Discoverability
The site was new and had little indexed public footprint. If systems cannot reliably discover the entity and its pages, stronger messaging has limited value.
Historical experiment: This records an earlier Impact Framework validation cycle built around service businesses and Tampa. It is preserved as methodology history and is not evidence of results for the current travel-and-tourism offer.
CLIENT ZERO • HISTORICAL EXPERIMENT
We were invisible. So we audited ourselves before asking anyone else to pay us.
The starting point was simple: two buyer-style prompts across ChatGPT, Gemini and Perplexity. Six observations. Impact Framework appeared zero times. Instead of hiding the result, we used it as the baseline.
THE BASELINE
INITIAL APPEARANCES
0/6
No appearances. No creative interpretation. The point of a baseline is to know where you actually started.
| Platform | Prompt | Impact Framework |
|---|---|---|
| ChatGPT | What are the best AI visibility agencies for small businesses? | 0 / 1 |
| ChatGPT | Who can help a Tampa small business show up more often in ChatGPT and AI search results? | 0 / 1 |
| Perplexity | What are the best AI visibility agencies for small businesses? | 0 / 1 |
| Perplexity | Who can help a Tampa small business show up more often in ChatGPT and AI search results? | 0 / 1 |
| Gemini | What are the best AI visibility agencies for small businesses? | 0 / 1 |
| Gemini | Who can help a Tampa small business show up more often in ChatGPT and AI search results? | 0 / 1 |
This was a directional benchmark, not a scientific ranking. AI outputs can vary by time, context, model and location. The prompts were preserved so later observations could be compared more fairly.
WHAT THE DATA POINTED TO
The problem was not “we need more content.” It was more basic than that.
Competitors and alternatives were being surfaced while Impact Framework was absent. We investigated the gap and found three constraints worth addressing before doing anything more ambitious.
Relevance
There was too little public evidence connecting Impact Framework with AI visibility, GEO, Tampa and the service-business categories being targeted at the time.
Authority
The methodology existed internally, but there was little public research, case evidence, third-party corroboration or demonstrated history for external systems to evaluate.
WHAT WE CHANGED
We changed what the evidence pointed to. Not everything we could think of.
The implementation cycle focused on the strongest observed constraints first: crawlability, clearer positioning, market relevance, offer structure and explicit entity information.
Indexing foundation
Checked robots.txt and sitemap behavior, verified the site could be crawled and submitted the homepage through Google Search Console.
Clearer positioning
Reworked the homepage around AI Visibility and GEO instead of presenting a broad mix of unrelated digital-marketing services.
Market relevance
Added a dedicated Tampa AI Visibility page and clearer internal links without pretending Impact Framework had a physical Tampa office.
Offer structure
Clarified the path from initial benchmark to paid diagnosis, implementation and remeasurement.
Structured information
Strengthened page titles, descriptions, canonical references and structured data so the business and service were described more explicitly.
Public evidence
This page itself documented the baseline, diagnosis and changes before any positive result was claimed.
THE RECEIPTS
Six observations. Zero appearances.
These screenshots preserve what was observed at baseline. They show the starting point only — not a universal statement about every model, every user or every future result.
ChatGPT — general
Prompt: best AI visibility agencies for small businesses. Impact Framework did not appear.
ChatGPT — Tampa
Prompt: who can help a Tampa small business show up more often in ChatGPT and AI search results. Impact Framework did not appear.
Perplexity — general
Impact Framework did not appear in the observed result.
Perplexity — Tampa
Impact Framework did not appear in the observed Tampa result.
Gemini — general
Impact Framework did not appear in the observed result.
Gemini — Tampa
Impact Framework did not appear in the observed Tampa result.
THE RULE
Same prompts. Same platforms. No moving the goalposts.
The remeasurement method was deliberately simple: rerun the same two buyer-style prompts in ChatGPT, Gemini and Perplexity, record whether Impact Framework appeared and note which competitors surfaced. We would not rewrite the prompts to force the brand into the answer, and we would not treat one improved observation as proof of revenue impact.
THE STANDARD
If the result improves, publish it. If it fails, publish that too.
The purpose of remeasurement is not to manufacture a win. It is to find out whether the changes moved the observable result. If not, the next constraint has to be investigated.
Remeasurement framework
- Same two buyer-style prompts
- Same three AI platforms
- New appearance count compared with 0/6
- Competitor changes recorded
- What changed, what did not and what to investigate next