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Research · buyer-intent SERPs

Who wins the moment buyers compare you?

We analysed 1,001 high-buy-intent searches — "brand vs rival", "brand alternatives", pricing, reviews, free trial — across 119 B2B software brands, and looked at who owns the top-ranked page and what that page is made of. The pattern is stark: businesses own the searches about buying from them, and have surrendered the searches about choosing them over someone else.

Who owns the #1–2 result, by search intent

Buyer searches…QueriesBrand's own page winsSomeone else wins
"brand pricing"11881%19%
"brand free trial"11881%19%
"brand cost"11881%19%
"brand discount"11864%36%
"brand vs rival"29233%67%
"brand review"11825%75%
"brand alternatives"11816%84%

Two-thirds of "you vs rival" searches — and five of six "your alternatives" searches — are answered by a page you didn't write. Often it's the rival's comparison page, an affiliate listicle, or a review aggregator. That page is what a buyer reads at the exact moment they're deciding between you and someone else.

Why this matters for AI visibility: when someone asks ChatGPT or Perplexity "should I use X or Y?", the assistant's search layer runs exactly these queries — our scans log the searches engines fire while answering, and comparison queries are all over them. The page that wins this SERP is the raw material for AI's answer about you. Surrender the SERP and you've surrendered the answer.

What the winning pages are actually made of

Feature prevalence across the 941 top-ranked pages we could fully crawl — some of it cuts against popular advice:

FeatureShare of winnersRead
Title contains the intent word (pricing/vs/alternatives…)71%table stakes
Call-to-action above the fold79%winners sell
Author byline77%common…
Author bio2%…but the "add author bios" advice? Winners skip it
FAQ schema11%not the ranking prerequisite it's sold as
Visible "updated" date26%intent-specific (see below)
Exact-match H110%near-match beats keyword-stuffing
Links out to authoritative sources~1% of pages' linkstransactional SERPs don't require it
Backlinks to the winning pagemedian 21page shape beats raw authority here

Position 1 vs position 2 is where authority shows: the median #1 page has 82 backlinks to the runner-up's 6. But a median of 82 is not a moat — it means the podium is reachable with the right page and a modest citation push.

Each intent has a winning shape

IntentThe shape that wins
"vs" (n=274)head-to-head comparison; 74% use a superlative ("best", "top"), H1 close to the query, honest both-ways structure. FAQ schema on just 7%.
"alternatives" (n=109)the numbered listicle: 79% have a number in the title, 50% a year, 47% a visible updated date, 93% a byline. The most third-party-owned intent (84%).
"pricing" (n=115)the brand's own plans page: 91% CTA above the fold, 35% an FAQ block, zero years-in-title, zero listicle theatrics.

What to do with this

Own your comparison moments before a rival or an affiliate does: publish an honest page for every "you vs rival" AI names against you, and your own "alternatives to you" page. The step-by-step anatomy, drawn from these winners, is in the comparison-page playbook. Your free scan shows which rivals AI actually names against you — that's your page list.

Which rivals is AI naming instead of you?

The free scan asks the engines your buyers' questions and names names. ~60 seconds.

Run the free scan →

Method & provenance: source dataset assembled by Distribb — 1,001 buyer-intent queries with the #1–2 ranked page and on-page features captured late 2025; independent analysis by Are you found by AI? (full recompute from the raw rows, July 2026). 941 of 1,001 pages fully crawled; feature stats use those 941. Sample skews B2B SaaS (119 brands, 347 winning domains). These are Google SERPs, not AI answers — we treat them as the retrieval layer AI reads, which is measured, not assumed, via the engine-run searches our scans log. Prevalence is correlation, not causation.

Method. Found by AI asks ChatGPT, Claude, Perplexity and Google's AI the questions real buyers ask for each category, then measures which businesses the engines actually name. Scores are 0–100 point-in-time measurements; the index re-scans and grows automatically. Businesses listed here were selected and measured by us from public directories — scan your own site free to see where you'd rank. Queries and methodology are open: github.com/techhorizonlabs.