Product Recommendations
Drive AOV across touchpoints.
Power recommendations on home page, PDP, cart, checkout, and post-purchase emails based on behavior and similarity.
Analytics Solution
Deliver personalized suggestions at scale. DASTATS Recommendation Engine helps you show the right product, content, or offer to the right person at the right time— across web, app, and campaigns.
A recommendation engine analyzes behavior, preferences, and context to suggest products, content, or actions that a user is most likely to engage with next.
DASTATS Recommendation Engine uses collaborative filtering, content-based methods, and hybrid models to power experiences like “You may also like”, “Frequently bought together”, and “Recommended for you”.
Drive AOV across touchpoints.
Power recommendations on home page, PDP, cart, checkout, and post-purchase emails based on behavior and similarity.
Not just for e-commerce.
Recommend blogs, videos, learning content, or offers that match user interest and journey stage.
React to what users do now.
Adjust suggestions based on clicks, views, and add-to-carts happening in the same session.
Use the right model.
Combine collaborative filtering (similar users), content-based (similar items), and rules-based overrides to match your use case.
Keep control over the output.
Enforce rules like margin thresholds, stock levels, category priorities, and exclusions for certain SKUs.
Prove impact.
A/B test recommendation strategies and track incremental lift in AOV, CTR, and conversion.
Increase basket size with relevant upsell and cross-sell suggestions.
Give each visitor a curated view instead of generic product lists.
Make it easier for users to discover what they’re most likely to buy or watch.
Keep users coming back with fresh, personalized content or product feeds.
Respect margin, stock, and brand rules inside the recommendation logic.
Prove uplift through controlled tests and clear reporting.
From catalog and behavior data to live, personalized suggestions.
Prepare product/content catalog with attributes, tags, and clean IDs.
Track views, clicks, carts, purchases, and content events.
Choose and tune algorithms and business rules for your use cases.
Deploy recommendations to UI and campaigns, then A/B test impact.
Increase AOV, conversion, and repeat purchases with tailored product flows.
Keep users engaged longer with relevant content queues and playlists.
Recommend features, plans, or resources based on behavior and profile.
Suggest next lessons, courses, or paths based on skill and progress.
We’ll help you design and deploy a recommendation engine tailored to your stack.
