Recommend personalised products and content

Shops, streaming services and news sites recommend personalised products and content to users

Needs setupAI Act: no extra obligationsRecommending & personalisingRetail & consumer goods, Film, music & audio, Journalism & publishing

Fits: Sales · Marketing & communications

Customers, listeners and readers are more likely to see what really interests them: matching accessories, the next episode, background on the article they have just read. You sell more or keep users longer, without everyone seeing the same home page.

Is this for you?

  • You have a large range that is hard to find your way around, and data on purchases, views or reading time.
  • You can obtain and manage consent for personalised offers properly.
  • You have people who set goals and review recommendations over months, not just set them up once.
First step today

Write down 15 items, titles or articles from your range with their category and invent three test users with a short history. Use the template below to have recommendations created with reasons, and check whether they just repeat the same thing, sound intrusive or also show something new.

How to go about it

  1. Define what a good recommendation is
  2. Combine purchase, viewing and catalogue data
  3. Set up the recommendation function with fixed rules
  4. Test with some users against the existing selection
  5. Switch on for everyone who has given consent
  6. Check the diversity and usefulness of recommendations

Templates to copy

Try it now
in the training
Analyse
in the training
Plan the rollout
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Included in the training

The complete guide

  • 6 steps explaining exactly what to do
  • 3 proven templates to copy into your own AI
  • Safe use: data, checking, deciding, informing
  • Pitfalls, effort and how to recognise success

With the training you get all 430 guides for as long as your access runs.

See the trainingOne-off per person, no subscription

Same approach, other use cases

13 more use cases follow the pattern “Recommending & personalising”.

Adapt members’ training plans with AIDraft meal plans from preferences and goalsAdapt the difficulty level to how people playAdjust resistance and programme on the machine automaticallyAnalyse skin photos and recommend care productsHave AI find similar products from a customer photoImprove shop search for typos and paraphrasesInvest customer money automatically by risk profilePut together complete outfits from your rangeRecommend suitable tariffs based on consumptionRecommend the right size to customersSuggest training that matches skills gaps
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G-HK-03 · Legal status 08.10.2026