The MAPS Method
The complete methodology for diagnosing and improving a brand. It combines the framework, the execution work and the disciplines that keep the work reliable.
The MAPS Method is a practical way to diagnose and improve how a brand works: in a buyer's head, in the market, and inside the search engines, AI answers and agents that now sit between them. At its core is the MAPS Framework: Meaning, Authority, Presence and Signals. The framework explains what needs to be true. The method adds the work required to make it real.
The complete methodology for diagnosing and improving a brand. It combines the framework, the execution work and the disciplines that keep the work reliable.
Meaning, Authority, Presence and Signals describe the four conditions a brand needs to meet to become understood, trusted, found and usable.
Explore the framework →Four workstreams turn the framework into action: define what the brand should mean, prove it, distribute the proof and enable people and machines to use it.
See the method →If one of these is weak, everything downstream gets fragile. You cannot schema your way out of unclear positioning, you cannot buy reach around a product nobody recommends, and you cannot PR your way around evidence nobody can find. The useful part is seeing how the pieces connect, so the next move is based on the constraint rather than the latest acronym.
Define who the brand is for, what need it meets and what it should be known for, so a buyer, a colleague and a machine resolve it the same way.
Explore Meaning →Build the proof that makes a claim credible and the experience that makes a customer recommend you.
Explore Authority →Put the brand and its proof wherever the audience already looks, including where machines look on their behalf.
Explore Presence →Make facts, offers and assets ready for every person on the team and every machine on every surface.
Explore Signals →The conditions do not change with the reader. What changes is the evidence you look at to know whether each one holds: for the people you serve, the markets you compete in and the machines that now answer on your behalf.
Buyers, users, advocates and your own team. The map suggests; the driver decides.
Every route a buyer can take to you: search, feeds, shelves, screens, word of mouth. Where you are, and how often.
Search engines, AI answers, agents and assistants that narrow the options before a person ever sees them.
Shortlisted by machines. Chosen by people. Trusted on the road.
| Condition | For people | For markets | For machines |
|---|---|---|---|
| Meaningunderstood | The right audience recognizes itself and the need you solve. No confusion about what you are. | Category and position are clear against the alternatives. | Entity, category, audience and relationships resolve without guessing. |
| Authoritytrusted | Customers get the outcome, are satisfied and recommend you. | Independent proof outweighs self-description. | Claims are corroborated by sources a system weighs. |
| Presencefound | You appear where your audience already is, with the proof they are looking for. | Share of attention across paid, earned, shared and owned channels. | Retrievable across queries, fan-outs and source ecosystems. |
| Signalsusable | Messages are consistent and expressible by anyone on the team, on any surface. | Assets, data and offers are ready for every channel's format. | Crawlable, structured, extractable, verifiable and actionable, including by agents. |
The same four conditions, checked for three readers. Most teams work the third column and call it AI visibility. MAPS asks for all three.
The framework describes the conditions. The method organizes the work required to create and improve them. Start with the constraint, not the shiny tactic. It saves time, and usually a few unnecessary blog posts and a media buy.
Establish the entity, category, ICPs and needs, message architecture, journeys, markets, target prompts and key relationships.
Support claims with expertise, outcomes, research, trial, customer satisfaction and independent corroboration.
Place the proof across every channel the audience uses: search, AI answers, paid, earned, shared, owned, reviews, partners, shelves and screens.
Make the proof accessible, structured, extractable, verifiable and actionable by machines on every surface, and findable by every person on the team.
A buyer forms a view of the brand before a sales call. A market rewards the brand it can place. An AI answer evaluates the brand before a click: it starts with learned associations, fans out into related searches, chooses a subset of sources, extracts passages, compares claims and decides what to mention or cite.
The same four conditions decide all three outcomes, which is why the framework does not change when the channel does.
Citations, impressions and share of voice are visible. The conditions that produce them are upstream.
MAPS works on those upstream conditions rather than treating the citation, the click or the sale as the whole strategy. Citations are evidence of an outcome, not a strategy in themselves.
Otherwise this would be a slightly awkward framework website.
Each pillar has a canonical page, consistent terminology, structured data and declared relationships.
The site publishes an XML sitemap, HTML sitemap, Schema.org graph, llms.txt and EntityMap v1.0 files at predictable URLs.
The framework visuals, audit, worksheets and the message architecture behind this site are available to download and use with attribution.
I use the framework to diagnose brand clarity, proof, channel presence and the technical conditions that help people and systems find and use the right evidence.