JATJay Templeton Consulting
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home-services · Growth · AssistBuy it

Automated review requests for local SEO

01 — The scenario

A home-services business where this lands in Marketing.

The friction
reviewslocal-seoreferralsreputation

02 — What is actually going wrong

You do good work and have eleven reviews. The competitor three suburbs over does average work and has four hundred. In local search that gap decides who gets called, and the only difference between you is that they ask every single customer and you ask when you remember.

How it works

When a job is marked complete, a text goes out a few hours later with a direct link to your review profile. Drafting help turns a customer's two-word reply into something readable, and negative sentiment gets routed to you privately instead of to the public page.

What good looks like

Review count climbs steadily every month without anyone thinking about it, your map-pack position improves for the suburbs you actually serve, and unhappy customers reach you before they reach Google.

03 — The problem, in money

$18,225$14,231,250/ yr at stake
Modeled
  • Completed jobs per month120 jobs1,000 jobsPlaceholder — not a validated benchmarkStarting point
  • Extra reviews per job0.15 ratio0.5 ratioPlaceholder — not a validated benchmarkStarting point
  • New leads per review0.5 leads2.5 leadsPlaceholder — not a validated benchmarkStarting point
  • Average job value450 USD2,530 USDPlaceholder — not a validated benchmarkStarting point

04 — The options

Buy$50–$150 / moOff-the-shelf tooling, live sooner.
Bin$0Do nothing — and accept the leak.

05 — The call

Buy it

Buy it. An off-the-shelf tool wins this one — it gets you live faster, and the math does not justify building from scratch.

06 — How this goes wrong

  • Review gating — filtering out unhappy customers before the ask — breaches Google's policy and can get your profile stripped. Route negatives privately, but never block them from reviewing.
  • Never let AI write the review itself. Fabricated reviews are fraud, and platforms are increasingly good at spotting them.
  • Asking too early. Send before the customer has seen the finished work and you are asking them to rate a mess.
  • Blasting your whole back catalogue on day one. Forty reviews in a week reads as bought and can trigger a filter.

07 — How you would actually do it

  1. 01Confirm your review profiles are claimed and the deep links work on mobile.
  2. 02Pick the trigger point — job marked complete, invoice paid, whichever is more reliable in your system.
  3. 03Set the delay by job type: same-day for a quick service call, a few days after a big install.
  4. 04Write the message in your own voice, short, with the technician's first name in it.
  5. 05Route anything with negative sentiment to the owner's phone instead of the public link.
  6. 06Cap the daily send rate when you first switch it on.

08 — Tools worth looking at

NiceJob / PodiumPurpose-built review engines with trade integrations.
BirdeyeHeavier, multi-location; overkill for a single crew.
Your FSM softwareJobber, Housecall Pro and ServiceTitan all ship review automation — check before buying.

Named for orientation, not endorsement. No affiliate arrangements, and nothing here has been paid for.

09 — Run it on your numbers

Start from industry averages, then drag the inputs to match your business. The number moves live.Drag each input to your number — the starting points are neutral midpoints, not industry data. The number moves live.

Worth to your business
$18,225per year
Modeled — industry averages
Revenue$48,600Modeled
Cost savings$0Modeled
Hours / week0Modeled
Industry averages
120 jobs
Industry avg: 120 jobsPlaceholder — not a validated benchmark
0.15 ratio
Industry avg: 0.15 ratioPlaceholder — not a validated benchmark
0.5 leads
Industry avg: 0.5 leadsPlaceholder — not a validated benchmark
450 USD
Industry avg: 450 USDPlaceholder — not a validated benchmark

10 — The evidence · what others report

No hard numbers reported.

Reported numbers are third-party claims, source-attributed — not verified by me, and never blended into the model above.

11 — Questions owners ask

Every figure is Modeled — computed from industry-average benchmarks against the scenario’s formula. Move the sliders to your own inputs and the numbers recalculate live. Nothing here is a promise; it is a starting estimate you can pressure-test.
The library is organized by department, outcome, effort and readiness so you can find what fits. Add scenarios to your plan, tune the inputs, and see the combined picture on your plan dashboard.
Want this to be a Projected number? That's what the Audit produces — my forecast on your real data, with my name on it.
Build means a custom system is the right move; Buy means an off-the-shelf tool wins; Bin means the math does not justify doing it at all. Binned scenarios can be favorited for reference but never enter a plan.

Is this your business?

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