US Home & Lifestyle Brand: 5.2x ROAS Scaling to $120K Monthly Ad Spend
A US-based home & lifestyle DTC brand spending $40K/month on Google and Meta Ads with a 1.9x ROAS, far below their 3.5x profitability threshold, due to structural campaign issues, untested creative, and critical attribution gaps.
Published: April 2026 · Timeframe: 3 months
Company Overview
- Industry
- E-Commerce / Home & Lifestyle
- Campaign Duration
- 3 months
- Primary Service
- Performance Marketing
- Type
- High-Growth DTC Home & Lifestyle Brand
- Status
- Active Client
The Challenge
The client had a product the market wanted, strong organic demand, repeat purchase rates above category average, but their paid media programme was haemorrhaging money. At $40K/month spend and 1.9x blended ROAS, they were generating less revenue than they spent on ads. The business needed paid media to become profitable before scaling further.
- Blended ROAS of 1.9x against a 3.5x profitability threshold, every ad dollar generating a loss
- Google Ads structured as a single broad campaign with no Search/Shopping/PMax separation
- Meta attribution broken after iOS 14, no Conversions API, 45% of conversions invisible
- 120+ ad creative variations in the account but no systematic testing framework
- Smart Bidding optimising against corrupted conversion data, self-reinforcing poor performance
- No first-party audience strategy, CRM data not uploaded to either Google or Meta
Our Solution
Phase 1: Attribution & Measurement Foundation (Week 1)
Every subsequent optimisation decision depends on accurate data. We fixed measurement before touching any live campaigns.
Google Ads Conversion Tracking Rebuild
Audited the existing Google Ads conversion tracking and found duplicate conversion actions firing, inflating reported conversions by 34%. Rebuilt from scratch using GTM data layer events triggered on confirmed order completion. Implemented Enhanced Conversions to recover identity-matched conversion data on logged-in Google users.
Meta CAPI Implementation
Implemented server-side Meta Conversions API with event deduplication. Recovered 45% of previously unattributed mobile conversions, immediately improving Smart Bidding quality signals on Meta. Event Match Quality score improved from 3.1 to 8.4.
First-Party Audience Upload
Uploaded 3 CRM customer lists to both Google and Meta: all-time purchasers, high-LTV purchasers (top 20%), and lapsed customers (no purchase in 120+ days). These seed lists became the foundation for lookalike audiences and RLSA targeting.
Phase 2: Google Ads Architecture Rebuild (Weeks 1–3)
With clean measurement in place, we rebuilt the Google Ads account into a structured Search + Shopping + Performance Max architecture with separate bidding strategies per campaign type.
Search Campaign Restructure
Rebuilt Search campaigns with single-theme ad groups (5–8 keywords max), eliminating the broad match waste consuming 38% of budget on irrelevant queries. Built a 400-term negative keyword library. Average CPC dropped 31% within 2 weeks of restructure.
Shopping + Performance Max Architecture
Rebuilt the Google Merchant Center feed with optimised product titles, custom labels for margin tiers, and corrected GTIN data. Launched Performance Max with 6 asset groups segmented by product category. PMax achieved 4.8x ROAS in the first 30 days.
Smart Bidding Calibration
Graduated campaigns from Max Conversions to Target ROAS once each campaign accumulated 30+ clean conversions. Set initial ROAS targets at 80% of actual performance (conservative) and stepped up 10% every 2 weeks. Prevented learning phase resets by never adjusting budget or bids by more than 15% in a 7-day window.
Phase 3: Meta Rebuild & Creative Scale (Months 1–3)
In parallel with the Google rebuild, we restructured Meta campaigns and built the creative testing infrastructure needed to scale.
Meta Campaign Architecture
Rebuilt Meta into 3 campaign types: Advantage+ Shopping (new customer acquisition), Dynamic Product Ads (retargeting), and a manual BOF campaign for high-value audiences. Clear budget allocation with ROAS targets per campaign type.
Creative Testing at Scale
Launched a structured creative testing programme, 8 new ad variations per week across 4 formats. Testing framework had clear hypothesis, statistical significance threshold (95%), and a winner-loser protocol. Of 120 tests run over 10 weeks, 31 winners were identified and scaled.
Budget Scaling Protocol
Once the account achieved consistent 4.5x+ ROAS for 3 consecutive weeks, we implemented a controlled scaling protocol: 15% budget increase per week, alternating between Google and Meta. Scaled from $40K to $120K/month in 10 weeks without ROAS dropping below 5x.
Results & Impact
Up from 1.9x at engagement start. Maintained above 5x through the $120K/month scaling phase, demonstrating sustainable efficiency, not one-off spikes.
Blended cost per acquisition dropped 58% through attribution fixes, audience improvements, and a Creative Testing programme reducing CPCs and improving conversion rates simultaneously.
From $40K/month at engagement start to $120K/month at month three, a 3x spend increase while ROAS improved from 1.9x to 5.2x.
Google Performance Max became the top-performing individual campaign with a consistent 4.8x ROAS across the 3-month period.
"DigiBlazon's performance marketing team transformed our paid media from a cost center into our highest-ROI growth channel. Going from 1.9x to 5.2x ROAS while tripling our spend was something we didn't believe was possible, they made it happen in 90 days."
Sarah Mitchell
VP of Growth, US Home & Lifestyle Ecommerce Brand
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