From flat to flying: how we doubled revenue and cut wasted ad spend in half.
"We didn't just improve their ads. We changed what the numbers meant — turning one-time buyers into a repeatable revenue engine."— Marketa
A mission-driven snack brand with a loyal following was stuck. Their eCommerce presence wasn't reflecting the quality of the product — listings were underoptimized, ad spend was inefficient, and repeat purchase behavior was going untracked and unlevered. They were getting traffic. They just weren't converting it, and they had no clear picture of what a customer was actually worth over time.
ROAS was sitting at 2.3. Good enough to keep running ads. Not good enough to scale.
Without a clear model for customer lifetime value, every acquisition decision was being made blind. The brand had the product, the community, and the mission. What they needed was a foundation — and then a plan to build on it.
The audit revealed a pattern we see often: a brand that had been running ads long enough to accumulate spend habits — but not long enough to question them. Campaigns had grown organically, with no coherent architecture underneath. Bids were set to win impressions, not revenue.
Listings were written for the brand, not for the buyer. A+ content existed but wasn't doing the conversion work it should. And without any LTV model, the brand had no way to know how much it could afford to spend to acquire a customer — which meant every growth decision was being made blind.
The result: a 2.3 ROAS that felt stable but was quietly capping the brand's ceiling.
We overhauled their A+ content — rewriting listings with search-intent copy, restructuring imagery hierarchy, and aligning every PDP with how their actual customers talked about the product in reviews. The listings started working harder without spending more.
Campaigns were consolidated, bid strategies were rebuilt around profitability targets rather than visibility, and we implemented AI-driven optimization to keep ROAS climbing without requiring constant manual adjustment. Every dollar of spend was now pointed at outcomes.
We layered in demand forecasting — making sure inventory levels matched the momentum we were building so stockouts didn't bleed the rankings we were earning. Growth doesn't mean anything if you run out of stock the moment it starts working.
We built out Subscribe & Save optimization, modeled customer lifetime value at $816 per repeat buyer, and tracked repeat purchase behavior for the first time. The brand stopped thinking in acquisitions and started thinking in relationships.
* Jan–Jul period. Revenue in USD.
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