Case Study
Sofalistic is an innovative online marketplace specialising in pre-loved sofas, connecting buyers and sellers in a marketplace model, offering fast collection and secure payments.
See how we helped Sofalistic launch and scale to over $400,000 per month
When Sofalistic approached us, they had already attempted Google Shopping campaigns but faced several key challenges:
Dual audience dynamics: Understanding marketplace dynamics and balancing acquisition of buyers and sellers
Unknown metrics: No established Average Order Value (AOV) or conversion patterns
Dynamic inventory: Hundreds of new products added daily
Limited brand awareness: New brand requiring market presence
Our first step involved establishing a comprehensive financial and measurement foundation:
Pre launch Analysis: Keyword research, Competitor research, Cost structure
Breakeven calculations: Determined target Cost Per Acquisition (CPA) and Return on Ad Spend (ROAS) thresholds based on financials to maintain oversight of blended acquisition costs and listing sales across brand and performance campaigns
Custom dashboard development: Built specialised tracking for marketing costs, variable expenses, and fixed overheads aligned with their specific financial KPIs
Tracking setup: Implemented comprehensive checkout funnel analysis to optimise abandonment points in funnel
Sign-up flow optimisation: Streamlined user onboarding for both buyers and sellers through Klaviyo
Initial Setup (tCPA to tROAS Evolution): Given the unknown AOV for this new brand, we launched with Target Cost Per Acquisition (tCPA) bidding to establish baseline performance metrics. Once AOV was established, we transitioned to tROAS bidding whilst closely monitoring conversion rates, listings & closed rates.
Feed Optimisation Strategy: The dynamic nature of marketplace inventory required a sophisticated feed management approach:
Automated product rules: Created segmentation by brand, condition, and key attributes
Quality control protocols: Implemented listing standards to maintain feed quality despite rapid inventory turnover - focusing on the listing process rather than individual product optimisation
Enhanced product data: Advised on adding crucial search-driven attributes including: Number of seats, Dimensions, Colour, Condition
Datafeedwatch: Moved to a feed provider that would allow for proper feed customisation and rules
Search Campaign Development: We adopted a layered approach to campaign expansion, only starting with certain campaign types after others due to budget and campaign constraints.
Shopping foundation, PMAX integration: Started with Shopping campaigns to gain search term visibility and capture BOFU queries first. Layered in PMAX once we had established awareness of high-converting search terms, given PMAX's limited visibility on search query data
Buyer-focused Search campaigns: Expanded into high-intent buyer terms, then broadened to retailer brands and wider categories
Seller-focused Search campaigns: Targeted seller-specific terms like 'sell my sofa' and related variations
Keyword organisation: Started with exact, scaled out to phrase, and used broad match only on high-intent keywords grouped by semantic similarity, with strategic use of negatives
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Initial Chat
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Account Audit and Analysis
I’ll review your ad accounts, tracking setup, and website to put together a strategy on how I can add value.
Review Strategy
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