Case Study · Carpet Clean Expert
Google LSA message leads qualified without a full-time coordinator.
Carpet Clean Expert relies on Google Local Services Ads to fill the schedule. InstantResponse.AI replies to LSA message leads, asks the configured intake questions, and passes the customer's preferred day and time to the team for human confirmation. Full calendar booking is currently in Beta.
Intake answers captured and a preferred window passed to the office for confirmation.
Illustrative example based on real product behavior. Not a guarantee of results.
The account's LSA message leads are answered by the configured assistant.
Rooms, square footage, fibers, and pet or stain notes, as configured by the business.
The customer's preferred window is passed to the team. Full calendar booking is in Beta.
These describe how the account is configured, not measured performance. We do not publish response-time, booking, or revenue figures for individual customers, and results vary by market and lead volume.
The challenge
Where leads were slipping through.
Carpet Clean Expert did not want to staff a full-time coordinator just to watch Google LSA message leads, but unanswered messages left customers waiting and gave the office no context to work from. Quick answers without intake questions also meant techs arriving without knowing what they were walking into.
The approach
What InstantResponse.AI runs for them.
- 1
Reply quickly to Google LSA message leads, in a voice consistent with the brand.
- 2
Ask the right cleaning intake questions: number of rooms, approximate square footage, carpet vs area rug, fiber type if known, and pet or stain concerns.
- 3
Confirm a preferred day and time with the customer, accounting for large or complex cleans (full calendar booking is in Beta).
- 4
Automatically nudge quotes that do not confirm right away so warm LSA leads stop going cold.
The outcome
What changed after switching on the AI front desk.
LSA message leads arrive as complete conversations with intake answers and a preferred window instead of phone-tag half-quotes, so the team can confirm work with context in hand rather than starting from a voicemail.
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