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Anthropic answer intelligence

Understand how Claude synthesizes your brand evidence.

Measure recommendations, source-backed claims and long-form comparison context across prompts where detailed reasoning matters.

Claude logo
Engine characteristic Long-form synthesis
Evidence layer Primary documentation
Measurement lens Claim consistency
Measured 2026-09-07

How Claude actually answers buying questions

From our own benchmark: 240 answers this engine produced for brand-free buyer questions across 12 categories, alongside the other engines on the same questions.

Answers analysed240across 12 categories
Answers naming at least one provider48%the rest gave guidance or pointed to a directory
Providers named per answer2.41fewer than the 2.70 average across all engines measured
Answers carrying citations85%engine average 96%
Citations per answer5.77counted only from markers inside the answer text
Answers ordered as a ranked list25%a ranked list is harder to enter than an unordered one
Answers pointing to a directory or review site16%where this is high, a directory listing is a precondition
Model queriedanthropic/claude-haiku-4-5disclosed so the figures can be reproduced
By category

Where Claude names brands, and where it stays generic

Sorted by how many providers this engine names per answer. Categories at the bottom are open ground: the engine currently answers them without naming anyone.

Category Answers Name ≥1 provider Providers / answer Most-named by this engine
Project management software 20 65% 3.35 monday.com
Furniture brands 20 55% 3.20 IKEA
Restaurants 20 45% 3.20 Bounty Kitchen
Skincare brands 20 45% 2.80 La Roche-Posay
Law firms 20 55% 2.35 Regas & Dallas P.C
Gyms & fitness studios 20 45% 2.30 Planet Fitness
Pet supplies 20 50% 2.30 PetSafe
Dentists 20 40% 2.25 Austin Dental Spa
Hotels 20 35% 2.00 Faena Hotel Miami Beach
HVAC & plumbing services 20 45% 1.90 Lennox
Electric bikes 20 50% 1.75 Aventon
Real estate agents 20 40% 1.55 Compass
Sources

What Claude cites

The domains this engine cited most across the benchmark. Engines differ here more than they differ on which brands they name, which is why source work has to be planned per engine.

DomainType CitationsCategories
reddit.comCommunities (Reddit, Quora…)349
alibaba.comOther sites153
rickjanson.comNamed providers' own sites91
nytimes.comNews & media63
forbes.comNews & media63
ebikeoracle.comNamed providers' own sites61
povison.comNamed providers' own sites61
dermapproved.comOther sites61
linkedin.comOther sites53
wrike.comNamed providers' own sites51
Crawler access

Letting Claude read your site

Anthropic separates content gathering from user-triggered fetches in the same way. Both are named agents, so both can be allowed or blocked deliberately.

ClaudeBot · Claude-User

Test your site against these agents · Read the crawler access guide

Anthropic documents server-side web search as a tool available in supported Claude API workflows.

Anthropic tool use ↗
Engine-specific lens

What to inspect in Claude.

Keep a shared core framework, then add the engine-specific evidence needed to explain differences.

01
Long-form synthesisRecord whether search or grounding influenced the answer.
02
Primary documentationConnect visible claims to exact source pages and domains.
03
Claim consistencyCompare the same question across measurement windows and competitors.
Optimization loop

A repeatable Claude visibility workflow.

The goal is evidence-led improvement, not guaranteed placement.

01 Select synthesis prompts Start with stable commercial and category questions.
02 Map claim evidence Preserve answer mode and source context.
03 Repair ambiguity Improve facts, structure and third-party support.
04 Review answer depth Run the same measurement set and compare changes.
FAQ

Questions about GEO for Claude

Can Claude use web search?

Claude supports server-side web search in supported product and API experiences. Availability and citation behavior can vary by configuration.

What evidence works well for long-form synthesis?

Clear methodology, stable primary documents, precise definitions and internally consistent product facts make synthesis easier to verify.

Should Claude be measured with the same prompts as ChatGPT?

Keep a shared core prompt set for comparison, then add engine-specific prompts for tasks where long-form analysis or document synthesis matters.

How often should Claude be re-measured?

Often enough to separate a real change from sampling variance. A single run is a baseline, not a trend.

Why does Claude name a competitor instead of us?

Usually because the evidence it can read about them is clearer or more corroborated. That gap is what the knowledge base and content work are for.

Do results from Claude transfer to other engines?

Partly. The underlying evidence is shared, but retrieval behaviour and citation formats differ, so each engine is still measured on its own.

From signal to action

Build a measurable Claude visibility program.

Create a project, confirm your market and start measuring the questions that matter.