Case study 02

Four metros competing against each other, all under one brand.

A replacement contractor operating across four metros in the Southeast, with 96 near-identical service-area pages that ranked for none of them.

Outcome

Nine months after launch.

Three figures from the engagement, each traced to the client's own reporting rather than ours.

01 CLIENT ANALYTICS
96 to 34

Pages that earn traffic

Ninety-six thin service-area pages were consolidated into 34 that each answer a distinct query. Organic sessions rose while page count fell by two thirds.

02 CLIENT CRM EXPORT
3.4x

Leads from the two weaker metros

The two metros the company had almost written off produced 3.4 times the qualified form fills they had in the comparable period.

03 CLIENT REPORTING
-58%

Cost per booked job

Blended acquisition cost across all four metros, comparing the quarter before the rebuild with the third quarter after it.

FIGURES APPROVED IN WRITING BY THE CLIENT. COMPANY NAME WITHHELD UNDER A CONFIDENTIALITY AGREEMENT.

The situation

Growth by acquisition had left the company with four metros served from one domain and a service-area template that swapped the city name into otherwise identical copy. Google treated the set as duplication. The two acquired metros were producing almost nothing and the owner was close to shutting one down.

What the audit found

Of 96 service-area pages, 71 had no impressions at all in the previous six months. Every one carried the same three paragraphs. There was no entity connection between a metro, the services offered there, and the crews who worked it, so nothing established that this was a real local operation rather than a national skin.

What we did about it

The matrix ranked every service against every suburb across all four metros by revenue potential. Thirty-four suburbs justified a page. Each one got genuinely local content, including permit rules, common roof stock, and storm history, with schema tying the metro to the services and the service area.

Where it landed

The weaker metros recovered first, because nobody there had published a real answer to anything. The strongest metro moved slowest, which is what you would expect where three competitors already publish well.

Before and after

Ninety-six pages, then thirty-four.

Fewer pages, more traffic. That is usually how it goes.

Before At audit

Templated across four metros

SERVICE-AREA PAGES96
PAGES WITH IMPRESSIONS25
UNIQUE COPY3 PARAGRAPHS
ENTITY MODELNONE
AI CITATIONS0 OF 62
After Nine months after launch

Thirty-four real local answers

SERVICE-AREA PAGES34
PAGES WITH IMPRESSIONS34
UNIQUE COPYPER SUBURB
ENTITY MODELMETRO + SERVICE
AI CITATIONS27 OF 62

FIGURES SUPPLIED BY THE CLIENT AND APPROVED IN WRITING. COMPANY NAME WITHHELD UNDER A CONFIDENTIALITY AGREEMENT.

What shipped

Consolidate first, then build.

01 / DISCOVER

Paid Discovery

Crawl of all 96 pages, a 62-query set across four metros, and a matrix ranking every service and suburb by revenue.

02 / CONSOLIDATE

Redirect and merge

Sixty-two pages retired into 34 with a full redirect map, so nothing that had earned authority lost it in the move.

03 / BUILD

Rebuild and launch

Metro hubs, per-suburb pages with local specifics, entity schema across the set, and post-launch crawl verification.

Questions

Questions about this engagement.

Does cutting pages not cut traffic?+

Not when the pages were duplicates. Sixty-two of them had no impressions in six months. Consolidating concentrated the authority instead of splitting it.

How do you write local content at that scale?+

Research per suburb on permits, roof stock, and storm history, written by people who work in this trade. It is slower than a template, which is why the matrix decides where it is worth doing.

What happened to the metro they nearly closed?+

It is now the second-strongest of the four by booked revenue.

Want this run on your market?

$2,500, and you find out what is winnable.