Sports & Team Merchandise E-Commerce
From $5K to
$25K/Month: Scaling Sports 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.
At $5K/month, the store was profitable with 350-400% ROAS. But they’d tried scaling to $10K twice before — both times ROAS dropped below 200% within weeks.
Classic scaling trap. At $5K, Shopping finds the easy conversions. At $10K+, the algorithm reaches beyond into broader traffic. Without segmentation, extra budget just inflated CPCs on the same queries.
Seasonality made planning harder — revenue concentrates around playoffs, back-to-school, and Q4 holidays. Previous approach: panic-scale during peaks, slash budget in lulls. No evergreen structure.
The feed had auto-generated titles like “Men’s Hoodie – XL – Blue” — no team name, no sport, no league. And Meta was completely untouched despite the category being driven by fan passion and identity.
What We Did
Feed overhaul with team-specific titles
Rewrote titles using [Team Name] + [Product Type] + [Detail] + [Size]. Added custom labels: 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), Catalog (conservative, long-tail), Seasonal Surge (scales 3-4x during peaks), Brand Defense. Each tier with its own ROAS targets matching the economics of those products.
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.
Pre-built seasonal infrastructure
Playoff and holiday campaigns staged in advance. When peaks hit, 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.
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