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Analytics Sharpens Customer Portraits

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Analytics Sharpens Customer Portraits 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 SPONSORED BY PRODUCED BY TECHNOLOGY SOLUTIONS GUIDE BI/ANALYTICS/BIG Data 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.
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