The Back Catalogue

Case studies.

Illustrative scenarios built for this scaffold, not real named clients. Replace with documented client results and written permission before launch.

Reputation: 30 reviews in 30 days

A 22-person foundation repair company averaging 4 new reviews a month, with a 4.3 rating dragged down by three unanswered one-star posts.

  • Review requests on every closed job
  • Private feedback gate before public ask
  • AI responses to the full review backlog

Reactivation: 900 dead estimates

A waterproofing group with roughly 900 estimate requests from the prior 24 months that never converted and were never followed up.

  • Segmented by reason for going cold
  • Worked in controlled weekly batches
  • Booked straight onto the inspection calendar

Nurturing: nights and weekends

A crawl space and concrete leveling firm losing after-hours inquiries to competitors who happened to answer first.

  • Sub-60-second reply around the clock
  • Long-cycle drip for undecided homeowners
  • Live handoff on urgent water intrusion
Worked example

Reactivating a 900-contact database

The situation

A basement waterproofing company with four inspectors and a healthy inbound flow. Their CRM held about 900 estimate requests from the previous two years that had gone quiet. No follow-up process existed beyond a manual call attempt in the first week, because nobody had time for more.

What we found in the audit

Segmenting the list revealed three distinct groups. About 40% had received a written quote and gone silent — usually a price objection. About 35% had inquired but never got as far as an inspection. The remaining 25% were past customers who had one area of the home repaired while another was flagged as a future concern.

Consent records existed for the large majority, captured on the original inquiry forms. A subset had no documented consent and was excluded from texting entirely.

What we ran

Sent in weekly batches of roughly 150 to protect deliverability and keep replies manageable. Every message carried opt-out instructions; STOP requests were honored immediately and permanently.

Illustrative outcome

In the first two weeks, roughly 60 inspections booked from the initial batches, with the past-customer segment converting at the highest rate and the price-objection segment producing the largest average ticket once financing was surfaced early. About 8% opted out — a healthy, expected number that also cleaned the database permanently.

Why it worked

Nothing clever. The demand already existed and had already been paid for; it simply had never been asked a second time in a way that acknowledged why the homeowner stopped. Segmentation did most of the work, and booking directly onto the calendar prevented the usual drop-off between "yes, I'm interested" and an actual appointment.

A note on this page

Everything above is an illustrative scenario written to show the shape of the work, using representative numbers. It is not a real named client and should not be presented as one. Before launch, replace it with documented results from actual clients who have given written permission — real numbers from a real company are far more persuasive than a well-written hypothetical.

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