You’re Not Going Crazy — You May Actually Be Paying Higher Prices Than Other People

Starbucks, a Seattle-based coffee chain, has been using artificial intelligence (AI) to create personalized offers for its customers. This personalized pricing strategy is not unique to Starbucks, but companies are increasingly leveraging customer data, often derived from loyalty programs, in coordination with machine-learning models to uniquely price goods and services based on an individual’s willingness to pay. The goal is to get customers to buy more items, buy the same items again, or spend more on the same items.

Traditional marketing tactics, such as segmenting customers who exhibit similar purchasing behavior and preferences, have been used to effectively offer different prices to different groups of consumers. However, advancements in AI have made these predictions more sophisticated and accurate. Companies can now answer questions like, “What is this person going to buy next? What do we think they’re going to be willing to pay? Where are they going to buy from? When are they going to buy it?”

Revionics, an AI company that specializes in helping retailers set prices, provides companies with analytics and predictive scenarios to figure out prices themselves. Instead of waiting for customers to respond in real time to price changes, Revionics’ clients get a toolbox to test out prices in advance. By predicting how much consumers will buy at different price points, Revionics helps retailers manage their inventories.

The personalization even extends beyond prices to targeting customers. For instance, a notification you receive informing you of a sale may be worded completely differently from a notification another customer receives of the same sale. Tractor Supply Co. recently announced it partnered with Revionics to more successfully adjust prices to the ever-changing market to “attract and retain customers.” The aim of partnering with Revionics was not to see how high they can raise their prices without turning away too many customers, but to curate specific offers individualized for customers. This often leads to lower prices and better value on the products and services our customers need.

However, it could also lead to identifying customers who don’t require promotions at all.

Read More @ CNN