The seven-stage customer journey: where AI search helps and what comes next

Awareness and interest: earn understanding

At awareness, the buyer asks what the problem is and whether it applies to their business. A clear explanation should connect unfamiliar terminology to a recognisable task. At interest, the question becomes how the work would apply in practice. A walkthrough, diagnostic checklist or labelled example can help. Measure relevant discovery and use of supporting pages where data is available, rather than judging everything by total traffic.

Consideration and intent: reduce decision risk

At consideration, the buyer compares options and credibility. Explain the method, evidence standards, limits and division of responsibilities. At intent, clarify scope inputs, cost drivers and the next conversation. Do not invent prices or a result timeline. A good service page says what is investigated, what requires separate agreement and which owner supplies factual approval. The practical CTA is a scoped enquiry, not an unexplained “start” button.

Conversion: make the real action work

The visitor needs a short, accessible path to send a relevant request. Label fields, provide privacy information, validate errors and return a clear receipt. A click on contact is not a completed enquiry. Do not require unrelated marketing consent to request a service. If a booking or payment capability is unavailable, use the actual working contact route rather than pretending it exists.

Retention: make progress inspectable

After engagement, the client asks what changed, what remains and what should happen next. A change register, accepted deliverables and a review method support that conversation. Search and AI observations belong beside business outcomes, with data gaps disclosed. Retention depends on useful delivery and communication; it is not an independent result of publishing AEO articles. Do not enrol a client into marketing messages without the appropriate permission.

Advocacy: give people a truthful reason to recommend

A clear handover, transparent limitations and reliable support can make a voluntary recommendation easier. Ask for an honest review only through a legitimate, appropriate process. Do not manufacture endorsements, filter requests only to happy customers or offer undisclosed rewards. Advocacy can introduce another buyer to the awareness stage, but a recommendation is not evidence of a universal AI ranking mechanism.

Worked local-service journey

In an illustrative Danish maintenance business, an owner learns why service conditions are misrepresented in AI answers. They read the access and evidence guides, compare the audit method and send the website plus approved scope for discussion. If an engagement follows, factual owners review changes and receive verification records. A later voluntary recommendation can start another buyer’s research. This is a proposed journey, not a recorded customer result.

Worked B2B consultancy journey

A fictional marketing manager first researches citation measurement, then checks the prompt protocol and sample report. Procurement asks who approves facts, which platforms are observed and how the deliverables are accepted. The manager requests a scoped conversation, reviews agreed work and uses the handover in a later supplier evaluation. Long consideration cycles can include several people and return visits; a single referral source rarely tells the whole story.

Keep the operating cycle separate

The customer journey describes the buyer. Discover, Diagnose, Decide, Plan, Produce/Implement, Verify/Measure and Improve describe the team’s work. Use that operating cycle to maintain the content supporting each stage. A seven-column planning table should not become seven nearly identical pages for every keyword.

Continue with the related decision

• AEO learning paths
• Prioritise AEO opportunities by evidence, relevance and delivery cost
• Discuss the scope of AEO and AI-search work