Closing the Hyperlocal Gap for Real Estate Auction Company
Google’s results had gone city-by-city, but Real Estate Auction Company’s SEO landing pages stopped at the state line. We shipped 1,000 city pages against the highest-priority markets and re-pointed the sitemap at Google. Here’s how the first 58 days are pacing against the modeled trajectory toward Low, Mid, and High ranking targets.
Search went hyperlocal. The site pages didn’t.
Real Estate Auction Company sells foreclosed homes, and buyers already search city by city: “foreclosed homes San Diego,” not “foreclosed homes California.”
Google’s own results reflect that: a generic query like “foreclosed homes” auto-resolves to city-level results with no location typed in the query at all, and every major competitor (Zillow, Trulia, Redfin, Realtor.com) ranks with a dedicated city page. Real Estate Auction Company had buyer intent at the city level and a real listing inventory to match it, but its SEO footprint stopped at the state page. That mismatch was the entire opportunity.
1,000 city pages, prioritized by demand.
We ranked every U.S. city by GA4 demographic demand and built a template that could scale to all of them without engineering re-litigating layout per market.
We partnered with Real Estate Auction Company’s web engineering team to launch the 1,000 highest-priority cities first, each with its own filterable listing view, auction-status data, and city-specific copy. The site’s XML sitemaps were rebuilt to include the new URLs and resubmitted to Google Search Console to accelerate discovery and indexation.
Day 58 of the program
The forecast isn’t three parallel outcomes. It’s one path. As the 1,000 city pages earn crawl trust and links, their average ranking position climbs, and traffic compounds rather than adding up linearly. Low, Mid, and High are the same forecast model’s near-term, later, and long-term readings of that one climbing curve, each tied to an average position the keyword set is expected to hold by that point.
The lift held as the sample grew.
The original case study reported the first 30 days. Extending the same read through day 58 nearly doubled the volume without diluting the rate: a sign the early read wasn’t a launch spike.
- Lift
- City-page total divided by sitewide organic total net of city pages, for the same date range (Jul 13–Sep 8, 2026). Sessions: 16,080 ÷ (111,649 − 16,080) = 16.8%. Events: 513 ÷ (15,804 − 513) = 3.4%.
- Low / Mid / High targets
- Search volume per target keyword × the average click-through rate for a given SERP position (source: FirstPageSage CTR-by-position study), summed across the home-auction and foreclosure keyword sets, at the average position each target assumes as rankings mature (position 8, 5, and 3 respectively).
- Trajectory
- A single compounding (exponential) curve fit through the day-58 actual run-rate and the High-target month, on the premise that ranking gains compound rather than accrue linearly. Low and Mid are the months that same curve crosses their target values: they are outputs of the curve, not independently scheduled.
- Day count
- Day 1 is July 13, 2026, the first date with recorded GA4 sessions to a city page. This report reflects data through September 8, 2026, 58 days live.
- Agency & attribution
- This program was delivered while employed at Ignite Visibility, a digital marketing agency, on behalf of a real estate auction client. Jonathan Catalan was the SEO Director responsible for this work. The client’s name has been withheld here; screenshots are shown for illustrative, factual reporting purposes.