Upholstery service
Within three months visibility recovered to about 10%, with AI again correctly representing the restructured services. A migration that could have been a lasting setback became a clean reset — on a clearer structure than before. Figures are rounded measured estimates, not exact daily rankings. Results vary by market, model, prompt set, and implementation.
Measured result
Background
An upholstery service with a healthy AI presence built up over time — until a domain migration and a restructuring of its service lineup changed everything overnight.
The challenge
The migration and restructure knocked it out of AI answers: visibility collapsed to about 2% and the models lost track of what the business now did, mapping it to the wrong services or none at all. Hard-won presence was at risk of being lost for good.
What we did
We ran it as a controlled recovery, not a rebuild:
- Mapped old-to-new URLs and implemented clean 301 redirects to preserve equity
- Rebuilt the service architecture so each restructured offering was distinct and machine-readable
- Re-established the entity and service signals the models use to match a business to a query
- Prompted re-indexing and monitored how each model re-learned the business
- Verified the models described the new service lineup correctly
Results
Within three months visibility recovered to about 10%, with AI again correctly representing the restructured services. A migration that could have been a lasting setback became a clean reset — on a clearer structure than before. Figures are rounded measured estimates, not exact daily rankings. Results vary by market, model, prompt set, and implementation.
Measurement & evidence
- Market:
- Upholstery service
- Period:
- 3 months
- Measurement:
- Fixed buyer-prompt panel, repeated across ChatGPT, Claude, Perplexity, and Google AI.
- Primary metric:
- AI Visibility — the share of relevant answers, across repeated runs of the fixed prompt panel, that name the business. How this is measured
- Starting point → latest measurement:
- 2% → 10%
- Actions completed:
- Mapped old-to-new URLs and implemented clean 301 redirects to preserve equity; Rebuilt the service architecture so each restructured offering was distinct and machine-readable; Re-established the entity and service signals the models use to match a business to a query; Prompted re-indexing and monitored how each model re-learned the business; Verified the models described the new service lineup correctly.
- Disclosed here:
- Category and market type, the measurement window, the metric definition, the provider set the prompt panel was run across, the before/after values, and the source-level work completed.
- Withheld:
- The client's name and domain, the verbatim prompt panel, and per-run answer text — the first because clients ask for anonymity, the last two because an engagement-specific panel would identify the client. Clients receive all three in their own reporting.
- Interpretation:
- Measured association after the completed work; not a guarantee that every change caused the full movement.
Before vs. after
By provider — AI Visibility
Client names withheld for privacy. Figures are rounded measured estimates, not exact daily rankings. Results vary by market, model, prompt set, and implementation. How this is measured.
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