targeting customers who are not as loyal as the brand ambassadors with incentives to be more loyal. For example, the ROI from targeting existing loyal customers is not as great as from targeting those who are sitting just below the top 20% of loyal customers. Retailers need to be able to identify those who give them the best return and engage with them to increase loyalty.
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Business Impact: Increases in sales due to improvements in marketing and customer services across all channels can be expected from enterprise customer loyalty systems. In addition, retailers will have an enhanced ability to segment customers based on improved cross-channel visibility into customer activity in channels. Customer satisfaction will also result from the ability to provide loyalty functionality in any channel.
Benefit Rating: High
Market Penetration: 5% to 20% of target audience
Maturity: Early mainstream
Sample Vendors: Aptos; Fujitsu; IBM; NCR; Oracle; SAP; Symphony EYC; Teradata; TIBCO Loyalty Lab
Recommended Reading:
"Market Guide for CRM in Tier 1 Retail"
"Improving Loyalty and Retention in Retail Primer for 2016"
Retail Mobile Payments Analysis By: Miriam Burt; Joanne Joliet
Definition: Retail mobile payment applications permit customers to pay for products or services via their mobile devices, using a variety of tender types.
Position and Adoption Speed Justification: Accessed through native mobile applications or mobile websites, mobile payments are initiated or authorized through technologies such as Near Field Communication (NFC), SMS, Wireless Application Protocol (WAP) and Unstructured Supplementary Service Data (USSD). The growth and adoption rates of the mobile payment technologies vary by economic and geographic market. Despite the hype surrounding the 3Q14 Apple Pay launch and the launch of various mobile payment applications backed by retailers and fnancial services frms, the global takeup of contactless transactions and NFC-enabled mobile payments has been slow. SMS-based solutions have had better adoption, particularly in India and in parts of Africa.
Consumers' lack of enthusiasm (which is mainly due to security concerns); the sloth of large, multichannel retailers to invest in mobile payment processing infrastructures; the assortment of ownership structures; and the varying interests of the stakeholders in the payments chain have now put this technology frmly in the doldrums of the trough. We expect the emergence of retailer- owned, digital wallet white-label applications, which include loyalty functionality, to kick-start resurgence of consumer interest.
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Mass global adoption in large Tier 1 multichannel retailers is likely to be in the fve- to 10-year range, but nearer fve than 10. More mobile payment implementations with higher adoption rates are found in quick-service restaurant (QSR) and transport segments.
User Advice: Before investing in mobile payment technologies, multichannel retailers need to:
■ Determine the priority that customers place on using their mobile devices for making payments, and prioritize investments in functionality accordingly. A 3Q14 Gartner multichannel retailer survey in the U.S. and U.K. showed that, on average, m-commerce accounted for only 3.2% of sales. Moreover, our year-over-year research indicates that a key barrier to adoption of mobile payments is consumers' concerns about security of payments made through their mobiles. However, the mobile channel is important as the gateway to shopping, and our 3Q15 survey indicates that mobile informational activities, such as searching for stores, product information and prices, are infuencing store sales by up to 21.3%.
■ Assess the different types of mobile payments available, and determine how they map to their requirements in customer payment processes; for example, how could the cash-to-card ratio change, and how could this affect cash and card utilization.
■ Investigate non-NFC solutions, such as the merchant-backed Merchant Customer Exchange (MCX) CurrentC digital wallet solution, which is based on quick response (QR) codes.
■ Pay careful attention to continuing customer concerns about the security and privacy of data and to the developments involving mobile payment standards, and demonstrate compliance.
■ Work with key stakeholders — for example, banks, card payment companies and telecommunications providers — to ensure streamlined front-end customer processes and back-offce processes; provide corrective action when things go wrong, such as disputed payments.
■ Monitor and assess the progress of contactless payment transportation schemes in regions where they operate to learn about customers' acceptance and adoption of these types of mobile payment solutions.
■ Investigate how digital wallet solutions can be used to introduce strong loyalty incentives to enable consumers to adopt mobile payments more easily.
Business Impact: Inside and outside the store, mobile payments could address the need for customer convenience and the likelihood that this will lead to more sales. In addition, payment transaction fees for mobile payments that are lower than those of credit and debit cards can provide clear savings for the retailer. However, the speed of adoption of mobile payments will be dictated by consumers, and solutions must be able to support a secure, convenient, hassle-free and rapid check-out experience.
In emerging economies, mobile payment may act as a viable alternative to cash. If consumers can also access microcredit — or, for example, the ability to access credit payments through installment plans through their mobile payment accounts — then retailers may see higher spending from transactions that involved mobile payments.
Benefit Rating: Moderate
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Market Penetration: 5% to 20% of target audience
Maturity: Adolescent
Sample Vendors: Amazon; Apple; eBay; Google; M-Pesa (Safaricom); MCX; Samsung
Recommended Reading:
"Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
"Refocus on Point of Sale as a Strategic Enterprise Application in Transforming to a Multichannel Digital Business"
Unifed Merchandise Planning Analysis By: Robert Hetu
Definition: Unifed merchandise planning provides retailers with the ability to simultaneously plan merchandise assortments, purchases, inventory levels and prices across all physical and virtual channels or touchpoints, while taking into account various marketing and event-planning calendars, as well as seasonal infuences.
Position and Adoption Speed Justification: The dramatic shifts in consumer behavior have accelerated the interest in unifed planning activities. The fast-paced evolution of e-commerce, social media and mobile commerce (m-commerce) is driving much consolidation and acquisition within the vendor community. This technology is moving to the forefront of interest, as Tier 1 retailers are seeking new core merchandising and merchandise planning applications that will service the cross-channel customer. This technology has entered the Trough of Disillusionment as retailers struggle with business and technology silos, as well as some very basic issues like accurate perpetual inventory at the item-location level.
User Advice: This technology has been renamed as "unifed merchandise planning" to more accurately represent the challenge and opportunities that omnichannel failed to capture. Channel- based silos built into the retailer structure are a signifcant impediment to the development of unifed merchandise planning. Organizational structure change, cross-channel workfows and change management are key contributors to a successful launch. Gartner research revealed that 70% of surveyed retailers plan future organization strategies that will take a centralized approach. Retailers currently using a homegrown legacy planning system, a Microsoft Excel-based approach or an aged software platform should look at packaged solutions that address the entire planning process. Others that have recently implemented a new planning suite will need to identify unifed planning capabilities within the existing package and consider best-of-breed additions to supplement capabilities.
While multichannel capability exists within the applications, the effort to confgure the software to support unifed planning should not be underestimated. The required processes are not provided as a standard toolkit. Well-structured and detailed design workshops would provide the process
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template for a customized confguration. In addition, unifed merchandise planning requires the ability to analyze, share, and utilize advanced and detailed customer behavior profles that are gathered from transactions, customer loyalty programs, credit cards and so on. This analysis must include channel-based data and lead to a retailerwide view of the customer. Retailers need to determine how channel growth will impact the consumer profle and which channels will lead the way to future growth. Various demand-planning forecasts from different sales channels must use the cost elements and planned promotional activity to more accurately determine margin plans, develop vendor forecasts and inform key stakeholders of performance expectations.
Ultimately, this is a process that can beneft from customer data and input from external sources, such as social media, as well as customer collaboration portals.
Business Impact: When done correctly, multichannel merchandise planning will provide differentiation and competitive advantage for Tier 1 retailers. Customer loyalty, service and brand perception will be enhanced by execution of the important and often-overlooked aspect of being in stock, driving growth in sales and market share. Ensure performance and proftability targets using a cross-channel planning workfow and business process. Integrated demand-planning activities will support better forecasting and inventory management; accurate, open-to-buy planning; and supply chain information for vendors, logistics and transportation functions.
Benefit Rating: High
Market Penetration: 5% to 20% of target audience
Maturity: Adolescent
Sample Vendors: Galleria; IBM; JDA Software; Logility; Oracle; Predictix; SAP; SAS; Symphony EYC; TXT e-solutions
Recommended Reading:
"Magic Quadrant for Merchandise Assortment Management Applications"
"Critical Capabilities for Merchandise Assortment Management Applications"
"Algorithmic Retailing: Merchandising Leads the Way"
"Transform the Merchandising Organization Now, With Prescriptive Techniques"
"How to Achieve One View of the Retailer Through Behavioral Segmentation"
Climbing the Slope
Multichannel Master Data Management for Retail Analysis By: Michael Patrick Moran; Andrew White
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Definition: Master data management (MDM) is a technology-enabled discipline in which business units and IT organizations collaborate to harmonize, cleanse, publish and semantically assure master data that needs to be shared across retail organizational channels in operational applications, as well as analytic applications.
Position and Adoption Speed Justification: The need to share semantically consistent data across multiple channels is becoming a major issue for leading retailers. As the challenge is principally one of business versus technology, most retail organizations lack the maturity to achieve the outcomes sought. The maturity of enabling technology also lags.
Retail MDM drivers are varied across:
■ Supply chain: Product data in support of global data synchronization from suppliers.
■ Demand chain: Consumer data in support of loyalty programs or product data for sell-side process integration, as well as an increased need to integrate operations across multiple channels.
■ Enterprisewide focus: In a few cases, and accompanying full retail system remediation.
New sources of information — part of a digital business transformation — are adding intriguing options to information strategists. Some retailers are following the leadership shown in the pharmaceutical industry, for example, where there is a healthy dialogue about how organizations share information for what was once thought to be confdential information (data related to drug discovery, for example). However, not enough retailers are thinking of this yet. Through 2016, retailers continue to develop a focus on MDM supporting multiple channels, as well as broader sets of digital content, as they started to deploy their digital strategies spanning multiple data domains.
User Advice: Use the discipline and practice of MDM and enabling technologies to achieve consistency, accuracy and integrity of critical information assets in upstream operational environments, as well as downstream analytical uses.
Some of these programs link to governance of content (master content management), which really only entered the market as a (hyped) concept fairly recently. There is a potential role for tactical MDM technologies in solving semantic inconsistency issues in downstream, BI, analytical and corporate performance management environments.
Organizations must ensure that these activities mesh with their MDM initiatives in the operational environment. They must create cross-departmental collaboration in adopting the discipline to realize and sustain the benefts. All MDM initiatives must be aligned with the business objectives of the organization's enterprise information management (EIM) program, which could span master data, content, analytical data, social data, reference data and others. When addressing MDM issues by subject or domain (such as customer or product), companies should leverage external service provider (ESP) expertise to expand into other domains. MDM efforts can originate in any function, but for maximum value, initiatives must be consolidated into a comprehensive EIM program. MDM is a discipline, so focus beyond enabling technology to also encompass the business processes and organizations impacted by sharing of master data.
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Key considerations for successful launch of MDM in a retail channel include:
■ Line of sight to a business case.
■ Buy-in from business leadership.
■ Governance and stewardship of master data established in a line of business.
■ Business/operational measures and analytics.
■ Viewing such initiatives as programs that are ongoing, not projects that stop.
■ Effective risk management practices that relate to the wider risk and security framework.
Business Impact: Retailers spread their master data across many systems. It is fragmented and often inconsistent. This makes it diffcult for organizations to streamline business processes and operations effciently, and to develop agile new business processes across retail channels.
It also affects consumers, who will often not perceive a single view or have a consistent experience with a given retailer across all channels.
With a single trusted view of master data, retail organizations can achieve benefts in areas such as:
■ Upselling, cross-selling and leveraging CRM and other customer-facing processes.
■ Increased effciencies on the buy side.
■ More effective data compliance (ingredients, for example).
■ Increased competitiveness through more effcient new product introduction.
■ Increased integration across cross-channel processes for improved customer service, reduced out-of-stock instances, and increased use of inventory.
Consumers will also see the following benefts or impacts:
■ More consistency in marketing, brand messages and management from retailers.
■ More reliable service, including more accurate store data and available-to-promise inventory.
Benefit Rating: High
Market Penetration: 5% to 20% of target audience
Maturity: Adolescent
Sample Vendors: IBM; Informatica; Oracle; Profsee; Riversand; SAP; Stibo Systems; TIBCO Software
Recommended Reading:
"The Five Vectors of Complexity That Defne Your MDM Strategy"
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"Should Organizations Using ERP 'Do' MDM?"
"Toolkit: RFP Template for Master Data Management Solutions"
"Toolkit: A Program Manager's Guide to MDM"
"Top Retail Business and Technology Trends"
"Market Guide for MDM External Service Providers"
Retail Mobile Shopping Analysis By: Miriam Burt
Definition: Mobile shopping websites and applications provide functionality that allows consumers to conduct shopping activities on their mobile devices.
Position and Adoption Speed Justification: Consumers have become very familiar with using mobile-optimized websites and apps on smartphones and tablets as part of their everyday shopping activities. Everyday functionality already implemented by many large multichannel retailers includes the ability to fnd stores, browse items, build shopping lists, reserve items, conduct social shopping, receive and review promotions, receive coupons, join community reviews, check prices and inventory, check the status of their loyalty program points and perform other activities.
More and more, these types of mobile functionality are converging with in-app mobile payment and digital wallet capability to offer the customer a more convenient end-to-end shopping experience.
In the past 12 months, the plethora of context-aware personalized mobile offers and social shopping apps and many new implementations and upgrades, as well as the major trend of the convergence of mobile and social in digital business, have propelled this technology rapidly up the Slope of Enlightenment. Although the hype around personalization has not materialized into large- scale full rollout implementations, this area will continue to be hot in the coming year as retailers come to grips with the fact that mobile converged with social is becoming the primary conduit of information in digital business. This convergence will also be accelerated through connection with the data-fueled Internet of Things.
User Advice:
■ Prioritize mobile shopping tools that consumers will value by understanding how they can support the consumer service basics, such as having products in stock and making it easy to fnd items and product information. This will also help to avoid the proliferation of unnecessary or gimmicky features or apps. For example, the ability to fnd a store, check stock availability, check and compare prices, read product reviews and receive promotions is high on the list of things that consumers want to do with their mobile devices, whereas using their mobile devices to make payments is not.
■ Conduct "personalization" initiatives by identifying the implications regarding all the technology requirements to support the underlying process. For example, pushing a personalized offer
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accurately to customers on their mobile phones when they are shopping in your store requires integration of several back-end applications such as real-time customer offer engines.
■ Understand that your mobile channel will have an impact on your other channels — in particular, the store and e-commerce — rather than receiving substantial revenue in its own right. Therefore, focus on the user experience in terms of how the mobile device is used in the overall cross-channel shopping experience. An example of this is making sure that the store is ready to service a customer who is browsing and reserving items on his or her mobile phone for picking up in the store.
■ Capitalize on the convergence of mobile and social, for example, by soliciting feedback through social channels in real time via customers' mobile devices.
■ Consider, where appropriate, mobile apps that have in-app mobile payment functionality as this could foster more "stickiness" and loyalty.
■ Investigate how services to enhance customers' lifestyles can be offered through mobile, rather than just looking to push products via mobile marketing.
Business Impact: Retailers can use mobile shopping tools to conduct advertising and marketing and to increase product and brand awareness to improve sales. Our retail research indicates that mobile will play a critical part in enabling retailers to make the shift toward digitalizing their businesses. According to a 3Q15 Gartner consumer survey, mobile already infuences 21.3% of store sales, and if retailers can improve process execution, it will become the key gateway in driving cross-channel revenue.
For example, a mobile app used to fnd the nearest store that has a desired item in stock may infuence a customer to go to that store and purchase the item right away — which means that the item should be physically available on the shelf, as expected by the customer who was "pushed" to the store by the mobile channel. Moreover, while in store, consumers who have opted in can be sent context-aware personalized offers through their mobile devices.
Benefit Rating: High
Market Penetration: 20% to 50% of target audience
Maturity: Early mainstream
Sample Vendors: Apple; Mobilize Systems; Nearby Now; Netbiscuits; Nirvaha (mPoria); Phunware; SapientNitro; Scanbuy; Usablenet
Recommended Reading: "Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
Customer-Centric Merchandising & Marketing Analysis By: Robert Hetu
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Definition: Customer-centric merchandising and marketing supports retailer efforts to offer the right product assortments to customers, defne the customer behavioral segments, defne critical elements of differentiation and service delivery standards, and measure the impact of all activities based on customer behavior segments.
Position and Adoption Speed Justification: This profle remains in the Trough of Disillusionment as retailers struggle with the foundational work and change management associated with becoming more customer-centric. Effectively, merchandising and marketing for customer segments is a complex business process, and the considerable effort of adding consumer behavioral data can seem equally complex and, as a result, overwhelming. The concept of customer-centricity is well- understood by retailers at a high level. However, the challenge that remains is how to apply algorithms to big data that enable the use of customer behavioral information in a meaningful way. This is true across all activities in the assortment development process, as well as enabling traditional and digital marketing activities. Further complications arise when a multichannel retailer begins the process of cross-channel customer segmentation. For this technology to progress faster from the trough, retailers will need to invest in robust master data management (MDM) strategies that include product and customer data from all channels, including a wide variety of unstructured sources. Once completed, advanced customer segmentation is required to build understanding of customer behaviors and shopping context.
User Advice: Prerequisites for incorporating customer data into merchandising and marketing processes include establishing comprehensive MDM for customers and items, categorizing the current customer base, setting performance metrics, identifying target behavior segments and understanding customer behavior by location, channel or touchpoint. Customer-centricity requires the application of algorithms to big data to extract meaningful information to enable customer- centric actions across merchandising and marketing. Often, a professional services frm or strong internal customer analytics group is required to bring these capabilities together.
These represent areas of signifcant collaboration possibilities within the retailer, such as between the merchandising and marketing business units. Similarly, in recognition of the value of shared data across industries, collaboration is required to ensure the customer has the highest quality experience.
Data points are exploding with advances in the Internet of Things (IoT), expanding social media and in-store monitoring through technologies such as beacons. Retailers should clearly understand how vendors are applying science and algorithms to big data to extract useful customer insights.
Business Impact: Merchandising and marketing presently diverge in the use of customer data, and the customer experience is frequently adversely impacted by this lack of coordination. Targeted assortments and strategically placed inventory aligned with targeted marketing will increase sales and margins while reducing costs and improving customer experience.
Benefit Rating: High
Market Penetration: 5% to 20% of target audience
Maturity: Adolescent
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Sample Vendors: dunnhumby; First Insight; FICO; IBM; JDA Software; Manthan; Oracle; Predictix; SAP; SAS
Recommended Reading:
"How to Achieve One View of the Retailer Through Behavioral Segmentation"
"Algorithmic Retailing: Merchandising Leads the Way"
"Information Innovation Powers Customer-Centric Merchandising"
"Predicts 2016: Digital Business Uproots Traditional Retail Revenue Generation"
In-Store Self-Service: Customer-Facing Applications Analysis By: Miriam Burt; Joanne Joliet
Definition: This technology includes informational and transactional customer-facing, self-service applications. These have been typically deployed on retailer-owned, wired and wireless in-store devices, such as kiosks, self-checkouts, self-scanners and shopping-cart computers. Retailers are now provisioning these types of self-service applications on consumer-owned mobile devices, such as smartphones and tablets.
Position and Adoption Speed Justification: These applications support in-store shopping activities. As the digital channels push more traffc into the store, retailers are experimenting with enhancing the in-store experience through customer-facing digital technologies. As well as the traditional use cases of self-checkouts and price scanners, more recent examples include way fnders; style guides; gesture-based interactive mirrors; digital signage, smart hangers, virtual clothes rails; "meet and greet" robots and holograms, 3D printers, digital shelf-edge labels to scan items for promotions; beacons that trigger personalized mobile promotions, quick-response (QR) scanning capabilities; and augmented reality applications.
In the past 12 months, we have seen increasing numbers of trials and implementations in store as retailers realize how the Internet of Things (IoT) can assist in merging the online and offine assets to offer customers a blended and seamless cross-channel shopping experience. This furry of feverish activity has caused this profle to jump ahead a few points on the curve from post trough 25% to post trough 40%.
The store is fast becoming the execution hub of digital business and as retailers move toward digitalization in the "connected store," we expect this profle to quickly accelerate upward on the Slope of Enlightenment over the next 24 to 36 months.
User Advice: Implement "write-once/run-anywhere" types of applications that can easily be ported onto various employee and customer devices, with content, user interface (UI) and usability tailored to specifc devices. Moreover, all customer-facing applications, whether informational or transactional, must be simple and easy to use, with uncluttered UIs and clear onscreen instructions. Investigate moving toward applications that support gesture-based and visually based interactions, rather than applications that require heavy text input. As IoT takes hold in the store, explore how
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technologies supporting customer-facing applications can be used in convergence, for example, ESLs, NFC and RFID for wayfnding. Store staff must be trained to solve any application or process issues that require intervention. These front-end, in-store, customer-facing applications must also be well-integrated with back-end fulfllment processes and systems, with special attention paid to cross-channel process integration, as well as the management of cross-channel content to maintain consistency.
It's worth noting that 3Q15 Gartner research shows that, in general, when in the store, customers prefer to speak to a store associate, rather than use the retailer's self-service technology (such as a kiosk) or their own mobile devices. As a result, retailers are investing in mobile capabilities that enable store associates to provide timely customer assistance.
Business Impact: Delivering the customer basics will remain a core competency in the digital business world. To thrive in digital business, it is imperative that in-store execution of the key basic informational and transactional requirements that customers want, especially in the store, can deliver a high-quality, in-store shopping experience and contribute to increased sales. However, regardless of the devices or "things" involved, customers will use these applications only if they're convenient and not cumbersome.
As retailers increasingly struggle to recruit pertinent store staff, store labor productivity could be improved by the full-time availability of the appropriate self-service technologies for customers, particularly as more traffc is pushed into the store from the digital channels. In-store, customer- facing self-service applications, particularly for repetitive tasks such as price checking, could also release store associates to perform more value-adding tasks, such as dealing with inquiries on complex products, which present opportunities for upselling and cross-selling.
Benefit Rating: High
Market Penetration: 20% to 50% of target audience
Maturity: Early mainstream
Sample Vendors: Authentise; Fujitsu; IBM; Microsoft; NCR; SES-imagotag; St. Clair Interactive Communications; Wincor Nixdorf
Recommended Reading:
"Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
"A Real-Time Store Monitoring Platform Is Critical for Digital Business"
Algorithmic Merchandise Optimization Analysis By: Robert Hetu
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Definition: Algorithmic merchandise optimization covers seven key retail merchandising process groupings: price, promotion, markdown, assortment, allocation and replenishment, size and pack, and space. Algorithmic optimization is derived from using business goals, product, location and smart data discovery to drive demand planning and to inform the merchandising and planning decisions and technologies.
Position and Adoption Speed Justification: This technology has been renamed this year from "merchandise and category optimization" in recognition of the larger opportunity provided by algorithms. Optimization technology can come from individual modules in larger retail suites, best- of-breed vendors or advanced analytic business intelligence vendors. The market has matured to the point where most of the major merchandise planning and category management vendors offer optimization as part of their suites. However, these optimizations are usually performed within a specifc channel. Cross-channel optimization remains largely undeveloped at this time. Each of the seven merchandising processes could be individually placed at somewhat different positions on the Hype Cycle. However, Gartner views these as intricately linked and, therefore, consolidated it to a group position. Price, promotion and markdown optimization are directly linked to merchandise and category optimization.
User Advice: Retailers are actively researching and implementing merchandise optimization applications. Cross-channel shopping behavior, combined with multichannel order management and in-store fulfllment capabilities, is causing an acceleration of interest in this technology. Gartner recommends implementing four of the seven possible optimization capabilities, based on the highest impact on customer effectiveness. For example, a combination of assortment, replenishment, space and allocation may help to alleviate a chronic out-of-stock problem in store. Retailers must consider the following when evaluating algorithmically driven merchandise and category optimization solutions:
■ Scalability (the ability to work with large numbers of SKUs and frequent reforecasts, such as daily reforecasts)
■ Ability to account for store execution constraints and status (such as planogram and fxture compliance)
■ Performance (the ability to provide users with real-time what-if capabilities)
■ Ability to easily manage the large number of goals and targets required to optimize decisions
■ Degree of integration between optimization, forecasting solutions and planning solutions
■ Delivery and pricing model (for example, SaaS versus behind the frewall)
■ An end-goal architecture that brings together common forecasting and optimization technologies into a centralized approach
■ Multichannel strategy supported by robust analytics and comprehensive data availability
■ Advanced analytic capabilities, including predictive analytics, machine learning, pattern matching and data visualization
■ Analytic self-service capabilities for user interaction
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■ Integration with legacy retailer applications
This technology is a lead-in to algorithmic retailing and, as such, can have a substantial impact on the future success of algorithmic business in retail.
Business Impact: Traditional planning applications are good at managing and automating planning basic tasks. Algorithmic optimization takes this a step further by improving and automating the decision making required to support seven merchandising processes — assortment, space, allocation and replenishment, price, promotion, markdown, and size and pack — to adjust assortments by store, cluster or channel; determine buy quantities; optimize space allocation and planograms; and maximize product allocation and availability. Ultimately, these technologies will help stores achieve higher sales and margins in their local markets. They facilitate the complex management that customer-centricity requires, enabling the retailer to do more-detailed planning with fewer resources. This technology is required to support customer-centric merchandising.
Benefit Rating: High
Market Penetration: More than 50% of target audience
Maturity: Early mainstream
Sample Vendors: IBM; JDA Software; McKinsey Solutions (Periscope); NCR (Retalix); Oracle; Predictix; Retalon; Revionics; SAP; SAS
Recommended Reading:
"Market Guide for Unifed Price, Promotion and Markdown Optimization Applications"
"Prioritize 10 Best Practices for Successful Price Optimization Implementations"
"Algorithmic Retailing: Merchandising Leads the Way"
"Retailers Find Success Using Self-Service and Advanced Analytics"
Electronic Shelf Labels Analysis By: Miriam Burt
Definition: Electronic shelf labels (ESLs) are programmable, wireless electronic signage that is typically affxed to shelf edges to display item pricing or promotional information in real time. Two types of ESLs have emerged in retail: LCD-based ESLs and, more recently, e-paper ESLs.
Position and Adoption Speed Justification: ESLs traditionally provided retailers' stores with the ability to manage cross-channel pricing integrity and consistency, deliver cost-effcient fexible pricing, boost productivity and manage stock availability. LCD ESLs continue to remain the dominant form implemented, although we are aware of some retailers considering mixed implementations, for example, using e-paper LCDs in the wine section and LCD ESLs in the grocery categories.
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Over the past 12 months, vendors have been focusing on, and aggressively marketing, developments in cross-channel capability and customer engagement functionality to boost revenue. Through integration with beacon technology, Near Field Communication (NFC) and RFID, ESLs are beginning to be deployed to drive personalized experiences on customers' mobile devices while they are shopping in the store.
There has been a noticeable resurgence of interest in this technology as retailers are beginning to realize how they can leverage ESLs in the digital store, both for cost optimization of store operations, as well to deliver revenue growth through the customer experience. With a rapid move to the trough-plateau midpoint, advances in this technology's capabilities push it into the emerging maturity level. More experimentation, trials and implementations in the past 12 months, as well as interest outside Europe, have raised adoption levels to 5% to 20% of the target market.
User Advice: A Gartner multichannel retailer survey conducted in 3Q15 indicates that up to 42.1% of in-store activity is infuenced by activity in the e-commerce channel and 21.3% through m- commerce channels. The ensuing push to the store is having a signifcant impact on in-store execution. ESLs can be used to optimize costs in the store by enabling numerous store and cross- channel everyday pricing and promotional pricing changes on a frequently recurring basis, supporting stock replenishment processes to improve on-shelf availability — the No. 1 customer service basic. In a digital business environment, ESLs, through integration with Bluetooth low energy (BLE), NFC and RFID can also be used to engage customers when they are shopping in the store, for example, through wayfnding capability or pushing out promotions to boost sales.
However, retailers should not underestimate the investment required in change management when implementing ESLs. For example, it will be especially challenging to maintain pricing and promotion consistency across all the channels due to the patchwork of "back-end" applications implemented by large multichannel retailers.
As they move into digital business, retailers should investigate the role of ESLs in relation to the Internet of Things in the store, in particular, focusing on the management of data generated by ESLs, as well as integration with other technologies such as NFC and RFID to deliver both operational and customer-facing benefts.
Flexible displays using e-paper technology offer many potential benefts over other display technologies, including reduced weight, decreased thickness, improved ruggedness and nonlinear form factors. Signifcant improvements in the readability and usability aspects of e-paper score highly in terms of ease of consumer use.
Business Impact: ESL technology can deliver both reduced costs and improvements in revenue. In particular, it can contribute to labor productivity gains, improve price accuracy and legal compliance (for example, weights and measures), support dynamic pricing, optimize stock availability, and deliver promotions to boost sales. It can also support retailers' efforts to be more operationally green by eliminating the printing of paper signage in stores.
Benefit Rating: Moderate
Market Penetration: 5% to 20% of target audience
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Maturity: Early mainstream
Sample Vendors: Altierre; Displaydata; Pricer; Store Electronic Systems
Recommended Reading:
"Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
"A Real-Time Store Monitoring Platform Is Critical for Digital Business"
Java-Based POS Software Analysis By: Miriam Burt; Joanne Joliet
Definition: Java-based point of sale (POS) software applications are "open" POS applications written to the Java Point of Sale (JavaPOS) standard. The device-independent nature of Java gives retail application developers independence from the proprietary details of the peripheral devices that they access and the POS hardware platforms and OSs on which the application runs. This language-centric platform is decoupled from any hardware or OS specifcs and gives the retailer fexibility in its choice of POS infrastructure.
Position and Adoption Speed Justification: Java-based POS applications are now well- established in the POS market and vendor offerings now include standard, out-of-the-box, cross- channel capability.
Over the past 12 to 24 months, there has been a furry of interest following the acquisition of Micros Systems by Oracle and the spinoff of Aptos from Epicor Retail. More signifcantly, vendors have delivered on their roadmaps regarding more open application architectures with common code base, abstraction of the business logic and reusable components. Developments also include POS web services centralized on a unifed commerce platform, which can act as a hub through which the services are accessible by all channels. This development also supports extensibility to protect the legacy assets of the large multichannel retailers. The more open application architecture will also facilitate retailers to move more fexibly and agilely in digital business. This will be delivered through the availability of functionality to enhance customer lifestyles through curated products and services, rather than to just sell products. The shift away from delivering cost optimization through transactional capability toward a potentially high revenue generating capability has caused us to adjust the beneft rating for this profle from "moderate" to "high." Note that this capability is not confned to Java-based POS applications, as it can also be found in .NET-based POS solutions.
These developments, together with a decent number of frst-time implementations and second- cycle upgrades, have moved JavaPOS quite quickly further up the Slope of Enlightenment.
While, SMB and midsize retailers are relatively comfortable with cloud-based implementations, a services-based approach could mitigate the risks of moving into the cloud in large multichannel and global environments. This can be done through implementing individual POS services, versus the full POS application or, as an example, in a private cloud scenario. However, until retailers are
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reassured on concerns over security, vendor maturity and resilience, the move to cloud in large multichannel and global environments is likely to be slow.
There is still an opportunity in the market for JavaPOS to replace legacy POS applications found in many large retailers, and we expect this technology to reach maturity of adoption in about two to fve years.
User Advice: As more and more traffc is pushed to the store through a variety of digital channels, the store is becoming the main channel of fulfllment of cross-channel processes, and retailers are currently focusing on multichannel integration of the store, websites and mobile commerce. However, retailers should also realize that multichannel is not the endgame. POS solutions must also support digital business through the seamless melding of the online and offine channels, including newer channels such as social media as well as integration with IoT. For example, the functionality which enables POS to tweet customers directly to announce new specials.
Retailers must look for solutions that have "open" architectures, as these will allow them to have more options for implementation, for example, centralized, decentralized or "mixed" application implementation architectures. POS web services which are "write once, run anywhere" and ported onto unifed commerce platforms or centralized hubs can be called, for example, through RESTful APIs, from any channel. The platforms can also provide a framework and a set of interface gateways that allow the retailer to build cross-channel fows such as click-and-collect.
Retailers should evaluate the multichannel capability as well as the nonfunctional requirements, such as the application architecture, usability, security, support, services and delivery model (for example, SaaS). They must also consider which assets they already possess in terms of applications, operating software, hardware and middleware; the level of experience and relationship that they have with a vendor; and the skill mix required to service these applications. A vendor's ability to be a strategic partner and provide effective and effcient support and services could be a differentiating selection factor.
Business Impact: Java-based POS software can deliver cross-platform compatibility and interoperability, therefore reducing capital costs when retailers upgrade POS solutions and reducing the ongoing costs of enhancement. It can also reduce operational costs, such as ongoing training, thus lowering the total cost of ownership. Componentization also supports reduction in time to make changes and supports speed to market for competitive differentiation. The newer application architecture can also support functionality to support services to enhance customer shopping experiences and their lifestyles.
Benefit Rating: High
Market Penetration: 20% to 50% of target audience
Maturity: Early mainstream
Sample Vendors: Oracle; PCMS; SAP; Toshiba
Recommended Reading:
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"Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
"Refocus on Point of Sale as a Strategic Enterprise Application in Transforming to a Multichannel Digital Business"
Unifed Price, Promotion and Markdown Optimization Analysis By: Robert Hetu
Definition: Sometimes referred to as "life cycle pricing optimization," unifed price, promotion and markdown optimization uses predictive analytics and optimization capabilities to plan and manage every aspect of pricing (initial, regular, promotion and markdown) for retailers and other providers of direct-to-consumer commerce throughout the life cycle of an item.
Position and Adoption Speed Justification: Gartner recently updated its "Market Guide for Unifed Price, Promotion and Markdown Optimization Applications," and as expected, promotion and markdown optimization are exceeding 60% implementations in the U.S. and U.K. Although a unifed pricing approach is currently available from many vendors, individual implementations of price, promotion and markdown optimization must be weighed against the unifed implementations. Gartner has detected some movement in the technology during the past year. At this point, there are many single or multiple implementations, but few completely unifed instances. We expect unifed pricing to accelerate in the near future, because of continued interest in product life cycle optimization. Multichannel pricing strategies are of particular interest for Tier 1 retailers, which have also delayed forward movement of this technology. The delay is driven primarily by two factors: lack of completed implementations and complexity of pricing strategies. Gartner predicts that, by 2018, 40% of Tier 1 multichannel retailers will execute consistent pricing with situational differentiation.
User Advice: Optimization requires the use of advanced scientifc algorithms. More retailers are adopting SaaS and cloud-based solutions, allowing them to take advantage of the latest science and application benefts without the expense and complexity of internal development. Newcomers to price optimization should start with a single process and merchandise area (for example, markdown of fashion items only), and then progressively add other areas as the organization gains experience. Selection of the initial optimization type will depend heavily on the business impact for sales and proftability. Retailers considering promotion optimization should start building causal and historical event databases (for example, knowing when an item was on promotion, and whether it was supported by an end cap, circular and so on).
Retailers looking for a unifed price optimization solution should ask vendors to demonstrate how the types of optimization work together. A longer-term consideration for retailers is to understand how unifed price optimization will ft architecturally with other optimization areas in merchandising and the supply chain.
Business Impact: This technology provides more-effective pricing and promotion planning throughout the entire life cycle of merchandise. Retailers using this technology have experienced improved margins and sales, as well as improved effciency in pricing and promotion operations.
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Gartner has seen 30- to 100-basis-point improvements in gross margins in various product categories, as well as a reduction in the negative sales impact from showrooming. In fact, Gartner research shows that the most effective retailers are more than twice as likely to be using a life cycle pricing approach.
Benefit Rating: High
Market Penetration: More than 50% of target audience
Maturity: Early mainstream
Sample Vendors: dunnhumby; IBM; JDA Software; Oracle; Predictix; Retail Express; Revionics; SAP; SAS; Upstream Commerce
Recommended Reading:
"Market Guide for Unifed Price, Promotion and Markdown Optimization Applications"
"Prioritize 10 Best Practices for Successful Price Optimization Implementations"
Entering the Plateau
Mobile POS Analysis By: Miriam Burt; Joanne Joliet
Definition: Mobile POS refers to a point of sale (POS) application that is usually delivered on a retailer-owned, untethered wireless device to enable scanning, queue-busting or payment processing on the store foor.
Position and Adoption Speed Justification: A fast and hassle-free check-out experience features consistently in the top basics that customers expect when shopping in store.
Plotted at pre-plateau 5% and with current adoption levels in the latter half of the 20% to 50% range, this technology is expected to reach its Plateau of Productivity in the next 12 to 18 months, and we expect it to come off the Hype Cycle at some time in the next two years.
However, consumers' expectations in the digital business environment are demanding a move away from specifc mobile POS capability, which is mainly transactional, to offering POS on a mobile device alongside other functionality to enhance the customer experience. Supported by application architecture developments in POS, the emerging trend in in-store mobile devices will include the capability to conduct transactions as well as to accommodate endless aisle, clienteling, guided selling, cross-selling and upselling, targeted promotions, and integration to social commerce and the Internet of Things (IoT). This trend will continue to grow as retailers recognize that the need to provide relevant services to enhance customer lifestyles is an absolute differentiator as we move beyond multichannel and into digital business models.
User Advice:
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■ Make sure to understand the customer process when customers are making transactions in the categories you sell. Mobile POS is more suitable for some categories than for others (for example, more suitable for grocery categories, rather than categories that include high-margin, high-ticket items, such as consumer electronics or apparel, which might require the store associate to also conduct activities such as detagging and bagging).
■ Factor in the business case for mobile POS when looking at store-associate-facing applications — not just as a business requirement for POS upgrades at the main bank and self-check-outs, but also as a business requirement to be included when refreshing the traditional handheld application portfolio for store associates (for example, together with stock management and price-check applications).
■ Factor in the capability to support critical cross-channel transaction processes, such as reserve online, and check-out or pickup in the store. Digital business will demand fast and smooth delivery of these processes for competitive advantage.
■ Ensure that any applications you use for payment transactions adhere to industry data security standards, such as the Payment Card Industry Data Security Standard (PCI DSS), and data protection requirements. Note that the retailer is responsible for any third-party vendor's compliance with PCI standards.
■ When investigating third-party mobile POS applications on devices such as Apple's iPhone and iPod touch, consider how the third-party mobile POS applications that are developed specifcally for those devices will integrate with the main POS application running on the fxed check-outs in the store.
■ Use upgrades to handheld devices or to the POS as an opportunity to implement the transactional capability of POS alongside functionality to enhance the customer experience.
Business Impact: Customers cite faster check-outs as a key customer service basic requirement and express a preference for store associate involvement in the check-out process. Mobile POS can improve queue management during the check-out process, especially during peak trading periods, such as the Christmas holiday season, leading to saved sales.
If appropriate for the business model, retailers operating smaller-footprint, compact stores should consider mobile POS to replace fxed check-out areas, thus releasing foor space for more merchandising.
Benefit Rating: Moderate
Market Penetration: 20% to 50% of target audience
Maturity: Mature mainstream
Sample Vendors: Aptos; Fujitsu; Manhattan; NCR; Oracle; PCMS; Starmount; Wincor Nixdorf
Recommended Reading:
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"Implications of Customer Expectations on Retail Business Strategies and Technology Investments for Digital Business and Beyond"
"Refocus on Point of Sale as a Strategic Enterprise Application in Transforming to a Multichannel Digital Business"
Appendixes
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Figure 3. Hype Cycle for Retail Technologies, 2015
expectations Advanced Analytics With Self-Service Delivery MC Master Content Management
Multichannel Location Analysis Augmented Reality in Retail
Real-Time Store Monitoring Platform Retail 3D Printing Intelligent Virtual Store Design Digital Wallets in Retail Multichannel Customer Analytics Real-Time MC Customer Offer Engines Social Commerce for Multichannel Retail Mobile POS Unified Price, Promotion and Markdown Optimization Multichannel Merchandise and Category Optimization Merchandise Java-Based POS Software Planning Multichannel Order Electronic Shelf Labels Fulfillment In-Store Self-Service: Customer-Facing Applications Multichannel Loyalty Multichannel Master Data Management for Retail Retail Digital Workplace Systems Customer-Centric Merchandising Retail Workforce Analytics Retail Mobile Payments Retail Mobile Shopping (Nonpayments) Retail Digital Coupons Multichannel Order Management As of July 2015 Peak of Innovation Trough of Plateau of Inflated Slope of Enlightenment Trigger Disillusionment Productivity Expectations time Plateau will be reached in: obsolete less than 2 years 2 to 5 years 5 to 10 years more than 10 years before plateau
Source: Gartner (July 2015)
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Hype Cycle Phases, Beneft Ratings and Maturity Levels Table 1. Hype Cycle Phases
Phase Definition
Innovation Trigger A breakthrough, public demonstration, product launch or other event generates signifcant press and industry interest.
Peak of Inflated During this phase of overenthusiasm and unrealistic projections, a furry of well-publicized Expectations activity by technology leaders results in some successes, but more failures, as the technology is pushed to its limits. The only enterprises making money are conference organizers and magazine publishers.
Trough of Because the technology does not live up to its overinfated expectations, it rapidly becomes Disillusionment unfashionable. Media interest wanes, except for a few cautionary tales.
Slope of Focused experimentation and solid hard work by an increasingly diverse range of Enlightenment organizations lead to a true understanding of the technology's applicability, risks and benefts. Commercial off-the-shelf methodologies and tools ease the development process.
Plateau of Productivity The real-world benefts of the technology are demonstrated and accepted. Tools and methodologies are increasingly stable as they enter their second and third generations. Growing numbers of organizations feel comfortable with the reduced level of risk; the rapid growth phase of adoption begins. Approximately 20% of the technology's target audience has adopted or is adopting the technology as it enters this phase.
Years to Mainstream The time required for the technology to reach the Plateau of Productivity. Adoption
Source: Gartner (July 2016)
Table 2. Beneft Ratings
Benefit Rating Definition
Transformational Enables new ways of doing business across industries that will result in major shifts in industry dynamics
High Enables new ways of performing horizontal or vertical processes that will result in signifcantly increased revenue or cost savings for an enterprise
Moderate Provides incremental improvements to established processes that will result in increased revenue or cost savings for an enterprise
Low Slightly improves processes (for example, improved user experience) that will be diffcult to translate into increased revenue or cost savings
Source: Gartner (July 2016)
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Table 3. Maturity Levels
Maturity Level Status Products/Vendors
Embryonic ■ In labs ■ None
Emerging ■ Commercialization by vendors ■ First generation
■ Pilots and deployments by industry leaders ■ High price
■ Much customization
Adolescent ■ Maturing technology capabilities and process ■ Second generation understanding ■ Less customization ■ Uptake beyond early adopters
Early mainstream ■ Proven technology ■ Third generation
■ Vendors, technology and adoption rapidly evolving ■ More out of box
■ Methodologies
Mature ■ Robust technology ■ Several dominant vendors mainstream ■ Not much evolution in vendors or technology
Legacy ■ Not appropriate for new developments ■ Maintenance revenue focus
■ Cost of migration constrains replacement
Obsolete ■ Rarely used ■ Used/resale market only
Source: Gartner (July 2016)
Gartner Recommended Reading Some documents may not be available as part of your current Gartner subscription.
"Understanding Gartner's Hype Cycles"
"Transforming to a Customer-Led Digital Business in Retail Primer for 2016"
"Orchestrating Execution of Critical Channel Operations in Retail Primer for 2016"
"Implementing Customer-Centric Merchandising and Marketing in Retail Primer for 2016"
"Improving Loyalty and Retention in Retail Primer for 2016"
"Hype Cycle for Retail Technologies, 2015"
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"Predicts 2016: Digital Business Uproots Traditional Retail Revenue Generation"
"Algorithmic Retail; Merchandising Leads the Way"
"An Overview of the Strategic Technology Map for Tier 1 Multichannel Retailers"
"Cool Vendors in Retail, 2016"
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