01
E-commerce · Fashion · Romania
Made-to-order footwear
Initial situation
Made-to-order footwear brand with over 1,500 active SKUs. Smart Shopping had been running for two years with ROAS around target but with no ability to control granularly by SKU. Margin varied dramatically across categories, but campaigns treated all products identically — budget flowed equally to profitable and break-even SKUs.
What I changed
- Full Merchant Center feed audit and restructure by margin attributes
- Migration from Smart Shopping to Performance Max segmented by margin category
- Automated exclusion rules for SKUs below minimum profit threshold
- Custom audiences based on customer value (LTV, frequency, recency)
- Server-side tracking for purchase events + value optimization
The result
ROAS sustained above the client's 5× target, maintained 90+ days post-implementation. Budget automatically concentrated on high-margin categories while break-even SKUs were excluded without loss of total volume.
Duration · 90 days · Status · Active
02
Services · Emergency · UK
Emergency callouts
Initial situation
UK provider of emergency intervention services (24/7) in a niche with five major competitors and CPC above £15. Conversion rate on the existing landing page was below 8%, while industry average sits between 8–12%. The £40K monthly budget wasn't generating enough qualified leads to justify scaling.
What I changed
- Full rebuild of landing pages around warm commercial intent (explicit urgency)
- Hourly and postcode bidding — concentrating budget on maximum-CR time slots
- Schema markup for emergency services + click-to-call optimization
- Page speed under 1.5s LCP on mobile (down from over 3s)
- Continuous A/B testing on headline and call-to-action
The result
Conversion rate above 30% on competitive segments — 3–4× the industry average. Budget was increased twice in 6 months while maintaining stable CPL.
Duration · 6 months · Status · Active
03
Services · Education · US
Dance lessons
Initial situation
Dance school chain across four US cities, each with different schedules. Cost-per-lead on Meta Ads exceeded $30, above the client's profitability threshold. Creatives were generic (stock footage), and campaigns ran the same strategy across all four local markets.
What I changed
- Full audit — discovered 60% of spend going to irrelevant placements
- Campaign restructure by geo (4 markets = 4 separate strategies)
- New creative — real footage from each school + short testimonial
- Separate local landing pages with school-specific booking schedules
- Full conversion tracking implementation for the booking funnel
The result
Cost-per-lead reduced by 3× from baseline, without volume reduction. The result enabled doubling the budget on markets with the highest post-lead conversion.
Duration · 90 days · Status · Completed