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A client case study with the Search Console export behind it, 59 to 349 clicks a day over 92 days

What the numbers are, what they are not, and the three disclosures that have to sit beside them

Published by AI Knows Us · Updated 22 October 2026

Most case studies in this category publish a percentage and no denominator. This one publishes the window, the export date, the daily figures month by month, and the three things that make the numbers smaller than they look. The client is clawlaw.in, a legal search company, and the commercial and ownership relationships are disclosed in full further down, because a case study that hides them is marketing dressed as evidence.

The figures, and the window they came from

Read from Google Search Console for clawlaw.in, window 13 July 2026 to 12 October 2026, which is 92 days with data. Exported 14 October 2026.

  • 18,537 clicks in the window
  • 929,405 impressions behind those clicks
  • 59 clicks a day at the start, 349 a day at the end, which is 5.9 times

Month by month, as daily averages rather than monthly totals, which is the distinction most case studies blur:

  • July 2026, 19 days of data: 59 clicks a day, 2,253 impressions a day
  • August 2026, 31 days: 154 clicks a day, 7,276 impressions a day
  • September 2026, 30 days: 282 clicks a day, 14,703 impressions a day
  • October 2026, 12 days: 349 clicks a day, 18,331 impressions a day

Those are daily averages. Reading them as monthly totals overstates the start of the window and understates the end, and the error runs in the flattering direction, which is why the unit is stated on every line.

The first disclosure. This domain had history

clawlaw.in had existing pages, existing links and existing crawl history before the window opened. These are growth figures on a working site, not a launch. Anybody reading them as what a new domain does in three months is reading them wrongly, and the difference is not small.

The implied click-through rate makes the point. 59 clicks against 2,253 impressions a day in July is about 2.6 per cent, which is a site already ranking in positions people click. A domain with no history does not start there, because click-through rate follows position and position follows everything a new domain does not yet have.

The second disclosure. The commercial and ownership relationship

clawlaw.in is a client of AI Knows Us. It is also a separate company founded by the same person who founded AI Knows Us. Both of those things are true at once and both belong on this page.

So this is not an independent third-party result. It is our own client, with a shared founder, and we are publishing it. That makes the export checkable and the selection biased: we chose which client to write about, and we chose the one that worked. Treat it as what it is.

This site argues continually that a vendor claim without a method, a denominator and a date should be discounted. Applying that standard to ourselves means naming the relationship rather than letting the figures imply an arm's length we do not have.

The third disclosure. What this case study does not show

  • It does not isolate a cause. Search Console records what happened on the domain over 92 days. It does not separate our work from the client's own publishing, from seasonality, or from anything else that moved in the same window. No page of ours will tell you those 18,537 clicks were caused by one thing, because the data cannot say so.
  • It is one domain. One case is a case, not a rate. We have no sample across clients and we are not going to imply one from a single export.
  • It is not a forecast. Nothing here predicts what another site would do, and a site without history would start from a different position in every sense of the word.
  • It is clicks, not revenue. We did not see the client's sales data and we are not going to describe clicks as business outcomes.

Why we publish the export date and the window at all

Because a reader can take those two facts and check them, and almost nothing in this category can be checked. In 635 readings of ChatGPT and Gemini on buying questions, measured 22 October 2026, 92.9 per cent of citations in the British set and 91.1 per cent in the Indian set went to a vendor's or an agency's own website. Review directories took 0.8 per cent and 0.7 per cent. The engines are reading vendor marketing because there is little else to read, and a case study with a window and an export date is one of the few things in the category that survives being checked.

What to require of anybody showing you a case study, including us

  • The window, with dates. Not "in three months" but which three months, and how many days actually carried data.
  • The export date, because Search Console figures move for about two days after the fact.
  • The unit. Clicks a day and clicks a month differ by a factor of thirty, and the ambiguity always favours the person showing you the chart.
  • The denominator. A percentage with no impressions behind it is unreadable.
  • Whether the domain had history. This is the single most load-bearing fact in any search case study and it is almost never stated.
  • The relationship. Client, employer, own property, or genuinely independent.
  • What the data cannot show. If a case study has no limitations section, somebody removed it.

What it would take to publish a rate instead of a case

A single export is a case. A rate needs a design, and stating the design is cheaper than pretending we already have one.

It would need a defined cohort, every client who started in a given window rather than the ones who did well. It would need a stated start point per domain, because a site with history and a site without are not the same experiment and averaging them produces a number that describes neither. It would need the domains that went nowhere reported alongside the ones that moved, since a cohort with the failures removed is a selection, not a measurement. It would need one window length applied to all of them, because 92 days of one domain against 30 of another is not a comparison. And it would need a stated counterfactual, even a weak one, because without it the figure is correlation presented as delivery.

We do not have that today and we are not going to imply it from one export. When there are enough clients to build the cohort honestly, the design above is what it will be built on, and the ones that did not work will be in it.

Where AI Knows Us fits

We measure whether ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews name a business when a buyer asks who to buy from, and we publish the method and the failures alongside the results. On our own domain that record currently reads: named zero times in 128 blind readings across India and the United Kingdom on 22 October 2026, and cited twice, both times on the British set. We publish our own zero because a benchmark that only ever flatters its author is not a benchmark.

Disclosure, since this page argues for disclosure: AI Knows Us sells AI visibility measurement, clawlaw.in is a client, and the two companies share a founder. Pricing is published in full on our pricing page and in our llms.txt, in rupees for India and in dollars for other markets.

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