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2.4x rebooking rate through automated follow-up

A 3-location cleaning company had past customers dormant in Jobber. Review reactivation and an SMS agent brought back 340+ in 90 days; rebooking rate 2.4x.

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Summary

Client
Multi-Location Cleaning & Restoration
Location
Details to follow
Modules
Review reactivation, SMS agent
Integrations
Google Business Profile, Yelp, Jobber, Twilio
Timeline
3 weeks to first deploy
Commitment and result
Agreed in the build plan

Client anonymized until they approve naming.

A 3-location Southeast cleaning and restoration company had recurring work but no rebooking system: past customers sat dormant in Jobber and 1-star reviews sat on Google for days. In 3 weeks we deployed review reactivation and an SMS agent into Jobber and Twilio. Within 90 days, 340+ dormant customers returned and rebooking on targeted segments was 2.4x the previous quarter's.

What was the business?

3 locations across the Southeast offering residential and commercial pressure washing, soft washing, and exterior cleaning. $5M to $8M in annual revenue, 20+ techs, and a growing commercial accounts division.

What was broken

The business model depends on recurring revenue: annual gutter cleaning, seasonal power washing, commercial maintenance contracts. But there was no automated rebooking. Past customers sat dormant in the CRM with no follow-up.

Negative reviews were handled after the fact. A 1-star review would sit on Google for days before anyone noticed, and there was no system to turn that unhappy customer into a saved relationship.

What we built

Review reactivation. Monitors new reviews on Google Business Profile and Yelp. A negative review triggers a save flow: an immediate SMS apology, a rebooking offer at a discount, and escalation to the owner if it is unresolved within 24 hours.

SMS agent. Automated seasonal rebooking sequences for past customers, triggered by last service date, service type, and local weather patterns. Personalized messages with one-tap rebooking links.

Media pending

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Media pending

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How it went live

  1. Week 1: audit the CRM data, segment the customer base, design the rebooking sequences.
  2. Week 2: deploy review monitoring and the SMS agent into Jobber and Twilio.
  3. Week 3: testing, optimization, and handoff to the internal team.

A single module deployment: review reactivation and the SMS agent as one combined 3-week sprint. No ongoing retainer; the system runs on its own with monthly check-in calls.

The numbers

  • Rebooking rate on targeted segments

    Before
    not stated (manual outreach the previous quarter)
    After
    2.4x
    When
    Feb 2026
    Method
    Rebooking rate on targeted segments increased 2.4x compared to the previous quarter's manual outreach.

  • Dormant customers reactivated

    Before
    not stated
    After
    340+
    When
    Feb 2026
    Method
    Within 90 days, the client reactivated 340+ dormant customers through automated SMS sequences.

  • Negative review response time

    Before
    3+ days
    After
    under 2 hours
    When
    Feb 2026
    Method
    Negative review response time dropped from 3+ days to under 2 hours.

In the client's words

To follow with the customer's permission

What would we do differently?

The first SMS sequences were too frequent for some customer segments. We would build a preference center from day one rather than adding it after the first week of complaints. Seasonal triggers also need to account for local weather more precisely: a generic "spring cleaning" message does not work as well in Florida as it does in North Carolina.

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