Case studies · Approved client outcomes
GEO Case Studies & AI Share-of-Voice Benchmarks
Approved, anonymized client outcomes connecting entity clarity, useful content, and AI search measurement.
By Best4GEO · Warsaw, Poland
The following outcomes were confirmed and approved for publication by Best4GEO. Client names are withheld. These are individual case results, not an industry-wide benchmark or a guarantee for future engagements.
Case Study 1 — Regional B2B SaaS Expansion into CEE
Problem
Competitors were appearing in ChatGPT vendor recommendations for European tech expansion while the client's brand was absent from the measured non-branded recommendation sample. The business needed a clearer entity footprint and useful, source-ready explanations of its regional offering.
Work Performed
- JSON-LD schema injection clarified organization and service relationships on the client's site.
- Entity verification on Clutch and Crunchbase aligned relevant third-party company information with the website.
- Data-dense guide publishing explained regional requirements, service scope, and buyer questions in accessible, structured content.
Results
- Non-branded AI recommendation rate
- 0% → 38%
- Within 60 days · +38 percentage points
- Qualified strategy call bookings
- 4.2×
- Increase relative to the reported baseline
The reported recommendation rate moved from 0% to 38% on non-branded AI prompts within 60 days, alongside a 4.2x increase in qualified strategy call bookings. The recommendation-rate change is expressed in percentage points; relative percentage growth is undefined from a zero baseline.
Exact prompt counts, calendar dates, and the client's raw response and booking records are not published on this page. The figures describe the approved case outcome and should not be interpreted as a controlled experiment establishing that GEO alone caused the booking increase.
Case Study 2 — B2B AI Search Visibility Audit for Industrial Services
This engagement examined how an industrial-services buyer journey surfaced regional expertise in AI-generated answers.
Results
The approved reported outcome was a direct citation in Perplexity AI answer overviews as a top Warsaw-based agency. This is a citation observed in the case, not a claim of a permanent Perplexity ranking or a universal recommendation across every industrial-services prompt.
A numerical citation rate, observation date, and before-and-after share-of-voice dataset are not published for this case. We therefore do not assign an invented percentage, timeframe, or traffic uplift to the result.
Reading AI Share-of-Voice Benchmarks Responsibly
A recommendation rate is the fraction of completed answers that recommend a brand. Share of voice compares that brand's recommendations with recommendations for a fixed competitor set. They are different measures: a 38% recommendation rate is not automatically a 38% share of voice.
Compare like-for-like prompts, markets, languages, and engine settings, and retain the raw completed sample counts. Track qualified bookings separately with a consistent qualification rule and attribution window. Our measurement methodology explains the definitions and limits used to interpret these results.