Year 1: The client wanted revenue growth, but the account was structurally broken—46 overlapping campaigns, unreliable tracking, unoptimized feeds, and no platform diversification. Foundation problems couldn't be optimized away; they had to be rebuilt first.
Year 2: New management added a constraint: prove efficiency before scaling. Market headwinds and AOV compression made validation critical. The question shifted from "How do we grow?" to "What does the data tell us to do?"
I consolidated the scattered campaigns into 6 tightly focused ones, rebuilt conversion tracking from scratch, and optimized the product feed with critical data signals. While Google was being refined, we launched on Bing Ads as a diversification hedge.
Within three months, revenue growth accelerated. High-margin products showed even stronger performance. The efficiency metrics were solid (blended ROAS improved to approximately 9.1x). By year-end, the account ran on a clean structure with reliable data and optimized feeds.
The foundation was built.
In early 2025, new management arrived with a different question: "Before we scale aggressively, which channels and products deliver the most value per pound spent?"
This constraint became the insight generator. Instead of "How do we grow revenue?" we asked "Where is our true competitive advantage?"
Together with management, I proposed a conservative testing phase: start with careful budget allocation (approximately £500 per day, ramping gradually) and use it to answer which products were genuinely efficient.
Q1 and Q2 revealed the answer decisively.
Core product categories delivered 11.8x to 12.9x ROAS. Everything else: 2x to 4x ROAS.
The company's competitive advantage sat in one product category, not spread across many. Most portfolio managers would diversify for safety. New management asked: "What does the data tell us to do?"
Starting in Q2, we realigned budget dramatically. By Q3, approximately 80-85% of spend went to core products. Secondary categories received just enough budget to monitor and test. Monthly budgets increased from conservative early-year levels , reaching peak efficiency in October.
This wasn't aggression for aggression's sake. This was following the data to its natural conclusion within the framework the business set: prove efficiency first, scale confidently later.
Year 1 to Year 2 comparison:
On paper, this looks like a trade-off. But it misses what actually happened.
Three factors shaped these numbers simultaneously. First: market headwinds. UK construction materials faced slowdown in 2025. Second: AOV compression of approximately 3% suppressed revenue across all channels. Third—and critically—new management's strategic constraint meant we deliberately ran conservatively in H1 to validate the data before aggressive scaling.
Aluminium Warehouse's two-year journey shows what's possible when the business brings strategic goals and you bring analytical frameworks, working together to shape an approach the data validates.
Efficiency rose 83%. Revenue fell 7%. The first number is the one that scales.
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