Home Improvement Google Ads Case Study: 3,160 Enquiries at £57.48 Each (UK)

Enquiries Generated
Six figures of quarterly spend held to £57.48 per enquiry, with an 8.61% CTR on Search
The Challenge
This is a considered, high-value home-improvement purchase: the customer researches for weeks, compares installers, and rarely buys on a first visit. At £182K of quarterly spend across a national UK audience, the risk is not a lack of traffic — 8.6 million impressions were served in the quarter — but paying premium prices for clicks that never become a quote request.
Our Approach
- Separated the account by intent rather than by product, so research-stage searches and quote-ready searches were never bidding against each other for the same budget.
- Tracked the enquiry itself as the conversion — brochure requests, quote requests and catalogue downloads — rather than optimising toward page views or time on site.
- Kept engagement actions such as the 3D fence designer tool, basket adds and phone-number clicks measured but outside the primary conversion column, so Smart Bidding optimised toward real enquiries instead of browsing.
- Ran Search and Performance Max to different jobs: Search to capture people already looking for the product, Performance Max to find demand across Google's other surfaces, with budget moved between them on reported cost per enquiry.
- Reviewed search terms weekly across a large national keyword set, where a single unqualified theme can absorb thousands of pounds before it shows up in a monthly report.
The Results
Over July to September 2026 the account generated 3,160 tracked enquiries from £182K of spend — an average cost per enquiry of £57.48 — from 168K clicks and 8.6 million impressions. Search carried an 8.61% click-through rate across roughly 774K Search impressions, well above the volume-weighted account average, while Performance Max added reach across Google's other inventory. Figures are as reported in Google Ads for the quarter; the enquiry count continues to rise slightly as conversions attribute back to their click dates.
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