The game is has changed in retail. Gone Retail Product are the days where retailers can simply pick the products recommended to them Recommendations by merchandisers or partners. Data NEAL ANALYTICS WHITEPAPER driven, technology competent and price sensitive millennials are more than happy By David McClellan to browse online until they find exactly what they want, and comparison shop until they find where they can buy that item the cheapest, fastest, easiest return, etc. In such challenging times, retailers are racing to use everything they know about their customers to add value back to the brick and mortar retail experience. In this whitepaper, we will explore the various ways in which retailers, particularly in fashion and other fast moving markets, stand to benefit from innovative and responsible use of data and analytics to enhance their in-store and omni-channel experience. Retail Product Recommendations Remaining Competitive in a Rapidly Changing Industry Understanding 21st century prices in tune with the market Customer Buying Patterns price for any goods that are not Nearly every piece of market private label or exclusives. research released in the last Having a solution providing this decade touches on the same capability is essentially table principle- The internet and stakes in what is currently a technology has brought some highly competitive global sales incredible new capabilities, but environment. With price often just as companies are using dictated by external factors, The customer deserves a good these to help their businesses, retail outlets must look for value exchange; it must be customers are becoming more other options of how they can clear to her how he or she is adept at using them in pursuit bring customers to their benefitting from sharing his of the best deals available. With businesses. or her information with the such information overload, retailer, and how their building customer loyalty and Leveraging Customer Data for information contributes to offering the right products in a Personalization Opportunities delivering a frictionless market trends that move faster Perhaps the most obvious and shopping experience. than suppliers can keep up is a common path forward surfaced constant battle. is to tailor promotion and ShiSh Shridhar- Worldwide In truth, the root problem runs advertisement activities to each Director, Retail Industry much deeper. The fundamental market, customer demographic customer buying patterns have Solutions at Microsoft group, or individual customer. changed with each passing The ideal outcome being a generation. Baby boomers and customer who wasn’t already Gen X are the old standard: going to buy that product Visit a B&M store, locate the seeing more relevant marketing product category they’re after, or promotions and buying the evaluate the prices and decide item. These analyses commonly then and there whether they use socioeconomic as well as are going to buy something. If demographic data, combining the price is too high, they’ll wait it with historical purchase until it goes on sale and then patterns to produce customer perhaps buy it. Millennials and personas. Recommendations at subsequent generations have the individual level come from developed much more complex comparing an individual’s patterns. The most common of purchases with others from which is browsing endlessly their persona/segment and using the internet until they trying to fill in the gaps. find exactly the SKU that they Understanding your customers’ want, and searching for that preferences has obvious value, SKU all across the internet for but situations like this require where it is sold. Once they vast amounts of data and an locate where they can find it for engaged customer base willing the best price, fastest delivery, to interact with apps that most convenient or best generate said required data. If experience, they purchase. It is the data isn’t granular enough, practically essential for most recommendation success rate retail markets to keep their drops significantly and further Retail Product Recommendations Remaining Competitive in a Rapidly Changing Industry data feeds are often required to that perfect fitting pair of jeans. with varying levels of complexity, determine the right product for She might be browsing in store with the right partner and sales team, mobile apps, or and a sales associate approaches outcome in mind the marketing materials to offer. her recommending a popular cut implementation is not as much of There are a few ways to bridge or fit purchased recently by other a moonshot as perceived. this gap without such feeds, and customers, but if that seller had Simple tools like RFID embedded the simplest one is keeping a the ability to see that each prior in membership cards paired with solid repository of product jean purchase this customer had readers at each entrance can attribute data. Instead of simply made were low rise bootcut, surface alerts on dashboards or building recommendations by she’d know exactly which to push notifications to nearby offering items which were viewed recommend. To do this, brick and sellers, instructing them with or bought by other users who mortar stores need to know who specific, tactical actions to viewed or bought that item, it customers are when they walk in enhance experiences, driving makes much more sense to try the door or approach a sales increases to customer lifetime and determine the root need the associate. While there are a value. customer is trying to fill. Let’s variety of technology solutions take a customer shopping for on the market to accomplish this Market Sales Drivers insights to actively increase and equally critical. Nearly without exception, almost manage their demand. While Bringing in relevant data for the every retail and consumer goods such answers are useful for selling regions around stores and company we have spoken with operations and sales execution, it outlets, as well as operations data has expressed an interest in turns out that knowing which within the store helps provide understanding why they sell the internal levers and external this more complete view of a amount they do each day, for if factors are most impactful is also customer buying decision. Does they can understand why a fundamental to recommending the store have significant particular store’s sales were up the right product. Just as competition nearby? Is it close to on a particular day or why a maximizing an understanding of a school, office, or park? What is customer bought 5x their normal customers and which products the average household income or average purchase size, that they buy is important, the context ethnic makeup in the area? Has retailer could leverage these within which they buy them is something been trending on Retail Product Recommendations Remaining Competitive in a Rapidly Changing Industry social media or the online out projections, the retailer can personalized offer. Sometimes channel? How about the direct customers to evaluate no promotion is required, but if weather or upcoming holidays? products which they are likely a seller approaches a customer These questions can all be to buy but also high in stock, a with the authorization from the answered by engineering the retailer can avoid stockouts and system to give that customer a right features and testing their “push” more of their product “for you only” discount on an predictive power in a variety of out of the door and into item they know is relevant to machine learning algorithms. If consumers’ hands. their interests but unlikely to buy a business can understand the This can be taken even further at the listed price, the sale can relationship between these through profitability analyses be made. Combine this with the factors and sales for certain which identify the most profit above analyses on SKU products or categories, tactical to be generated among those availability and profitability, the interventions can be made to potential recommendations. cost of such a personalized offer promote or recommend SKUs The result is an algorithm which is effectively minimized and the that are the best fit for that directs customers to products additional revenue more than situation. which have ample stock, are makes up for it. most profitable, and most likely SKU Assortment & Inventory to be purchased by the buyer. Extending into IoT Optimization While all these analyses can be powerful game changers on This demand driver analysis can Promotion Optimization their own, none is perhaps more be taken even further by Finally, in exchange for the data “cool” than the tracking of understanding which product they share for personalization individual customers’ movement assortments are ideal for each and their continued loyalty, in store and surfacing offers for location. This analysis compares customers command immense products they are looking at. the assortment of products at power to compel retailers to In partnership with Footmarks, similar stores to identify which offer competitive discounts, Neal Analytics developed a POC products bring customers into promotions, and other offers. for recommending products to a store and not only buy that Through analyzing the success customers using all of these product, but purchase others, and utilization of various analyses combined for a full raising overall store sales as historical promotions, a retailer 360° picture of how product well. is able to identify the most cost recommendations of the future However, in retail, identifying effective options to increase might operate. the products which increase purchase likelihood within a overall store sales is only half of the problem. It solves part of the “pull” demand by finding products that will be in the highest demand by that local customer base. However, it is often the case that inventory management is as much a function of clearing out product as it is putting it in the store. This is where it connects to product recommendations.