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OrcaScope

Case studies

We only show two kinds of thing here: anonymised real measurements, and ourselves. Named case studies wait for written client permission โ€” until then, one entry is better than a fabricated second.

What you won't find here: No invented clients, no borrowed logo wall, no made-up โ€œ+X% upliftโ€. Every number below comes from real sampling in our production database. The brand has not authorised being named, so it is published anonymised โ€” we don't even state the category, since that alone would identify it.

One real quarterly re-measurement

Anonymised ยท real data

35 prompts ยท 8 engines ยท Chinese and English ยท a 30-day window. The three numbers below come from one and the same sampling run.

97.9%
92 / 94
Mentioned, in-category
8 prompts
0.2%
4 / 1647
Mentioned, broad category
27 prompts
2.12
v4
Overall visibility score
as of 2026-08-01

โ‘  One score split into two โ€” only then does it mean anything

An overall score of 2.12 looks bad. But 27 of the 35 prompts target the broad category โ€” 77% of the weight sits on a battlefield where this brand is simply absent. The overall score faithfully reflects that weighting: it doesn't say โ€œthis brand is weakโ€, it says โ€œwe're mostly measuring where it hasn't turned up yetโ€. Reporting the single number alone would lead a client to exactly the wrong conclusion.

โ‘ก Three weeks earlier we refused to draw this conclusion

In the previous report, the in-category mention rate read 50% โ€” on a sample of 2. We flagged it as โ€œโš  n=2, a lead rather than a conclusionโ€ and did not let the client act on it: one flipped cell would have made it 0% or 100%. This period the sample reached 94 cells at 97.9%, and only then did the lead become a conclusion.

When n is too small we say nothing; when it is large enough we speak. That is the reason to trust the rest of the numbers โ€” and the only thing we ask you to take on trust.

โ‘ข The 0.2% is solid

1,647 cells, 8 engines, both languages, 30 days โ€” mentioned 4 times. That isn't one platform's bias; it's across-the-board absence. This conclusion can be acted on.

The same ruler, pointed at ourselves first

Verify it yourself

Until we have a named client endorsement, the most honest proof is to lay our own practice open. Each of the four below can be checked on the spot โ€” anything we couldn't let you check, we left out.

The scoring methodology is published in full

How scores are computed, how citations are judged, how thin samples are flagged โ€” auditable and reproducible.

Read the methodology โ†’

8 engines, each scored separately

Only engines that actually work are labelled "Live" โ€” engines still being integrated never enter a score or a chart.

See the engine roster โ†’

Industry benchmarks are public

Per-industry percentiles are published openly; industries with fewer than 5 sampled brands publish nothing โ€” a privacy floor enforced in the database, not by policy.

See the benchmarks โ†’

Run a free checkup yourself โ€” no signup

You don't have to take our word for it: enter your own brand name and get a snapshot in minutes.

Run a free checkup โ†’

Want to be the first named case study here? We don't pay for a name and we don't trade discounts for endorsements โ€” we'll ask you once, and only once your own numbers feel worth talking about.

Start with a free checkup โ†’
Case studies ยท OrcaScope