HIGH SALIENCE / WORK / EXAMPLE ANALYSIS
EXAMPLE ANALYSIS · NOT CLIENT RESULTS. AN ILLUSTRATIVE TEARDOWN OF THE PROCESS.
Example Analysis / B2B Software
How we'd attack a B2B software category owned by two incumbents.
A worked example of the High Salience process on a typical challenger scenario: the map we build, what it exposes and the intervention order we'd choose. No client is behind this page, and it claims no results. It shows you exactly what the work looks like.
01The Scenario
A challenger brand with enough existing authority to compete for category leadership, but two incumbents control the third-party sources and commercial query clusters feeding both conventional and AI search. The gap is structural, not creative: the market's questions are being answered on ground the challenger doesn't hold.
02The Map
What the intelligence phase produces.
We'd build the commercial query universe for the category (typically several hundred queries across category, comparison, alternative and recommendation intent), then measure every brand's presence across Google and the major AI surfaces. The map is designed to expose four kinds of gap:
- Coverage gap: the challenger appears in a minority of the commercial query universe while the leading incumbent appears in most of it.
- Recommendation gap: on recommendation-intent queries in ChatGPT and Gemini, the challenger is rarely named at all.
- Source gap: a small set of third-party sources accounts for the majority of AI citations in the category, and the challenger has accurate presence in almost none of them.
- Retrieval gap: the pages targeting the right demand are structured so that no passage can be cleanly retrieved or quoted by an answer engine.
03The Intervention Order
Three fronts, in order of leverage.
Rebuild the retrieval layer
Category and comparison pages rebuilt around the commercial query clusters: explicit claims, evidenced comparisons, self-contained passages that answer engines can extract.
Penetrate the source layer
Source opportunities ranked by citation frequency and attainability. Campaigns land accurate brand presence in the review, comparison and industry sources the AI surfaces keep citing.
Consolidate the entity
Entity signals, corroborating coverage and internal architecture aligned so machines resolve the brand, its category and its differentiators consistently.
04How It Gets Measured
The map is the KPI.
Progress is measured against the original query universe, not vanity metrics: coverage share, recommendation frequency on money queries, accurate presence in the cited sources and the branded-search and pipeline movement that follows. The map is remeasured quarterly, and the plan changes when the evidence does.
When real engagements produce documented numbers, they'll be published here as case files, with the method behind every figure. Until then, this page stays labeled what it is: an example.