Find It, Fix It, Prove It: A 3-Step SEO and AI Visibility Method
Short answer
Find It, Fix It, Prove It's Tarun Gehani's three-step method for SEO and AI visibility work: find where a brand shows up, where it doesn't and why; fix the gaps that matter most; then prove the change by re-measuring the same questions on the same engines, before and after.
Find It, Fix It, Prove It explained
Most SEO and AI visibility work breaks down at one of three points: the diagnosis is vague, the fixes never ship, or nobody can show what changed. Find It, Fix It, Prove It puts a step at each of those points.
Find It
Measure where the brand shows up, where it doesn't, and why. That covers search rankings and AI answers, technical access for search and AI crawlers, content structure, and the brand's public record: reviews, forum threads, third-party mentions and the recurring themes in AI answers about it. The output is a baseline and a ranked list of gaps (AI visibility audit).
Fix It
Decide the moves and document them so someone can carry them out. The client's team or a partner makes the changes, sequenced so blockers like crawl access and indexing come before content, and content comes before off-site work like citation outreach. Fix It also covers publishing proof that's buried today, like customer results or original data, in a form AI systems can cite.
Prove It
Re-run the same questions on the same engines and compare before and after. AI answers vary between runs, so visibility is reported as rates across repeated runs, with dates and ranges, instead of single screenshots. Reports separate what moved from what can be credited to the work, and pipeline claims are made only where tracking exists, such as AI referral traffic or a "how did you hear about us" field. Then priorities reset for the next cycle.
Why the third step matters
Marketing leads have to justify SEO and AI spend to leadership, and traffic alone now undercounts the effect of visibility work. Pew Research found people clicked a traditional result on about 8% of Google searches that showed an AI summary, against 15% when there was none. Prove It reports evidence a marketing lead can defend: AI visibility rates, search visibility, branded search demand and, where tracking allows, pipeline.
In practice
Each step answers a question every engagement has to answer: where are we, what do we change, and did it work. The last one can't be bolted on afterward. Without a baseline taken before the work starts, there's nothing to compare against, so in my engagements the prompt set, the engines and the measurement schedule get locked before any fixes ship.
Common misconception
"Prove It" can sound like a promise of guaranteed results. It means evidence a client can defend: the same measurements before and after, with a clear line between what moved and what can be credited to the work.
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