Industries
AI for Retail and E-commerce
Retail feels the AI shift on both sides of the business. Inside, it changes forecasting, pricing and personalisation. Outside, it changes how customers find products at all.
The position
That second shift is the one most retailers are unprepared for. When a shopper asks an AI assistant what to buy, the assistant answers from what it can retrieve and trust - and a catalogue built entirely for search engine crawlers is not necessarily legible to it.
We help retailers govern the personalisation and pricing systems they already run, and make their catalogue and brand retrievable by the engines customers now ask.
What is pressing
Four pressures specific to this sector.
01
Discovery is moving
A growing share of product research starts in an AI assistant rather than a search box. Being absent from those answers is a distribution problem, not a marketing one.
02
Pricing and personalisation fairness
Dynamic pricing and personalisation create outcomes that differ between customers. Those differences need a defensible basis, and a boundary nobody crosses.
03
Demand forecasting under volatility
Forecasting models trained on stable demand fail in exactly the conditions that make them valuable. Knowing when a model should be overridden is part of the system.
04
Customer data across channels
Personalisation depends on joining data across channels, which is where consent obligations are most often quietly broken.
Where the divisions apply
Which divisions this sector uses, and in what order.
Listed most relevant first. Most organizations in this sector enter through the first and draw on the others later.
04
AI Visibility
Increase the chance ChatGPT, Gemini and Claude recommend your business.
Read the division01
AI Strategy
Know where AI creates value in your organization before you spend on it.
Read the division02
AI Governance
Build your AI governance framework before regulation forces you to.
Read the division03
AI Audit
Prove the AI you already run does what you say it does.
Read the divisionQuestions
What this sector asks first.
- How do we know whether AI assistants recommend our products?
- Ask them, systematically and repeatedly, and record what comes back. That is what our free AI visibility report does: it checks whether the major engines mention a brand, how they describe it, and what they cite when they do.
- Is optimising for AI answers different from SEO?
- It overlaps but is not the same. Search rewards ranking; AI answers reward being retrievable, unambiguous and corroborated across sources the model trusts. A page can rank well and still never be cited.
- What governance does personalisation actually need?
- A stated basis for how customers are segmented, limits on the attributes that may drive differences, monitoring for outcomes that would embarrass you if published, and a route for a customer to ask why they saw what they saw.