Funding
Funding not disclosed
Founders
Product
Problem
Online retailers often struggle to deliver relevant product recommendations and search results, leading to low conversion rates, reduced average order values, and poor customer loyalty. Traditional static merchandising tools cannot adapt in real time to individual shopper behavior or intent.
Solution
Searchspring’s 4‑Tell platform provides an AI‑driven personalization suite that tailors search results, product recommendations, and merchandising logic to each visitor. The system continuously learns from browsing patterns, order history, and in‑session actions to rank products, suggest bundles, and apply boost rules based on margin, newness, or seasonal priorities. Merchandisers can define segment‑based targeting while the engine dynamically adjusts offers for one‑to‑one experiences without manual intervention. All personalization is delivered through a cloud service that integrates with existing e‑commerce sites via APIs and front‑end widgets, enabling retailers to increase conversion, average order value, and repeat visits.
Target Audience
Primary customers are mid‑size to large e‑commerce retailers and brands that need scalable, data‑driven personalization to improve site conversion and customer lifetime value.
Features
- AI‑powered personalized search that ranks items based on real‑time shopper behavior
- Real‑time product recommendation engine (Athos) with boost rules for strategic criteria such as margin or newness
- Dynamic custom profiles that adjust recommendations using live signals like filter selections and search terms
- Predictive product bundling and segment‑driven targeting that merge one‑to‑one personalization with audience segmentation
- Cloud‑based analytics and merchandising dashboard for monitoring performance and fine‑tuning logic
- Easy integration via APIs and front‑end widgets compatible with major e‑commerce platforms