technology SOLUTIONS GUIDE Analytics Sharpens

Customer Portraits Joel Vincent Director of Product Marketing New data sources, including location-based and social, Aerohive bring greater clarity to retailers’ view of shoppers It’s a paradox of business analytics: the more data that’s available about custom- ers and their activities, the harder it can be to find the insights that support solid decision-making. Retailers can now learn about shopper likes and dislikes via so- Diane Neaven Senior Director, Retail cial networks, and can minutely track store traffic patterns with video analytics Product Marketing and location-based applications using their stores’ wireless networks. But the task Epicor Software Corp of translating these new and emerging data sources – along with existing data sets from transaction histories and loyalty programs – into actionable insights remains a challenge. Retail business intelligence and analytics solutions are now scaling up to accommodate the larger volumes and greater variety of Big Data-sized da- tabases. When they are used to create sharply delineated portraits of customers, Kevin Walker these tools can help retailers predict what shoppers will do, what messaging they SVP, General Manager, Americas will respond to, and how to more fully engage them for the long term. Manthan Systems

Retailers are al- transactions and merchandise at a lower data, particularly unstructured data gener- ready accustomed level, in greater detail. This means being ated by social media. Retailers now engage to dealing with able to track and interpret an ever greater their customers with everything from Face- Q large databases. volume of data, to define more complex book and Twitter to Pinterest, so they must What is different about the and subtle patterns of cause and effect, be able to make sense of the qualitative in- current iteration of ‘Big and to apply that information in more ag- formation available in those channels and Data’, and what challenges ile, effective, and localized decision-making leverage it in meaningful ways. does it present to retailers? about product distribution, customer pref- The third difference between the ear- DIANE NEAVEN: Big Data is expanding erences, seasonal trends and pricing. This is lier and current generation of analytics is opportunities for today’s retailers – and where the potential advantages of Big Data that it will challenge many retailers to trust challenging their capabilities – in three key really come into play – and why it is fast their data and systems more thoroughly. ways. The first stems from their need to becoming an imperative of competition. To be effective in the world of Big Data, gain a clearer and richer view of their op- A second and related opportunity and your managers and buyers can no longer erations by understanding their customers, challenge is to accommodate more types of act on what they observe directly or believe

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instinctively; instead, they must be able to “To be effective in the world of Big Data, your managers and buyers trust complex analytics generated well be- yond their direct line of sight. can no longer act on what they observe directly or believe instinctively; instead, they must be able to trust complex KEVIN WALKER: It’s true that large data stores are not new to retailers. In general, analytics generated well beyond their direct line of sight.” the capture and processing of data is not Diane Neaven, Senior Director, Retail Product Marketing, the issue in the current iteration of ‘Big Epicor Software Corp. Data.’ Over the years, both data volume and velocity has increased so dramatically that these advances have become an expec- tation. However, it’s when new varieties of online retailers have been extremely suc- WALKER: The first step to valuable insight data, in particular unstructured and exter- cessful is a data-driven understanding is collecting data into a single repository. nal data sources are introduced to the mix, of each customer created by analyzing Without a single database that spans all that the retailer is challenged with captur- and processing data from browsing activ- channels, whether in-store, online and/ ing and processing, but more importantly ity. Doing this, websites are able to gather or social, that provides a 360-degree view understanding, which pools of data to use unique customer insights and offer recom- of the customer, it is very difficult to glean and aggregate in such a fashion as to derive mendations to make the shopping process insights regarding behavior and purchase competitive advantage. This end cannot be more painless and convenient and actually preferences. Once the data is consolidated, wholly satisfied with the new and improved increase the average ticket. Thanks to real- retailers can leverage analytics applications IT toolsets for unstructured data crunching. world analytics facilitated by something ev- to realize insights regarding product affini- It also requires a culture of advanced ana- eryone is starting to take for granted (WiFi), ties, ideal product pricing and promotions lytics, and furthermore the ability to execute it’s now possible to compete with this abil- and relevant marketing communications. on analytical strategies throughout the retail ity in an offline world using analytics of For instance, once the brick-and-mortar organization with a true business solution. real-world mobile devices. By installing a retailer identifies a product affinity, this re- sensor in a physical storefront that detects tailer can tweak space allocation and place- The most competi- WiFi capability and unique tags from cell ment, pricing, cross-promotions, or sales tive online retailers phones, the right analytics service can pro- tactics (POS or location-based prompts) to have been extremely vide complete anonymous metrics such leverage this particular insight that formu- Q effective at ana- as traffic, repeat visitor ratio, ‘walkbys,’ lates new shopping habits and that increase lyzing customer activity. visit duration, and many others. Brick- customer spend. How can brick-and-mortar and-mortar retailers can then use an un- retailers gain equivalent derstanding of this data to get actionable NEAVEN: Retailers need to have cohesive levels of insightS about insights into real-world shopper behavior strategies and capabilities that actively their customers’ activities? and optimize business operations around encourage cross-shopping in-store, multi- joel VINCENT: Among the reasons why their customers’ needs. channel shopping (since multi-channel shoppers spend more than their single- channel counterparts), and that support unified analytics. This is another area in “The first step to valuable insight is collecting data into which Big Data can help by identifying a single repository. Without a single database that spans shopping patterns and purchase correla- tions for more profitable, customer-centric all channels, whether in-store, online and/or social, that product placements, offers and trigger mes- sages at the point of purchase. Without the provides a 360-degree view of the customer, it is very right analytics tools, these opportunities too difficult to glean insights regarding behavior and often go un-noticed or are forfeited with no follow-up. I recall buying two of the same purchase preferences.” tops in different colors from one of my fa- Kevin Walker, SVP, General Manager Americas, Manthan Systems vorite retailers, giving them a perfect chance to leverage my known color and style prefer-

18 J U N E 2013 RIS NEWS.COM Technology solutions guide BI/Analytics/Big Data

ences. Later, I learned that same top came in other colors I hadn’t seen or that were not “When are the bulk of your repeat customers coming in? in stock at that time and location. If they told me that at the POS and reached out to How do they walk through the store? Where should the me with an offer, they could have easily dou- end-caps be? All this insight can be gained by using the right bled the sale. Wasted information is wasted profit – it’s as simple as that. WiFi infrastructure and Big Data analytics to provide

How can retailers tangible benefits to the store.” maximize the value Joel Vincent, Director of Product Marketing, Aerohive of location-based Q solutions to provide BI insights? trends early to maximize transaction size, the vision with insightful analytics, the final VINCENT: There are many things this data but also the application of predictive analyt- piece in the puzzle is guiding the user in can help retailers with, including: ics to support personalization and segmen- implementing the right strategic action. • Identifying customer behavior – re- tation efforts across product mix, pricing, peat visits, commonly travelled path promotional offers and communications. NEAVEN: The need for Big Data is by now through the store, unique visits (to under- well-established; the challenge going for- stand marketing’s effectiveness in attract- VINCENT: First and foremost, the market- ward will be to keep pace with change. In ing new customers), and many more to ing department. Marketing programs can an era in which few retail offerings are truly optimize marketing dollars. now be optimized. Everything becomes unique, competitive advantage will go to • Individualized marketing channels – measurable around customer behavior. those retailers who can continually refine sending rewards and promotions directly to And if you can measure it, you can op- their knowledge of who is buying and seek- customer devices via a good WiFi infrastruc- timize around it by understanding your ing what, where and why, and to act on that ture increases the average ticket amount objectives and key performance indica- knowledge in highly efficient ways. and ultimately the per-store revenue. tors. You even have the ability to ‘A/B test’ • Effective store management – by us- a marketing program. ‘A/B testing’ is very VINCENT: ‘Boiling the ocean.’ I see MANY ing the WiFi built into everyday phones common for online retailers (which ver- retail analytics solutions out there. Video you can start to combine the understand- sion of a banner ad performs better, for ex- cameras that analyze the footsteps of ing of customer behavior and the ability ample). Now you can test two promotions people walking around and count change to reach out to customers who opt in to across different stores and see which version of direction and speed of their walking. a loyalty program to better merchandise of the promotion brought in more new cus- That’s a massive amount of data. But the your store and create many more buying tomers (if that was the goal). Then the bet- amount of data doesn’t matter as much as opportunities. ter promotion can roll out nationwide. how usable the data is. Don’t boil the ocean. Break down retail analytics into usable parts Which areas within Going forward, – use your WiFi infrastructure and people’s the retail enterprise what do you see phones that they already have, for instance will benefit the as the biggest – then implement the technology incremen- Q most from insights Q challenges for tally. Gaining an understanding of how the generated by Big Data- retailers in this area? data is relevant is more important than the fueled analytics? WALKER: I see two distinct challenges for ‘bells and whistles.’ Once you gain insights WALKER: All areas of the business can retailers. First, the threat of analysis paral- that level the playing field with online retail- significantly benefit from insights derived ysis becomes more significant with greater ers, then you can move on to very sophisti- from Big Data-fueled analytics. However, access to data, especially data from mul- cated systems that can provide advantages the departments that can leverage Big Da- tiple sources with varying standards. The that online retailers cannot gain. But online ta-fueled analytics to maintain relevance second challenge is the inability to balance retailers should be given credit: the basic in- in the eyes of the customer can benefit strategy and execution. Yes, retailers need sights they gain on customer behavior and enormously. This entails using analytics to applications to provide real-time informa- the ability to push things in front of the cus- evolve from a product-centric to customer- tion across a larger swath of data stores, tomer has created a sustainable advantage centric marketing and creative merchandis- but they also need these applications to for them…until today when the mobile-first ing approach. Not only does this require distill the data in a manner that is useful generation has provided us a way to gather flexible, intuitive retail analytics to identify for the end user. After the retailer obtains the same intelligence. RIS

20 J U N E 2013 RIS NEWS.COM Technology solutions guide BI/Analytics/Big Data

COMPANY NAME/ WEBSITE RELEVANT PRODUCT/SOLUTION KEY CLIENTS

1010Data Market Basket Analysis, Loyalty Card Analysis, Dollar General, Rite Aid, Vitamin Shoppe www.1010data.com inventory optimization, out of stock analysis

Aerohive www.aerohive.com Retail Analytics 7-Eleven, Drakes Supermarkets SEE AD ON PG 17

Alteryx www.alteryx.com Strategic Analytics VF Corporation, Walmart

Applied Predictive Test & Learn for Sites, Test & Learn for Customers, Technologies (APT) Test & Learn for Ads, Market Basket Analyzer, Abercrombie & Fitch, Chico’s, Staples www.predictivetechnologies.com Merchandise Optimization, Performance Manager

Epicor A.C. Moore, Canadian Tire, charming www.epicor.com Retail Suite, Eagle SEE AD ON PG 19 charlie

IBM www.ibm.com Smarter Analytics Barnes & Noble, Dillard’s, OfficeMax

Infovisionix www.infovisionix.com Retail Data Warehouse N/A

Kronos www.kronos.com Workforce Ready, Workforce Central The Container Store, , PUMA

Lighthaus Logic www.lighthausvci.com Visual Customer Intelligence (VCI) System Champs Sports, Foot Locker

Manthan Systems ARC Merchandise Analytics, ARC Customer Analytics, www.manthansystems.com ARC eCommerce Analytics, ARC Store Operations, Crocs, Love’s, Sprouts SEE AD ON PG 21 ARC Human Resource Analytics

MicroStrategy www.microstrategy.com Intelligence, Express, Cloud Guess?, Limited Brands, Lowe’s

MI9 Aubuchon Hardware, Barneys New York, Business Intelligence, SMART, Retail Hub www.mi9retail.com Crabtree & Evelyn

Nuevora Big Data and Market Analytics, CRM Analytics, N/A www.nuevora.com 360-Degree Analytics

Oracle Customer Analytics, Data Model, Merchandising Burlington Coat Factory, Deckers Outdoor, www.oracle.com Analytics, Workspace Finish Line

Panorama www.panorama.com Necto, BI 3.0 for Retail Office Depot Israel

22 J U N E 2013 RIS NEWS.COM The chart below provides information on solutions in a specific category to help retailers begin their search for vendors in the RFP process. The chart is not a comprehensive resource. Please visit

vendor websites for further information.

COMPANY NAME/ WEBSITE RELEVANT PRODUCT/SOLUTION KEY CLIENTS

PivotLink www.pivotlink.com RetailMETRIX, DataCLOUD, AnalyticsCLOUD Carhartt, Party City, REI

Predictix www.predictix.com Forecasting, Planning, Pricing & Promotions Crate and Barrel, dELiA*s, Rent-A-Center

Profitect www.profitect.com Profit Amplification Suite, QuickInsight Abercrombie & Fitch, Weis Markets

Qlikview Decision Orchestration Platform, Enterprise Data Burlington Coat Factory, DXL Group, Pacific www.qlikview.com Model (EDM), Retail Exception Engine, Q Foundation Sunwear

People counting, loss prevention, marketing & RetailNext www.retailnext.net merchandising, POS exception reporting, Caché, Gander Mountain, Gordmans queue optimization

Revionics Performance Intelligence, Advanced Analytics, Cabela’s, Dick’s Sporting Goods, Family www.revionics.com End-to-End Merchandise Optimization Suite Dollar

SAP BusinessObjects, Lumira, Crystal Reports, Predictive Ace Hardware, eBay, Chico’s FAS www..com Analysis

Demand Forecasting, Intelligent Clustering, SAS www.sas.com Forecasting, Revenue Optimization Suite, Size AutoZone, Brooks Brothers, Macys.com Optimization

Scopix Real.Engagement, Real.Suite, Real.Merchandise, N/A www.scopixsolutions.com Real.People

ShopperTrak Managed service, business analytics, interior charming charlie, Crate and Barrel www.shoppertrak.com analytics

Tableau www.tableausoftware.com Retail Analytics Barnes & Noble, eBay

Big Data Analytics, Business Intelligence, Data Teradata , Hallmark, METRO Governance, Demand Planning, Data Mining & www.teradata.com Group Analytics

Unit4 Coda www.unit4software.com UNIT4 Business Analytics IKEA, Jordan’s Furniture iInside, a WirelessWERX Precise Indoor Location technology, Location company Business Intelligence, Consumer Traffic Analytics N/A www.iinside.com and Indoor Engagement Solutions

YFind www.y-find.com TheRetailHQ N/A

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