Client case study · 4 months Illustrative

18%→41%

Enquiry-to-booked-job rate, over 4 months.

Elapsed: 4 months
How it was measured: Booked jobs matched to enquiry source in the CRM, same ad spend before and after.
Running alongside: No change to advertising budget or channels during the period.
Published with permission: Anonymised at client request

The constraint

The leads were fine. Nobody was answering them.

Six figures a year going into advertising, and enquiries landing in a shared inbox that got checked between jobs.

Median time to first contact was just over four hours. In home services the second call is usually the lost one.

Shared inbox with no owner
No record of who had contacted whom
Follow-up entirely dependent on someone remembering

What we found

The audit, including the unflattering parts

We timestamped ninety days of enquiries against first outbound contact.

Median was 4 hours 12 minutes. A quarter were never contacted at all.

26% of enquiries received no outbound contact
Median first contact: 4h 12m
No follow-up on any unanswered enquiry

The plan

The 90-day roadmap as it was actually written

One build, three weeks, no changes to marketing.

Form and call submissions create a CRM record instantly
Route by service type and postcode to the right tech's phone
Auto-reply to the customer with a booking link
Escalate to the office if nobody responds in ten minutes

Month by month

What shipped, and what it moved

The line extends as you scroll. Every step below is a real month, including the one where nothing happened.

01Month 1

Baseline

Four hours to first contact, a quarter never contacted. Same spend, same channels, same leads.

Baseline: 18%

02Month 2

Routing live

Form to CRM to the right tech's phone. Median first contact fell to 47 seconds.

+33%

03Month 3

Escalation added

Unanswered enquiries escalate to the office after ten minutes. Nothing goes cold.

+38%

04Month 4

Follow-up sequence

Three touches over ten days, cancelled the moment the job is booked.

+24%

What went wrong

The part most case studies leave out

The first build texted the on-call tech for every enquiry including out-of-area ones, so within a week they had started ignoring the alerts. We added the service-area filter and alert fatigue disappeared.

Alert fatigue is the failure mode nobody warns you about.

The first version texted the on-call tech for every enquiry, including jobs well outside the service area. Within a week the alerts were being swiped away unread, which is worse than no alert at all.

The fix was a service-area filter and a quiet-hours rule. Obvious in hindsight; we should have scoped it in the first build.

The numbers

Where it landed, and how we know

Enquiry-to-booked-job rate: 18% → 41% over 4 months. Booked jobs matched to enquiry source in the CRM, same ad spend before and after.

Booked jobs matched to enquiry source in the CRM. Advertising spend and channels were unchanged throughout, which is what makes this attributable.

Enquiry-to-booked-job: 18% to 41%
Median first contact: 4h 12m to 47 seconds
Enquiries never contacted: 26% to under 2%
Build paid back in month two

Results reflect this client's market, licence status and starting position. We publish the method alongside the number so you can judge whether it transfers to yours.

In hindsight

What we'd do differently next time

Scope the service-area filter into the first build, not the second
Add quiet hours from day one
Instrument the response time before promising anything, so the before-and-after is not arguable

Before you ask us to do this for you

Does this actually apply to your situation?

This worked because of specific conditions. If yours don't match, say so on the first call and we'll tell you what would change.

Market: Any business where enquiries arrive faster than a person can answer them.
Starting point: An existing CRM or the willingness to adopt one.
Timeline: Four to six weeks. This is one of the faster builds we do.

Start with the audit. It's free and it's specific.

Send us a URL. You'll get back the technical issues, your AI-search readiness score, what competitors are doing that you aren't, and what we'd fix in the first ninety days.

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