Case Study: Scaling a London Sewing Supplier to 20x ROAS

Inheriting the "Messy" Middle

In July 2023, we took over a Google Ads account for a London-based sewing and dressmaking supplier. On paper, the business was doing "okay," but the account structure was a classic example of what we call the "Messy Middle." It suffered from fragmented campaign architecture, over-reliance on Broad Match without a negative environment, and zero distinction between high-margin "hero" products and low-margin "clearance" stock.

The primary objective was simple but technically demanding: transform a scattered web of campaigns into a high-efficiency profit engine that could scale without eroding contribution margins.

Technical Truth: Most "okay" accounts aren't failing because of bad products; they're failing because their account structure is so convoluted that Google's algorithm spends 80% of the budget on the wrong search intent.

The Transformation: Engineering a 20.85 ROAS

By shifting the focus from "Revenue" to Incremental Profit, we achieved results that placed this account in the top 1% of global performance benchmarks for the e-commerce sector.

| Metric | Performance | vs. Industry Benchmark | | :--- | :--- | :--- | | ROAS | 20.85 | +626% | | Conversion Rate | 10.18% | +192% | | Average CTR | 9.19% | +43% | | Average CPC | £0.26 | -60% | | Net Profit (Ad-Driven) | £642,268 | -- |

Strategic Pillar 1: Semantic Campaign Sculpting

We rebuilt the account using a Performance-Based Segmentation strategy. Instead of grouping products by "category" (which is what Google suggests), we grouped them by their economic value to the business:

• Hero Campaigns: Reserved for products with high margins and high conversion rates. These were given premium budget and aggressive bid targets.
• Sidekick Campaigns: Solid, reliable performers that provide the account's baseline volume.
• Villain Campaigns: Previously underperforming products that were "sculpted" to only appear for exact-match, high-intent searches, turning them from loss-makers into profit-drivers.

Caption: A technical visualization of the 'Hero/Sidekick/Villain' segmentation model used to maximize contribution margin.

Strategic Pillar 2: Intent-Priority Funnels in Shopping

Instead of a single, flat Shopping campaign, we implemented an Intent-Priority Funnel. This uses Google’s campaign priorities (High, Medium, Low) and negative keywords to force search queries into the correct bucket:

1. Generic Bucket: Captures broad searches (e.g., "sewing machine") at low bids.
2. Brand Bucket: Captures brand-specific searches (e.g., "Bernina sewing machine") at medium bids.
3. Model-Specific Bucket: Captures high-intent, bottom-funnel model codes (e.g., "Bernina 770 Plus price") at the highest bids.

Strategic Pillar 3: Performance Max as a "Retargeting Wrapper"

We used Performance Max not as a catch-all, but as a specialized tool for retargeting and cross-network discovery. By feeding PMax only our highest-performing audience signals and margin-rich product data, we achieved a standalone 31.85 ROAS on retargeting efforts.

Technical Implementation: Replicating This Success

To achieve a 20x ROAS, the following technical steps were non-negotiable:

1. Server-Side Tracking: We implemented server-side GTM to bypass cookie restrictions and ensure a 1:1 match between orders and ad data.
2. Margin-Based Data Feeds: We modified the GMC feed to include a custom_label for margin tiers, allowing us to bid differently for a £50 item with a 50% margin vs. a £50 item with a 10% margin.
3. Bid Caps on PMax: We applied portfolio bid strategies with max CPC caps to prevent the algorithm from over-bidding on "easy" brand conversions.
4. Negative Keyword Sculpting: We deployed a script that automatically adds search terms to a "Negatives" list if they exceed a certain spend threshold without a conversion.

High-Value Consultation: The Bottom Line

A 20x ROAS isn't a "lucky break." It is the result of structural discipline and a refusal to follow Google’s "automated" advice blindly. By treating the account as a financial instrument rather than a marketing platform, we turned a London sewing supplier into a market-leading profit machine.