SEO case study · The last three months against the same three months a year earlier
A property platform added close to a million search clicks in three months
Google was spending its time on filter pages that had nothing to rank. Cleaning that up, rewriting listings for search and building neighbourhood pages took clicks from 2.15M to 3.1M.
77M
impressions, from 70M
4%
click-through rate, from 3.1%
5.5
average position, from 7.7
Measured over
The last three months against the same three months a year earlier
What to notice
The top row reads 3.1M clicks against 2.15M and 77M impressions against 70M. On the chart the solid band for this year runs above the dashed band for last year across the whole period, with no single spike.
Want numbers like these?
Get a free written review of your own account.
Who the business is
A national property and real estate listings platform. It is not named here, so it is described by its trade and by what the screenshot shows.
Why marketing mattered
Property searches are local down to the street. The platform with a real page for each neighbourhood meets the buyer first.
- Service
- SEO
- Sector
- National property listings platform, SEO
- Period measured
- The last three months against the same three months a year earlier
- Figures from
- A Search Console performance screenshot for the account
What was not working
The problem
A national property listings platform where Google spent much of its crawling on filter pages with nothing unique on them, and where neighbourhood-level searches had thin pages or none.
- Google spent crawl time on filter-combination pages with no unique content.
- Category listings in search were functional and looked like everyone else's.
- Neighbourhood, postcode and new-development searches had thin pages or none.
Where things stood before the work began
In the same three months a year earlier the platform took 2.15M clicks from 70M impressions, at a 3.1% click-through rate and an average position of 7.7.
- 2.15M
- clicks, same period last year
- 70M
- impressions
- 7.7
- average position
What we found, and why we started there
The thinking
On a site this size no single change moves the total. Three were made together: stop wasting Google's crawl, make each listing in search more specific, and cover the local searches the site was missing.
How we did it, step by step
- 1
Filter pages closed to indexing
Filter combinations beyond one level were set to noindex, paginated pages were given canonical tags, and a clean sitemap of real listings and editorial pages was submitted.
- 2
Titles and descriptions rebuilt
Category and location pages now lead with the place and property type, include a live count of listings and end with a price indicator.
- 3
Pages for 4,200 local search groups
Neighbourhood names, postcode prefixes and new developments found in the search data each got an improved or new page.
What the numbers show
The result
3.1M
organic clicks in three months, up from 2.15M
3.1M clicks against 2.15M in the same three months a year earlier, and 77M impressions against 70M. Click-through rate rose from 3.1% to 4% and average position improved from 7.7 to 5.5.
| Measure | Same period last year | Last three months |
|---|---|---|
| Clicks | 2.15M | 3.1M |
| Impressions | 70M | 77M |
| Click-through rate | 3.1% | 4% |
| Average position | 7.7 | 5.5 |
From the work to the outcome
- Crawl waste removed
- Position 7.7 to 5.5
- 77M impressions
- 3.1M clicks
How to read this, and what it does not prove
A three-month comparison against the same period a year earlier, from Search Console. Year-on-year comparisons remove the season and add a year of other changes.
A year separates the two periods, so other things changed too, including the property market and Google itself. Clicks are visits, not enquiries to agents. The figures are read from a small screenshot of a very large account. The client is not named, so a reader cannot check the screenshot against the account. It is one account with no control group: it shows what happened alongside the work, and it cannot show how much of that the work caused.
Want this for your business?
It starts with a free written review.
What you can take from this
Do not let filters fill Google's index
If your site makes a page for every filter combination, tell Google which ones count.
Put a number in the title
A live count of listings tells a searcher the page is worth opening.
Go one level more local
City pages are crowded. Neighbourhood and postcode pages are where a listings site can still win.