Scaling past the efficiency ceiling
A founder-run e-commerce brand selling digital products had built a profitable Meta advertising operation at around $50,000 per month.
But every time they tried to scale beyond that, efficiency collapsed. They'd increase budgets, ROAS would drop, and they'd pull back. The founder understood their seasonality and adjusted spend accordingly—but couldn't break through the ceiling profitably.
The client wasn't looking for someone to take over their account. They wanted to understand why they couldn't scale, and learn how to fix it themselves.
The Goal
Identify what was blocking profitable scale—and build the client's capability to break through it themselves.
The Strategy
This was a coaching engagement, not a managed service. Six sessions over two months, working backward from the scaling problem to identify root causes.
The diagnostic surfaced several structural issues that were capping growth.
Campaign Architecture. The account had grown organically, with campaigns added as new products launched. This fragmentation meant the algorithm was optimizing across too many small ad sets, none of which had enough conversion volume to exit learning phase efficiently. The question: should campaigns be consolidated or separated by product category? The recommendation: consolidate by category using CBO, giving the algorithm clearer signals while making performance diagnosis easier.
Bidding Strategy. The client had been running max conversions bidding, which spent the full daily budget regardless of efficiency. When they scaled up, the algorithm just spent more—even when acquisition costs spiked. This explained why ROAS collapsed at higher spend levels. Cost caps would solve this—automatically reducing spend when acquisition costs exceeded the target, then scaling back up when efficiency returned.
Audience Strategy. The client had been running interest targeting for years and wasn't sure if there was room to expand. We designed a testing roadmap: LALs versus interests first, then LAL percentage testing (1% vs. 3% vs. 5%), with Advantage+ as a third option. Broader audiences could unlock scale—but only if tested methodically with clear success criteria.
Creative Testing Framework. Scaling also meant the client would need to test new creative concepts without disrupting campaigns that were already working. We designed an A/B split test structure that isolated creative variables while protecting proven performers—a repeatable process they could run independently.
The Tactics
The client implemented the recommendations between sessions.
Restructured campaigns with cost cap bidding. Instead of max conversions CBOs that would spend the full budget regardless of efficiency, the new structure used cost caps that automatically throttled spend when acquisition costs rose. This proved critical during a major competitive period when ad inventory was flooded—the campaigns simply spent less rather than burning through budget inefficiently, then resumed normal spend when conditions improved.
Ran the audience testing sequence. LAL audiences built from recent purchasers outperformed interest targeting. The 1% LAL became the primary audience, with Advantage+ running as a parallel test.
Built the creative testing protocol. New concepts launch in isolated ad sets, compete against proven creative types, and graduate to the main campaign if they hit benchmarks.