Product Agents
Feature
Sarah Miguel Cournane
Sarah Miguel Cournane is a data scientist in Hello Retail's R&D department, splitting her time equally between understanding what has already happened in ecommerce data and deciding what needs to happen next. This is a special episode — recorded the week Hello Retail launched Product Agents — where the conversation pulls back the curtain on the data science that makes the product work. That means going into product intelligence, the vector space behind it, and how predictive and generative AI are being combined in a way Sarah describes as the perfect mix.
The technical centrepiece is product intelligence — Hello Retail's approach to personalisation that does not require knowing who a user is. The foundation is a vector space with more than 700 dimensions, where every product occupies a point defined entirely by its behaviour: what it is bought with, what it is not bought with, how it relates to everything else in the catalogue. When a new customer arrives, a single click is enough to draw on all the collective purchasing intelligence around similar products across thousands of stores. Two numbers anchor this: 30% of products drive roughly 70-80% of revenue, and 50% of products active in any catalogue today will not be there in six months. Product intelligence is what stops that constant churn from erasing everything the system has already learned.
Product Agents combines both sides of AI: predictive to choose the right product and the right moment, generative to write the message. The examples Sarah walks through are concrete — price drop emails for products a shopper viewed but never bought, replenishment timing based on package size (a 1kg dog food order signals a different reorder window than a 2kg one), and alternative recommendations when the original product is no longer in stock. Every trigger is decided by product intelligence. Every email is written by generative AI, in the brand's own tone of voice, in the customer's language.
That last point turned out to be more interesting than expected. Friendly in Spanish is not the same as friendly in German. Formal in Swedish carries different connotations than formal in Danish. The solution was building a matrix of tone-by-language combinations and verifying them at scale through automated quality checks — because reading thousands of emails across every language by hand is not possible. The end result, as Sarah frames it: the shop coming to the shopper, rather than the shopper having to go back to the shop.
Key takeaways
Three things to take from this conversation
Personalisation without personal data
Product intelligence works because products, unlike users, can be studied without privacy constraints. Every product is mapped by its purchasing behaviour across thousands of stores — what it is bought alongside, what triggers it, how it relates to similar items. A single click from a new customer is enough to draw on all of that collective intelligence.
50% of catalogue products change every six months
Inventory turns over constantly. If a customer viewed a mascara that is no longer stocked, a system that only knows user behaviour loses that intent signal completely. Product intelligence preserves it — by finding the closest alternative and sending a relevant email rather than going silent.
Friendly in Spanish is not the same as friendly in German
Tone of voice across languages is not just translation — it is a matrix of tone-by-language combinations, each requiring its own calibration. The engineering challenge behind Product Agents' multilingual voice was automating quality verification at scale: catching repeated words, overly childish phrasing, and accidental legalese across every market.
The guest
About Sarah Miguel Cournane
Sarah Miguel Cournane
Data Scientist · Hello Retail
Sarah Miguel Cournane is a data scientist in Hello Retail's R&D department. She holds a master's in business analytics from DTU, where her thesis explored AI-powered fashion recommendations. Before Hello Retail, she spent a year at a machine learning research centre in Japan. At Hello Retail, she works across product analytics, campaign analysis, and the predictive AI powering Hello Retail's product intelligence.
View on LinkedIn
Edited by
Nicklas Beran
Editorial Director, Hello Retail