Authors:
Kirk Goldman, Jon Hoffman, Manda Miller, John Pistone, Dan Coole, Peter Koliopoulos, Dimple Nanwani
Abstract:
Grocery retailers and consumer products manufacturers have struggled with introducing new products to shoppers. Crowd sourcing has become a common utilization of technology to advise consumers utilizing the similar experiences of others. Taste Finder/Taste Match utilizes the grocery data (structured and unstructured) to crowd source common interests and tastes from like-minded shoppers. The application would use anonymized grocery data from the crowd to compare with the user's purchase history. The solution finds commonality and generates recommendations (products, recipes, etc.) based on what others with similar tastes also purchase. The manufacturers would fund marketing initiatives to target shoppers with incentives who match profiles of those likely to purchase their goods and services.
Background:
Consumers are always looking to try new things... and grocery manufacturers are always looking for new shoppers to buy their products. In any retail segment or industry, everyone is always looking to optimize recommendations to consumers. For example, a prominent online Search Engine gets optimal dollars for their Ads when they know the search results will lead to a purchase. As players look for the moment of truth (when a consumer chooses a product to buy), this helps direct a consumer to that moment in a way that the retailer can engage and observe.
Description:
There are three profiling parts to the solution. First, historical basket analysis. The solution analyzes the shopping history from all the shoppers in a loyalty program. The analysis looks for commonality of purchases to determine interests, likelihood to buy other products, etc. Second, the participating shopper is given a tailored questionnaire to confirm and expand upon their tastes and interests. The questionnaire is developed based on their shopping history and potential interests as identified through commonality analysis. Third, the shopper goes through a gamified process to finalize interests... similar to a Prominent Site that uses... swipe left if you like this, swipe right if you do not.
Once comprehensive profiles of shoppers are finalized, manufacturers are given an opportunity to define their product attributes and enter a bidding process to create targeted offers for these clients.
Finally, the shopper gets a set of weekly recommendations and offers based on their interests, potential likes, and buying history.
TGCS Reference 1660
