Recommendation Systems
Deliver what your users want—before they even ask. We build, deploy, and monitor recommendation engines that drive sales, engagement, and loyalty.
Get a Free ConsultationWhy Invest in Recommendation Systems?
Recommendation engines power the world’s top retailers, media sites, and apps. Whether you want to boost conversions, cross-sell, personalize feeds, or surface new content, we design custom models that turn your data into measurable growth.
Delight your users, lift KPIs, and future-proof your product—with tailored rec systems, not just generic plug-ins.
Where Recommendation Delivers Value
E-commerce Product Suggestions
Show “You might also like” products—driving higher cart values and repeat purchases.
Example: An online retailer implements cross-sell and upsell engines, increasing average order size and customer satisfaction.
Content & Feed Personalization
Curate news, articles, or media for each user—raising engagement and session time.
Example: A news platform personalizes article feeds for every reader, driving more visits and ad revenue.
CRM & Cross-sell/Upsell
Serve the right offer at the right time—on your website, app, or inside your CRM workflow.
Example: A telecom company boosts upsell acceptance with a “next best offer” model, tuned to each customer’s profile.
Hybrid & Advanced Recommendations
Blend user behavior, item features, and business goals—unlocking smarter recs for cold start and fairness challenges.
Example: A streaming service blends collaborative and content-based models, surfacing more diverse recommendations for new users.
Our Recommendation System Process
- Free Discovery Call: Tell us your goal and sample data. We’ll share options, examples, and honest pricing—no obligation.
- Data Profiling & Health Check: We assess your user, item, and interaction data—flagging gaps, cold start, or bias risks.
- Model Design & Development: We select, build, and validate the best rec model—collaborative, content-based, hybrid, or deep learning.
- Deployment & Integration: Get live APIs, UI modules, or batch jobs—plus docs and support for integration and monitoring.
- Optional Ongoing Tuning: We offer quarterly tuning, A/B testing, and monitoring to keep your recs accurate as your business grows.
What You Need to Get Started
- Clear recommendation goal (products, content, offers, etc.)
- User, item, and interaction data (≥1,000 examples is ideal)
- Features for users/items (for hybrid modeling)
- Willingness to sign a mutual NDA (your data and models are protected)
Not sure if you have enough data? Most teams can start faster than they expect—book a free consult and get clarity.
Starter Pricing
- Pre-consult & Discovery: Free
- Typical recommendation system project: $3,500 – $8,000
Contact us for a custom quote—every recommender is tailored for your data, goals, and audience.