One pooled campaign for four locations. Every site underperformed.
A four-location clinic group ran a single pooled campaign with budget spread blindly across all sites. Beeyacorp rebuilt it into per-location campaigns with radius targeting, local landing pages, and location-level call tracking. Weekly enquiries rose from 8 to 34 across the group on the same total budget, with appointment slots running out before budget did.
A four-location clinic group ran a single pooled campaign with budget spread blindly across all sites. Beeyacorp rebuilt it into per-location campaigns with radius targeting, local landing pages, and location-level call tracking. Weekly enquiries rose from 8 to 34 across the group on the same total budget, with appointment slots running out before budget did.
Four locations, one pooled budget, and no way to grow any of them
The group’s four locations shared one campaign and one pooled budget, so spend flowed toward whichever site the algorithm favoured rather than where demand and capacity actually were. No location had its own targeting, page, or tracking, and none could be optimised individually. The result was uniformly soft performance and no way to diagnose it.
Objectives
- Give each location its own campaign. Add per-site targeting and reporting.
- Tie enquiries to specific locations. Deploy call tracking by site.
- Increase total weekly enquiries. Grow output without increasing total budget.
- Match spend to demand and capacity. Allocate budget by each site’s real potential.
What the audit put on the table
We open every engagement with a full audit; everything below was documented straight from the account.
| Area | Finding |
|---|---|
| Paid Media | A single pooled campaign for four locations, with budget allocated blindly rather than by location performance. |
| Tracking | No location-level call tracking, so enquiries could not be attributed to sites. |
| Landing Pages | Generic pages with no local relevance for individual locations. |
| Structure | No radius targeting, so ads served well outside each clinic’s catchment. |
Pooling four locations into one campaign removed any ability to optimise or budget by site, and without location-level call tracking, no site’s true performance was visible; generic pages and loose targeting weakened relevance for every location.
How we fixed it
Break the pool apart. We built a separate campaign for each location with radius targeting, local landing pages, and location-level call tracking, so budget could follow demand and capacity at each site individually.
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What we did
- Split the pooled campaign. Built four location-specific campaigns.
- Applied radius targeting. Matched each clinic’s real catchment.
- Built local landing pages. Gave every location its own relevant page.
- Deployed location-level call tracking. Enabled per-site attribution.
How it was sequenced
| Phase | Timeframe | What Happened |
|---|---|---|
| Discovery | Week 1 | Location catchments, capacity, and demand mapped |
| Rebuild | Weeks 2–4 | Per-location campaigns, pages, and tracking |
| Optimise | Weeks 4–8 | Budget matched to each site’s performance |
| Scale | Month 3+ | Expansion by location and treatment value |
From 8 to 34 weekly enquiries on the same total budget
The numbers below are account-sourced, not estimated, reflecting the documented results of the engagement.
| Metric | Before | After |
|---|---|---|
| Weekly enquiries | 8 | 34 |
| Campaign structure | One pooled | Four location-specific |
| Call attribution | None | 100% by location |
| Total budget | Baseline | Unchanged |
| Appointment demand | Underfilled | Slots ran out |
Pooling locations hides the performance of each, while location-level call tracking is essential for multi-site healthcare, since group averages conceal which clinics are winning and which are starving; local relevance, in both targeting and pages, lifts performance at every site simultaneously. Multi-location healthcare groups need per-location structure, radius targeting, and location-level call tracking, a pattern we see across our healthcare marketing clients.
Frequently Asked Questions
Because budget flows to whichever location the algorithm favours rather than to where demand and capacity actually are. No individual site can be measured or optimised, so weak locations stay weak and strong ones get starved.
It attributes every phone enquiry to the specific clinic it was meant for. Without it, a group average hides which locations are winning and which are struggling, making it impossible to allocate budget intelligently across sites.
By splitting the pooled campaign into four location-specific campaigns with radius targeting and local pages, so each site's budget matched its real demand and catchment. The same total spend simply worked far harder.
For multi-location groups, yes. Local pages improve relevance for patients searching near a specific site, which lifts both ad quality and conversion for that location rather than sending everyone to one generic page.
Related client results
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