Authors:
Shay Merchant, Liah Carpenter, Suzanne Griep, Sean Hebert, Blair Helms, Natalia Kechedzhieva, Collin Kersten, Linda Newton, Donna Roberts, Matthew Slessman, Jessica Snead, Scott Summey
Abstract:
This disclosure proposes using individual customer statistics to perform predictive inventory analysis, based on the shopper’s purchase history, including shopping habits such as frequently bought items and usual shopping times. From this data, the store can determine when specific items sell out and use this information to send targeted notifications to customers.
Background:
Many grocery shoppers purchase the same items on a regular basis, yet the store inventory is hard to predict from the customer's point of view. Shoppers expect their regular items to always be in stock and become frustrated when they are not. For example, if a shopper buys three gallons of milk a week, they expect the store to be able to maintain the stock to support them. Some stores show stock availability on their websites, but most grocery stores do not.
Description:
Based on aggregate and individual shopper purchase history and current orders, it would be feasible to use individual customer statistics to perform predictive analysis on future product demands.
With this solution, the store uses predictive analysis drawn from member shop history to know what day the customer is likely to shop. On a larger scale, the store will look at aggregate data involving all loyalty customers’ shopping habits including frequently bought items and usual shopping times. This can include shopping trends based on the daily rush, weather forecast, etc.
From this data, the store will be able to determine when specific items sell out and use this information to send targeted notifications to customers. For example:
- A shopper often buys a particular brand of milk in a certain quantity each week
- The store knows that this shopper always buys milk on Mondays, and that this particular brand sells out at 6 PM (via known shopping trends and predictive analysis of future shopping trends)
- Store prompts the customer with a notification with plenty of time on Mondays that their favorite milk brand is in stock and that they should purchase their order now before the rush comes in.
This helps to mitigate customer frustrations with deficient stock and inventory while optimizing the shopping experience.
TGCS Reference 2579
