WAwellness & ai
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Workbook

AI Recommendation Engine Playbook

Build a learning content engine that knows what your audience needs before they do.

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Step-by-step workbook for building a personalised recommendation system using AI signals, dismissal-based learning, affinity scoring, and anonymous-to-authenticated profile bridging. Includes the exact architecture we use on this site — browse signals, domain affinity heatmaps, daily analytics, and the dismiss-to-learn feedback loop. Covers both individual wellness platforms and practitioner portals.

Who it's for

For practitioners scaling 1:1 work without scaling burnout.

Best for

  • You run a coaching, nutrition, functional-medicine or longevity practice.
  • You want to use AI as a delivery layer — not replace your clinical judgement.
  • You're done re-explaining the same protocol in every consult.

Not the right fit if

  • You want a fully managed software product — this is a build-it-yourself system.
  • You're not ready to put your method in writing.

Audience: Practitioners · Domain: other

Inside · paste-ready blocks

AIrecommendation enginepersonalisationcontent strategyaffinity scoringpractitioner tools

This playbook walks you through the exact recommendation engine architecture behind Wellness & AI — from anonymous browse signals to logged-in enrichment, domain affinity scoring, dismissal-based negative learning, and daily analytics reports. You will build a system that gets smarter with every visitor interaction.

🔒 The step-by-step guide unlocks after purchase.

Before you buy.

It's built for practitioners — coaches, nutritionists, integrative clinicians — who want to give clients a private AI workflow without recommending another consumer app.

Find the next layer of your stack.

One tool down. The whole system is here.

Resources hit harder when they sit on top of the method, the proof, and the right toolset.