I had a very engaging call today with a large retailer; we spoke at length about how to understand the customer and to use this understanding to create change. Change in assortments, store design, service, etc. all have to derive from this understanding. As the call progressed it reinforced to me the importance of understanding behavior. Behavior is the key to knowing how a customer will react to a particular experience. It is the key to becoming more prescriptive in all areas of retail.
I have blogged and written research to help explain this concept so here I will try not to be repetitive. As a retailer ask yourself if you really know why a customer purchased chose a particular product, a certain checkout, or why they shop on a particular day or time? Demographics can help to answer the question but they only scratch the surface.
Three women are shopping for ketchup on isle 4. All have similar jobs and income, live in a similar neighborhood, and have a husband and 2 children. All are looking for a family size bottle of brand X. Unfortunately the family size of brand X was out of stock. Customer 1 reviews the options and chooses to purchase a smaller size of brand X. Customer 2 reviews the options and walks away. Customer 3 opts for the family size bottle of Brand Y. Can we determine what happened here? Only through behavior analysis can we begin to understand these complex dynamics that are occurring thousands or millions of times a day. What caused them to behave this way and can we predict it?
First of all, shame on us for being out of stock on brand X. Putting that aside customer 1’s family have a brand affinity and preference for brand X and she is too busy to make another stop. Customer 2 is brand conscious but also very price sensitive so she is not willing to buy the more expensive smaller bottle. Since the product she wanted was not there she decided to wait until her next visit. Customer 3 doesn’t care what brand it is or how much it costs and just wants to get home. Only through in-depth customer analytics can we understand and ultimately predict demand transference for ketchup on isle 4 in Rapid City, SD. Back in 1925 the shopkeeper would know exactly what each customer was looking for and would understand their level of substitutability. Through technology we must replicate this personalized experience to the best of our ability to meet the demands of the customer.
100 Data and Analytics Predictions Through 2024
Gartner’s annual predictions disclose the varied importance of data and analytics across an ever-widening range of business and IT initiatives. Data and analytics leaders must consider these strategic planning assumptions for enhancing their vision and plans.Read Free Gartner Research
Category: customer-analytics data-and-analytics-strategies merchandising-process retail-analytics retail-trends
Tags: analytics assortment bi consumers customer-analytics customer-centricity merchandising retail satisfaction
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.