Last Year’s Holiday Data Can Help Retailers in 2016
During the 2015 holiday season, retailers collected massive amounts of data from their customers. It can be easy to forget about this information during the hectic holidays, but as the New Year gets rolling retailers have a tremendous opportunity to score a competitive advantage in 2016. Many lessons can be gleaned from analyzing data collected at the register as well as using new tools such as video analytics. Combining different types of data can provide a more holistic view of brick-and-mortar shopping, as well as offer actionable insights on how retailers can create shopping experiences that earn new customers and preserve existing ones.
Here are three ways retailers can take advantage of the data they collected during the 2015 holiday season:
1. Understand shopping trends and make adjustments. Data analytics collected during the holiday season can help retailers understand shopping trends and make adjustments for the coming year. For example, by analyzing the flow of shoppers and how they move around the store, retailers can adjust endcaps and movable displays to improve sales. And by looking at both point-of-sale (POS) data and video analytics from holiday shopping, particularly Black Friday, retailers can understand what products sold — and what didn’t — and how shoppers responded to different offers.
Furthermore, POS data alone can be misleading. Was an item that sold well a first choice or was it a choice of last resort, while a higher-margin item was browsed by shoppers but not purchased because it was out of stock? Video data can show what was browsed on the shopper’s journey, while POS data provides what was actually bought.
2. Improve the destination experience. Analytics can also be used to help retailers identify if their store is viewed as a destination experience and a place people want to visit for more than just buying merchandise. Retailers can use analytics to compare the size of crowds moving through a store (down to the areas where they congregate) to the number of items sold. The insight from this analysis helps retailers improve the destination experience for shoppers, increasing the amount of time they spend in-store and interacting with merchandise, and ultimately increasing sales.
3. Enrich training programs for associates. Video analytics also provide insight into interactions between shoppers and store associates. Computer vision and video analytics, as well as human behavioral models, can measure sentiment, motivation and satisfaction in real time for both shoppers and associates. In addition to enabling department supervisors to help in closing sales in real time, these analytics can be applied to enhance training programs for associates.
Data analytics can provide valuable insight into how customers shop and how retailers can make changes to provide a better experience. Analytics which integrate data from traditional sources such as POS and inventory with emerging data sources such as video can provide deep insight into shopper preferences and behaviors. Retailers can take advantage of the data collected during last year’s holiday season to improve the brick-and-mortar shopping experience year-round.
Peter Paul is principal scientist at PARC, a Xerox Company, that provides custom R&D services, technology, expertise and IP.