From $5K to $25K/Month:
Scaling a Sports Merchandise Store
Without Killing ROAS
The Challenge
US-based Shopify store selling sports and team merchandise — jerseys, caps, accessories across dozens of teams and leagues. The catalog had thousands of SKU variants: one hoodie available in 15 teams, 6 sizes, 3 colors = 270 Shopping variants. Multiply by hundreds of products — tens of thousands of active SKUs.
At $5K/month, the store was profitable with 350-400% ROAS. Mostly branded search and a handful of hero products. The problem: they’d tried scaling to $10K twice before. Both times ROAS dropped below 200% within weeks, and they pulled back.
Classic scaling trap. At $5K, Shopping finds the easy conversions — fans searching for specific team gear. At $10K+, the algorithm reaches beyond this core into broader traffic. Without segmentation, the extra budget just inflated CPCs on the same queries while buying low-converting impressions on generic terms.
Seasonality made planning harder. Revenue concentrates around playoffs, back-to-school, and Q4 holidays — 3-4x spikes, then crash to baseline. Previous approach: panic-scale during peaks, slash budget in lulls. No evergreen structure.
The feed was a mess. Auto-generated titles like “Men’s Hoodie – XL – Blue” — no team name, no sport, no league. Google couldn’t match to searches like “Dallas Cowboys hoodie XL.” A $15 cap and $85 jersey shared the same bidding target. And Meta was completely untouched — zero Facebook or Instagram presence for a category driven by fan passion and identity.
What We Did
Feed overhaul with team-specific titles
Rewrote titles using [Team Name] + [Product Type] + [Detail] + [Size]. "Men's Hoodie - XL - Blue" → "Dallas Cowboys Men's Pullover Hoodie — Navy Blue, Size XL." Added custom labels across four dimensions: team popularity, margin tier (A: 40%+, B: 25-40%), seasonal relevance, and performance tier
4-tier campaign structure
Hero Products (top 100 variants, aggressive bids, 50-60% of revenue). Catalog (everything else, conservative, long-tail). Seasonal Surge (playoff teams and holiday bundles, scales 3-4x during peaks then throttles back). Brand Defense
Meta launch from zero
Prospecting with lookalikes from top 5% highest-LTV customers. Creative: lifestyle imagery of fans wearing merch, dynamic product ads by team, carousel collections. Retargeting: site visitors who browsed specific teams but didn't buy, cart abandoners with urgency messaging
Controlled scaling protocol
Budget increased 20-30% per 2-week cycle. Each increment required maintaining previous cycle's ROAS before unlocking the next. If ROAS dipped, held budget and optimized for 2 weeks before trying again. No more "throw money and hope
Pre-built seasonal infrastructure
Playoff and holiday campaigns staged in advance. When peaks hit, we activated existing campaigns instead of building from scratch. Between peaks, maintained evergreen $15K/month baseline instead of crashing to $3-5K
The Results
Previous attempts to scale past $10K crashed. The difference: tiered campaigns, segmented feeds, and a protocol that increased spend only when the math supported it. Meta delivered incremental revenue from Day 1 — within 3 months, ~25% of total revenue came from a channel that didn't exist before. Peak holiday ROAS exceeded 5x — the store's best ever.
Evidence
Ad spend scaling — $5K → $25K/mo with ROAS overlay
Feed titles before/after comparison
Revenue by channel — Google + Meta contribution
“We tried scaling past $10K twice and crashed both times. They built the structure that made $25K work — and we actually make more money per dollar at the higher budget than we did at the lower one.”
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