CASE STUDY · HOME & GARDEN · FIRE PIT SURPLUS
Fire Pit Surplus: 8.6x ROAS on High-Ticket Outdoor Products
Fire Pit Surplus is a US Shopify retailer of high-ticket outdoor fire pits and accessories, where a single sale matters and a wasted click costs real money. The challenge was scaling in a seasonal category without letting efficiency slip. Logical Gecko focused budget on purchase-ready searches, planned spend ahead of the season and held a strict ROAS floor. Between Jan 15 and Aug 26, 2024, the account delivered $220,000 in sales from $25.6K in ad spend: 8.6x ROAS at $188.24 per conversion.
- Sales$220K
- Ad Spend$25.6K
- Conversions136
The client
Fire Pit Surplus
Fire Pit Surplus is a US ecommerce retailer specializing in outdoor fire pits and accessories, with high average order values and strong seasonal demand swings.
- Industry
- Outdoor Fire Pits & Accessories
- Category
- Home & Garden, Fire Pits
- Market
- United States
- Platform
- Shopify + Google Ads
- Period
- Jan 15 to Aug 26, 2024
- Goal
- Scale a seasonal high-ticket catalog profitably
The challenge
High ticket, high seasonality, low margin for error
With few transactions and large order values, the account could not rely on volume-based optimization. Every dollar had to go toward people close to a purchase decision.
- Strong seasonality in outdoor fire pit demand
- High competition from large home improvement retailers
- Limited brand recognition against established players
- Long consideration cycle on high-ticket items
- Low conversion volume for algorithmic learning
- Need to protect profitability while scaling
Our strategy
How we approached the account
Target intent, not traffic
Focused budget on bottom-funnel, purchase-ready queries and excluded research and inspiration traffic.
Work with the season
Adjusted budget and bids ahead of demand curves instead of reacting after the peak had passed.
Protect the margin
Held a strict ROAS floor and grew spend only where profitability was proven at the product level.
What we did
The work behind the numbers
Intent-Led Keyword Strategy
- Bottom-funnel commercial queries prioritized
- Research and DIY queries excluded
- Brand and competitor terms handled separately
- Match types kept tight to protect budget
Seasonal Budget Planning
- Budget ramped ahead of demand peaks
- Off-season spend reduced, not paused
- Dayparting aligned with buying behavior
- Holiday and gifting periods planned in advance
Shopping Feed Optimization
- Titles built around fuel type, size, and material
- High-margin SKUs prioritized
- Clean product types and categories
- Promotions and shipping details surfaced
Audience Targeting
- Homeowner and outdoor living segments
- Remarketing tuned to long consideration cycles
- Cart and product-view audiences prioritized
- Low-intent placements excluded
Creative Testing
- Outdoor living benefit angles tested
- Warranty and shipping trust messaging
- Price and financing messaging tested
- Winning angles rolled across campaigns
Profit Protection
- Strict ROAS floor enforced per campaign
- Product-level profitability monitored
- Spend scaled only on proven SKUs
- Continuous waste audits on search terms
The result
$220K in sales at 8.6x ROAS on $25.6K of spend
Across roughly seven months the account delivered $220,000 in sales from $25.6K in ad spend, an 8.6x return (see our ROAS formula guide for the math) that held steady through seasonal swings.
Before Logical Gecko
- Seasonal demand causing unpredictable results
- Spend leaking into research-stage traffic
- Limited visibility against major retailers
- No product-level profitability view
- Scaling attempts hurting ROAS
After Logical Gecko
- 8.6x ROAS sustained over seven months of scaling
- $220,000 in tracked sales
- Efficient $188.24 cost per conversion on high-ticket items
- Year-round sales instead of peak-only revenue
- Profit-safe framework for future scaling
Key lessons
What other brands can take from this
High-ticket needs intent, not volume
With few conversions, precision targeting matters far more than reach.
Plan seasonality in advance
Ramping budget before the demand curve captured cheaper clicks than reacting at the peak.
A ROAS floor makes scaling safe
A hard efficiency rule allowed confident budget increases without risking profitability.
Feed detail wins Shopping
Descriptive titles with fuel type, size, and material matched the way people actually search.
Keep reading
Related Services and Guides
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