By Tangenix · Published 2026-10-23 · Free template

AI Search Visibility Benchmark Template

Record repeatable AI-search observations for your software brand, with query context, actual citations and a baseline that avoids ranking promises.

When to use this template

Use this before changing your content so you can distinguish an observed answer from a claim that your brand always appears. Choose questions relevant to a real customer decision.

Choose another approach when: You intend to treat one personalized answer as a market-wide ranking, feed private customer details into public tools, or invent an appearance rate without a defined sample.

Gather these inputs

A small fixed set of relevant brand and task questions.
The search-enabled product, account context and observation date.
Public evidence links and a place to preserve the answer context.

Copy and adapt the template

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AI Search Visibility Benchmark Template: editable text

Worked example

Illustrative example, not a Crany customer result. Replace every example detail with facts you can verify.

A fictional founder tests “How can an independent designer organize a client handoff?” in a search-enabled AI product. The saved answer lists several approaches and does not mention the founder’s app. A separate branded question cites the app’s public overview but incorrectly calls its waitlist a free plan.
The benchmark records two different outcomes: no task-query presence and an inaccurate branded answer. It does not report “50% market share.” The founder can now investigate the inaccurate source and repeat the same questions after publishing a clearer access explanation.

How to use it

Choose questions before looking at answers to avoid selecting only favorable examples.
Record the actual linked URLs and conditions in the response, not just a brand-name match.
Repeat the same observation protocol and label changes as sample results.

Check before using it

The engine actually used web search for the recorded observation.
Personalization and sampling limits are recorded.
A citation, a mention and an endorsement are counted separately.

What to measure

Compare dated observations for the same question set, alongside real referral and product outcomes. An answer can vary without a site change, so this benchmark is a diagnostic record rather than a causal ranking experiment.

Research and sources

The sources describe search-based AI experiences and reliable content. The sampling log and observation categories are original measurement choices; neither source endorses a visibility score or guarantees inclusion.

Google: AI features and your website — checked 2026-10-23. Search eligibility, visible content, AI feature reporting and the absence of special AI markup requirements.
Google: Creating helpful, reliable, people-first content — checked 2026-10-23. Original value, useful answers, transparent sourcing and a clear audience.

This original template and worked example were prepared with AI assistance. Source documentation supports the principles stated above; it does not endorse Crany or guarantee this template’s performance.

About Crany

Crany is an AI marketing co-founder in development for software founders and vibe coders, designed to strategize, execute approved marketing and improve based on results. This free resource is usable independently of the product. Join the public waitlist.