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AI personalisation at the Retail Trust: the Netflix of wellbeing

Downloads | AI case studies

The Retail Trust uses AI personalisation to give each retail worker wellbeing support built for them, at about 50p a night. Poppie Foakes and Tim Walpole explained at aiblLIVE London 2026 how the 60-person charity built what Walpole calls the Netflix of wellbeing.

It started as a crisis phone line that 98% of people never used. After three stages of AI work, 20 to 25% of an organisation now use its services, mostly before they reach crisis.

Retail Trust in numbers

  • 20 to 25% of an organisation now use the Trust’s services, against about 2% for a traditional employee assistance programme.
  • 60% uplift in colleague engagement from AI-written internal comms.
  • About 50p a night to run the personalisation model for up to 3 million people.
  • 16 weeks from start to production for hyper-personalisation, with a four-week proof of concept.

All figures as stated on stage by Poppie Foakes and Tim Walpole.

Why did the Retail Trust turn to AI?

To reach millions of retail workers without adding staff. As a crisis phone line, it never reached 98% of people. It wanted to offer everyday wellbeing support to the 3 million people in retail, from sleep to anxiety, while still helping the 2% in crisis. A 60-person charity could not hire its way there.

How does the Retail Trust’s AI personalisation work?

It builds a model of each person rather than each segment. Every interaction is weighted and time-decayed to judge someone’s wellbeing state. That is combined with demographics and answers to about 10 core questions in a 1024-dimension vector. A two-tower model then matches the person to content, with Netflix-style social proof.

This is a unique set of data just for you with recommendations just for you. I call it the Netflix of wellbeing.

Tim Walpole, Head of Data & Creative Technology, Retail Trust

How did a small charity build it so fast?

By putting its data in one place first and proving each stage in weeks. A Databricks lakehouse came first, in 2022 and 2023. Agentic comms took a two-week proof of concept and eight weeks to production. Hyper-personalisation took four weeks to prove and 16 to ship, with a tech team of five or six.

How does it protect privacy and trust?

The platform is an optional benefit that retailers provide, and it takes in no personally identifiable information. Every piece of content written for retailers goes through a human in the loop. Responsible AI policies are sponsored from board level down, and Walpole says AI is not yet trustworthy enough for full prediction.

People trust Retail Trust, and as soon as we lose that trust, then we’re lost.

Tim Walpole, Head of Data & Creative Technology, Retail Trust

Key takeaways

  • Get the data in one place first. Every later AI stage built on it.
  • Prove value in weeks. Each stage started with a short proof of concept.
  • Model the person, not the segment. Two people with the same role and age need different support.
  • Test with synthetic users. About 10,000 go through the model at every build.

About the speakers

Retail Trust logo

Poppie Foakes is Director of Product and Innovation at the Retail Trust, the charity for people who work in retail. Tim Walpole is its Head of Data & Creative Technology. They spoke on the Customer track at aiblLIVE London on 20 October 2026.

What’s in the full case study

If you want to personalise support or content at scale on a small budget, this is the model to borrow. The full PDF goes deeper than this page, in the speakers’ own words.

  • The three-stage build, from lakehouse to agentic comms to a model for every person.
  • How the recommendation model works, step by step, from signal weights to the two-tower match.
  • How it was funded, including partners, apprentices and a build cost of about a quarter of a million.
  • Five actions to take back to your own organisation.

For HR and wellbeing leaders, data and product leads, and charity leaders with big audiences and small teams. Six pages, about a nine-minute read.

Personalise support at scale

AI personalisation at the Retail Trust: the Netflix of wellbeing
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