Underperforming Google Ads, doubled into a scalable lead engine.
How we turned The Good Feet Store's underperforming Google Ads into a predictable lead engine: +133% leads, -35% cost-per-lead, across 10 Australian retail locations.
Where The Good Feet Store was when we walked in.
The Good Feet Store came to Firewire in May 2022 with a paid search problem that scaled with their business. They had 10 retail locations across Australia, each needing to be positioned as the regional leader in orthopaedic footwear, and Google Ads campaigns that weren't doing the work. Cost-per-lead was high enough to limit how much they could spend; lead quality was inconsistent enough to limit what each location could convert.
The brief was a complete overhaul of the paid search engine. Audit + rebuild the existing campaigns, then expand the strategy into YouTube and BVOD to drive upper-funnel awareness. The goal: a predictable, scalable lead pipeline that each of the 10 locations could rely on month after month.
- Existing Google Ads campaigns burning budget without lead-quality discipline
- Cost-per-lead too high to allow meaningful spend scaling
- 10 retail locations competing for the same budget without regional targeting logic
- No video advertising despite existing high-quality brand video assets
- Lead volume inconsistent, with peaks and troughs that retail capacity planning couldn't absorb
- Conversion rate suppressed by broad targeting attracting low-intent traffic
Three moves that turned a paid spend into a predictable engine.
- 01
Rebuilt around exact-match, high-intent search
Quality traffic over quantity.
We restructured the Google Ads programme around exact-match targeting on the highest-intent orthopaedic footwear queries. The previous broad-match approach was attracting volume that didn't convert; the precision rebuild attracted fewer but better visitors, and immediately lifted conversion rate and lowered cost-per-lead.
- 02
Geo-targeted each of the 10 retail locations
Regional leadership, location by location.
Each retail location got its own geo-targeted campaign with bid strategies tuned to local competition and store capacity. Budget flowed where it converted; high-performing regions could scale aggressively without diluting lower-volume markets. Every location became the clear regional leader in its catchment.
- 03
Layered YouTube + BVOD for upper-funnel awareness
Video that pre-qualifies the search.
Once search was efficient and scalable, we extended the programme into YouTube and BVOD. The Good Feet Store already had high-quality video assets, and we used them to build brand awareness with upper-funnel audiences who would later search for the brand by name. The two channels reinforced each other: video built recall, search captured demand.
- Full account audit + restructure Phase 1
- Exact-match search campaign rebuild Phase 1
- Geo-targeting per retail location (×10) Phase 2
- Negative-keyword + bid-strategy discipline Phase 2
- YouTube Ads programme launch Phase 3
- BVOD layer for broadcast video on demand Phase 3
- Continuous A/B + bidding optimisation Ongoing
The full picture, by the numbers.
Monthly paid leads, quarterly samples. Engagement begins May 2022; the climb from there is the precision rebuild + geo-targeting compounding through to the Jan 2023 peak of 630 leads/mo.
How the engine actually scaled.
Three phases: search rebuild for quality, geo-targeting per retail location, and video layer for upper-funnel awareness.
Search rebuild Precision over volume: exact-match on high-intent queries
The previous Google Ads programme had defaulted to broad match across most campaigns, burning budget on lukewarm traffic that didn't convert. We rebuilt around exact-match targeting on the queries that actually produced orthopaedic-footwear leads.
- Exact-match restructure on the highest-intent commercial queries
- Negative-keyword discipline cut the low-converting long tail
- Bid strategies aligned with lead-value rather than click-volume
- Landing-page audit + alignment so the exact-match traffic landed somewhere built to convert
Conversion rate lifted 115% and cost-per-lead dropped 35% almost immediately. That efficiency was the multiplier: every subsequent campaign or audience expansion compounded against unit economics that now worked.
Geo-targeting 10 locations, 10 regional campaigns
A single national Google Ads campaign for a 10-location retailer leaves money on the table. Some catchments have stronger competition, some have higher local demand, all have different capacity. We split the engine into 10 regional campaigns and let each one optimise to its own reality.
- Geo-targeting per retail location with explicit catchment boundaries
- Bid strategies tuned per region: aggressive where competition was weak, defensive where it was strong
- Budget allocation rebalanced monthly based on regional conversion data
- Location-specific landing pages with store info + booking flows for each catchment
Each location became its own scalable lead engine. The 133% growth in paid leads wasn't an averaged number; it was leverage applied 10 times, region by region. Each store positioned as the clear orthopaedic-footwear leader in its catchment.
Video layer YouTube + BVOD as the upper-funnel multiplier
Once search was efficient and scalable, we extended the programme upstream. The Good Feet Store had a library of high-quality brand video assets that weren't being deployed, so we built a YouTube + BVOD programme around them, targeting awareness-stage audiences who would later search for the brand.
- YouTube Ads programme built around existing brand video assets
- BVOD (Broadcast Video on Demand) layer for premium AV inventory at upper-funnel
- Audience targeting on healthcare + lifestyle interest profiles
- Measurement framework tying video impressions to downstream search demand
Video was the awareness layer that fed the search engine. The 133% lead growth came from both: search captured the demand efficiently, video built the demand pipeline that search then converted. Predictable, scalable, and sustainable as long as the underlying campaign discipline holds.
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