How Cosentino’s Food Group uses Goodlight AI to drive repeat store visits without discounts

The challenge: Growing sales without training shoppers to wait for discounts

Regional retail chains are already struggling with thin margins, and continuing to “buy” customers through discounting is no longer a viable option.

Grocery operates with extremely thin margins. Discounting, the most common promotion practice in the industry, hurts the bottom line. Cosentino’s partnered with Goodlight AI, who suggested testing the thesis that they could drive repeat visits without relying on discounts by making the buying experience hyperpersonalized to each shopper.

Like many grocery retailers, Cosentino’s had valuable customer information spread across loyalty and point-of-sale systems. The opportunity was bigger than sending more promotions: the team needed a clearer understanding of how shoppers behaved, what they were likely to need next, and how to turn those insights into relevant customer experiences.

The goal was to make every interaction more valuable. In doing so, they would encourage customers to shop more often and buy more on each trip.

Turning loyalty and POS data into personas

The Goodlight AI team brought loyalty and POS data together to analyze purchase behavior by individual shoppers. Using proprietary machine learning technologies, the team was able to generate specific personas of shoppers, based on their buying preferences, to create an overall profile of the shopper demographic. The models also predicted when the shopper would visit next and what they would buy.

This persona generation is a first in the market for retail grocery, and has been instrumental in giving retailers a deeper understanding of their shopper profiles.

Recommendations tailored to each customer

Goodlight AI combined the resulting personas and behavioral signals to generate product recommendations tailored to each shopper. Recommendations were grounded in what customers had bought, how they shopped, and what they were likely to find relevant. The personas allowed for deeper and more relevant product recommendations at the individual customer level than the current industry standard.

This created a more relevant path to growth: help customers discover products that fit their needs, build more complete baskets, and give them reasons to return. The goal was to bring back shoppers into the store more often.

From insight to action with Goodlight’s AI agent

The data and recommendations only create value when they reach customers with the right message at the right time. To generate individual, hyper-personalized marketing messages for hundreds of thousands of shoppers at once, Goodlight AI leans on an autonomous AI agent that determines the best phrasing for each shopper.

The agent also identifies each shopper’s cadence of store visits, and determines the right time to send the message. This agentic approach allows for the highest level of personalization to be offered in the retail grocery industry today.

Delivering industry first personalization

The core value comes from a level of personalization the industry has never seen before—where every single shopper receives an entirely different personalized email based on her purchase patterns and buying behavior.

This is different from what most vendors call personalization: simply changing shopper names and product mentions in emails are table stakes. Goodlight AI’s advanced models determine the best product to promote, the best offer to mention, and the best recipe to share based on each shopper’s persona.