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Topickz Research

AI Recommendation Scorecard: Is Your Brand AI-Search Ready?

A free interactive scorecard that grades your B2B SaaS brand on how likely AI engines (ChatGPT, Claude, Gemini, Google AI Overviews, Perplexity) are to recommend it. 22 checks across five pillars, scored out of 100, with your highest-leverage fixes.

Vignesh Sampath Kumar Last updated June 27, 2026 4 min read

Your buyers are asking ChatGPT and Perplexity for a shortlist before they ever reach your site. This free scorecard grades how likely those engines are to put your brand on that list, and shows you exactly what to fix first.

Score yourself on 22 checks across five pillars. You get a number out of 100, a grade, a per-pillar breakdown, and your three highest-leverage fixes. It runs in your browser, takes about three minutes, and asks for nothing.

1. Foundation be findable and verifiable

Your G2 and Capterra profiles are claimed, complete and kept current

You are listed in independent "best of" editorial lists in your category

You use one consistent name and one-line positioning everywhere

You have a clear entity footprint (Knowledge Panel, consistent profiles)

Organization and Product schema markup is on your site

2. Content be citable

You publish original data (3+ unique points: a survey, benchmark or internal test)

Key buyer questions are answered in self-contained 2 to 4 sentence passages

Important pages are refreshed within 90 days and show a visible date

You publish transparent details instead of hiding everything behind "contact sales"

Every claim is backed by a number or a source

3. Consensus be talked about

You earn mentions in the real communities and subreddits for your category

You get covered by YouTube reviewers and established publications

Third-party comparison and review content about you exists

You have topical authority: a cluster of pages on one subject

4. Per-engine tuning cover each model's tell

ChatGPT: community consensus plus clean comparison pages

Claude: verifiable, documented claims

Gemini: Google E-E-A-T, entity clarity and schema

AI Overviews: original data, freshness and extractable structure

Perplexity: fresh, dated pages that answer the query directly

5. Measure and iterate close the loop

You prompt each AI engine monthly and record who it recommends

You track referral traffic and citations from AI engines

You re-check visibility after every content refresh

How the score works

The scorecard is built on one finding: AI engines recommend the brands that show up, consistently, across the third-party sources they already trust. They look for consensus, and they look for evidence. Marketing you control barely moves the needle.

Each pillar maps to a different part of that picture. Foundation is whether the engines can find and verify you at all. Content is whether your pages are citable. Consensus is whether independent sources agree on you. Per-engine tuning covers the specific tell of each model. Measurement is the loop that keeps you visible as the engines change.

The pillars are not weighted equally. Content and consensus carry the most points, because original data and third-party agreement are what actually get a brand cited. A page with at least 3 original data points is about 4x more likely to be cited in AI answers, per 2026 industry analyses, and 61% of B2B SaaS tools sit inside a single 0.3-star rating band in our own analysis of 816 tools, so your own numbers rarely separate you.

What to do with your result

A low score is not a verdict, it is a worklist. The tool surfaces your three biggest gaps by point value, so you start where the return is highest instead of guessing.

Most brands find the same pattern: foundation is half-done, content is thin on original data, and nobody is measuring anything. Fix those three and the rest compounds.

When you are ready to work the full list with your team, the complete playbook walks through every check, engine by engine, with the reasoning behind each one.

Read the full AI recommendation playbook →

Questions buyers ask

Is this tool actually free? Yes. No signup, no email, nothing stored. It runs entirely in your browser and the result disappears when you close the tab.

Where do the checks come from? They are the 22 actions in the Topickz AI recommendation framework, the same one behind our full playbook . The framework is grounded in how ChatGPT, Claude, Gemini, Google AI Overviews and Perplexity each source what they recommend.

Does a perfect score guarantee recommendations? No tool can promise that, and any that does is lying. A high score means you are showing the signals these engines reward. The engines still decide.

Can I share or embed the scorecard? Yes, link to this page freely. A free, useful tool is exactly the kind of thing that earns links, which is also one of the signals it measures.

Sources and original data

Original Topickz data. The rating figure (61% of tools rated 4.3 to 4.6) comes from Topickz’s analysis of 816 B2B SaaS tool entries, May to June 2026. See the B2B SaaS Buyer-Behavior Report .

Third-party figures, attributed. The citation statistic (3+ data points about 4x more likely cited) is drawn from 2026 industry analyses of AI Overview and generative-engine citations, not generated by Topickz.

For our independence and corrections policy, see our editorial standards .

Written by

Vignesh Sampath Kumar

Topickz Editorial Team · Review methodology