Brand Niche: Home Improvement
Total Ad Spend: ~$2,500
Total Revenue Generated: ~$12,200
Average ROAS: ~4.9x
Market: United States
Primary Channel: Meta Ads (Facebook & Instagram)
This case study showcases how a data-driven Meta Ads strategy was used to grow a US-based home improvement brand, focusing on controlled testing, efficient scaling, and consistent return on ad spend.
The objective was to validate audiences and creatives quickly, scale winning campaigns, and maintain profitability in a competitive US market.
My Role & Scope
Meta Ads Campaign Structure
Built and managed clearly segmented campaigns for:
Top-of-Funnel (TOF)
Lookalike (LAL) Testing
Audience Testing
Creative Testing
Mid-Funnel (MOF) support
Used CBO and testing frameworks to identify scalable opportunities
Creative & Copy Testing
Ran dedicated creative testing campaigns to identify high-performing angles
Tested multiple ad copies, hooks, and formats tailored to the home improvement audience
Scaled winning creatives while controlling frequency and fatigue
Audience & Funnel Optimization
Tested cold audiences and lookalikes to find efficient acquisition segments
Leveraged funnel-based targeting to improve conversion quality
Ensured strong alignment between ad intent and user journey
Budget Control & Scaling
Allocated spend based on performance signals, not assumptions
Scaled budgets only after ROAS stability was confirmed
Controlled spend during testing phases to protect efficiency
Conversion Tracking & Data Reliability
Ensured accurate Meta Pixel and purchase event tracking
Relied on clean data to evaluate ROAS, CTR, CPC, and conversion value
Used performance metrics to guide scaling and optimization decisions
Strategic Approach
My approach for this brand focused on:
Structured testing before aggressive scaling
Letting data validate audiences and creatives
Maintaining profitability while expanding reach
Treating Meta Ads as a conversion system, not just a traffic source
Key Outcomes
Generated $12K+ in revenue from ~$2.5K ad spend
Maintained a strong ~4.9x ROAS across multiple campaigns
Identified scalable audiences and creative directions
Built a repeatable Meta Ads framework for continued growth