Fundamentals
Contextual AI Presence Mapping (CAPM) is Aethon's method: map the moments that create demand in your category, measure which brands AI recommends in each one, then ship the work that earns you the mention.
Why it exists
Someone gets engaged, gets rear-ended, or watches traffic drop. They tell ChatGPT, Claude, Gemini or Perplexity what happened. Assistants infer a need and name brands. CAPM is the method for owning those moments instead of only chasing the keywords that show up later.
GEO and AEO still matter for prompts and answers. Keyword SEO still matters for crawlable pages. CAPM starts one step earlier: which moments create demand, who owns the recommendation today, and what to publish so the shortlist changes.
The CAPM loop
Each stage has a clear output. Aethon runs this loop in the product.
Stage 1
List the life and business situations buyers in your category describe to assistants, written the way a person would say them out loud.
You collect moments from sales calls, support tickets, reviews and industry boards. Each moment is a situation, not a keyword.
A moment library for your category, with the needs those situations create and the brand types assistants often name.
Stage 2
Run those moments across ChatGPT, Claude, Gemini and Perplexity on a schedule. Record who gets named, and who is missing.
Each tracked moment is asked the way a buyer would ask it. Answers are logged by assistant over time.
A clear view of presence and gaps by moment and by assistant, before you change anything.
Stage 3
When another brand owns the mention, CAPM looks at the context assistants trust for that situation.
You review entity clarity, structured data, citations and coverage on the sources assistants lean on for that moment.
A plain-language reason the shortlist looks the way it does, tied to work you can actually ship.
Stage 4
Turn gaps into briefs for content, schema, citations and coverage. Keep SEO, GEO and AEO for the layers they already cover.
Fixes are ranked by the moments that matter most in your category, then handed to marketing and content teams.
An action board of briefs you can publish, plus a baseline so you can see whether the recommendation changed.
Worked example
A clearly fictional brand, so you can see the method without treating the outcomes as a customer case.
A multi-location dental group wants assistants to name it when someone describes urgent tooth pain while traveling.
"My crown just cracked on vacation and I am in a lot of pain. Who can see me today?"
Northline adds this to its healthcare moment library under urgent restorative care, with related moments for weekend fever-of-the-mouth and lost fillings.
Across ChatGPT, Claude, Gemini and Perplexity, assistants often name national urgent-care dental brands and local ER options. Northline is rarely in the shortlist for out-of-town travelers.
Trusted sources for this moment emphasize same-day hours, location clarity and plain-language pages about cracked crowns. Northline's site buries hours and has thin entity markup for each clinic.
Ship a cracked-crown guide, clinic-level schema, same-day hours on every location page, and citations on directories assistants already use. Keep SEO for "emergency dentist" keywords and GEO for related prompts.
How the layers fit
Complementary layers. You do not rip out what already works.
| Layer | Starts from | Primary question | Typical output |
|---|---|---|---|
| Keyword SEO | Queries people type | Can we rank for this keyword? | Pages, links and technical crawl health |
| GEO and AEO | Prompts and answers | Do we show up in AI answers for known prompts? | Prompt tracking, answer visibility and content shaped for assistants |
| CAPM | Life and business moments | Which situations create demand, and who gets named inside them? | Moment maps, presence by assistant, diagnosis and ranked fixes |
Read how Aethon works alongside GEO tools and what moment intelligence is.
In the product
The same views from the homepage, shown whole so you can read the UI.




Observed: Aethon records assistant answers for a moment across runs and measures whether they name your brand. Modeled: estimated monthly conversation volume, your value per lead, and category conversion assumptions produce a directional revenue estimate. Dollar figures are modeled estimates, not booked revenue. You can replace the starting inputs with your own numbers. Aethon does not read your billing or CRM system.
Key takeaways
Demand often starts as a story told to an assistant. CAPM maps that story.
Presence without action is a scorecard. CAPM ends in ranked fixes.
SEO, GEO and AEO stay. CAPM is the moment layer beside them.
FAQ
Contextual AI Presence Mapping. It is Aethon's method for the moment layer under GEO and AEO.
Keyword SEO targets what people type into a search box. CAPM starts earlier, with the situations people describe to AI assistants before a clean keyword exists.
GEO and AEO improve how you show up for prompts and answers. CAPM maps the moments that create those prompts, measures who assistants recommend inside them, and ranks what to publish next.
No. Keep SEO, GEO and AEO for crawlable pages and prompt visibility. CAPM adds the moment layer and works alongside them.
A life or business change that creates need before a product-style search. People describe these to assistants in everyday language.
Read the Life Moments Report, run the free AI Visibility Checker for a baseline, then book a demo to see your category's moment map.
Book a 30-minute demo, or start with the free checker.