Analyzing baskets and behavior, 3×3 Insights provides more valuable data
By W. R. Tish
With today’s POS technology, so much sales data is available at the touch of a button that we almost take it for granted. Sales by product, category, time frame, price point, etc. But the data just beyond what’s evident can make a huge difference. 3×3 Insights (3x3insights.com) specializes in next-level data analysis, not just of sales but also purchase patterns. Information presented in the 3×3 DataBar enables merchants to proactively retarget customers with offers that drive more in-store visits and increase basket size.
Which Pinot to Promote?
Consider this example: While deciding on stock purchases one month, a Retailer was given a deal on two Pinot Noirs from their distributor and wanted to pick one to discount and promote.
Using 3x3’s basket analysis technology, the Retailer saw a full view of how Brand #1 performed compared to Brand #2, as well as the market as a whole. Total sales of Brand #1 and Brand #2 were comparable; but the contexts of their sales were not. While the Brand #2 buyer, who visited the store five or more times a month and bought only one other item each time, Brand #1 buyers were often (44% of the time) first-time customers and had baskets close to $80 a visit.
Based on these findings, the retailer went forward with purchasing and promoting Pinot Noir Brand #1. The sale was incredibly successful in driving revenue. During the promotional period in 2017, the Retailer saw Brand #1 enjoy a 65% lift in sales compared to the same period in 2016, increasing the total revenue for the store by more than $10,000.
One Level Deeper
With the 3×3 DataBar, the Retailer was not only able to pick the right wine for the promotion, but also was able to more effectively price and position their products.
After learning that the Brand #2 buyer was a regular, the store managers knew that they could raise the price minimally without worry that the customer would shop elsewhere. They also repositioned products in the store to try increasing basket prices. With customers walking past other products commonly bought with Pinot Noirs on their way to their regular Brand #2, the opportunity to buy more increased.
Knowing that the Brand #1 buyer was usually a first-time customer, and that the brand was often bought with other high-margin wines, the retailer was also able to rearrange end caps and displays to increase purchases.
The case of picking the right Pinot is a single example of how richer, deeper data analysis can benefit retailers. On the highest level, comparing market share across different varieties of wine, liquor or beer help narrow down which categories you should be selling and promoting. Deeper down, you can compare the market share of specific brands across their categories and other details that will lead you to exactly the right product for promotion.