Skip to content
All For One
(602) 428-9228 Get a quote
An air conditioner condenser beside a stucco home, with a tool bag and gauges on the pad
All work
Case 04 / 08 East Valley HVAC company

Local SEO built on what people actually search

The owner wanted commercial pages. The search data said almost nobody was looking. So I rebuilt the site around the 6,710 searches a month that were real, and found the niche he had named himself.

Headline figure
6,710 searches a month mapped across the company's 16 service cities
Built with
Eleventy, Component library, Keyword research API, Census data
Status
In progress
The problem

The company wanted to rank for commercial work. Before writing a word, I pulled the search data. Every commercial term came back at 0 to 40 searches a month. The site was aimed at demand that barely existed and was missing the demand that did.

The numbers

Measured on the project. Nothing rounded up, nothing projected.

01 6,710 searches a month mapped across the company's 16 service cities
02 ~600 monthly Arizona searches for evaporative cooling, at low competition
03 0 to 40 monthly searches for each commercial term the owner first asked for
04 18 city pages re-pointed at real search demand, with zero duplicated sentences between them
03

What I found

6,710 searches a month across their 16 service cities, with "ac repair" plus the city name as the top term in every one of them. And one the owner had mentioned himself: about 600 searches a month for evaporative and swamp coolers in Arizona, at low competition. His own differentiator was sitting in the data.

Inside the build

Mockups with sample data. The way the system works is real.

  1. 01 / 02The search data came first, before a word of copy was written.

  2. 02 / 02City pages built around the searches that were real. Shown here as a generic mockup.

04

What I built

  • All 18 city pages re-pointed at real demand, four rewritten from scratch, with zero duplicated sentences between any two pages
  • A dedicated swamp-cooler page
  • A commercial section with structured data that matches the visible copy exactly
  • The client's own job photos and drone footage in place of 22 placeholders
Top-down aerial of an Arizona neighbourhood with backyard pools
05

Status

In progress. The new pages are on a preview build ahead of launch, so there are no ranking results to report yet, and I will not make any up.

Built with

  • Eleventy
  • Component library
  • Keyword research API
  • Census data
  • JSON-LD

The client is kept anonymous. Every number on this page was measured on the project. Photos are stock and screens are mockups with sample data.