SEOJetty implemented an AI-driven recommendation engine for a US DTC fashion brand, resolving low retention. Within 12 months, we successfully doubled repeat purchase rates and increased Customer Lifetime Value (CLV).
A US-based mid-market DTC fashion e-commerce brand (20-100 employees) selling contemporary apparel and seasonal collections.
The brand struggled with high one-time buyer volume, inefficient inventory forecasting, generic product recommendations, and a CLV lagging below industry benchmarks.
Double repeat purchase rates and significantly increase CLV within 12 months using personalized AI recommendations.
We transitioned the brand from manual merchandising to a predictive AI model. Rationale: AI instantly captures fast-moving seasonal trends and matches personal style preferences, turning costly one-time buyers into high-LTV loyalists.
Success was measured via repeat purchase rate tracking, CLV analysis, email revenue attribution, and inventory turn optimization. (Limitation: Multi-device browsing slightly fragmented exact email attribution).
Shifting from generic seasonal email blasts to size-personalized, dynamic new arrival alerts dramatically spiked repeat conversions.
Expand the AI recommendation engine into automated SMS campaigns over the next 90 days.
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