Recommendation Engine Development
A recommendation engine suggests the products, content or courses each user is most likely to want, based on their behaviour and similar users. We build recommendation systems for online stores, media platforms and learning apps, and measure the effect with A/B tests.
Good recommendations balance relevance with variety and business goals such as stock levels and margins. We start with proven methods, handle new users and new products sensibly, and prove the uplift with controlled tests.
What we offer
- Product recommendationsRelated items, frequently bought together and personalised picks.
- Content recommendationsArticles, videos or courses for each user.
- Search personalisationRe-rank search results for each user.
- Email and pushPersonalised suggestions in campaigns.
- A/B testingMeasure the real impact on sales or engagement.
Common use cases
- eCommerce cross-sell and upsell
- Course suggestions in an LMS
- Article recommendations for publishers
- Property suggestions on real estate portals
Technology
- Python
- Implicit / LightFM
- Vector databases
- Redis
- AWS Personalize
- Shopify / WooCommerce integration
Business benefits
- Higher order valueswith relevant cross-sells and upsells
- More engagementwith personalised content and products
- Better discoveryof long-tail products
- Personalised emails and notificationsthat people actually click
Why work with Webtech Evolution
- 10+ years of delivery272+ projects for 118+ clients in 12+ countries since 2014.
- One team, end to enddesign, front end, back end, mobile, QA and DevOps under one roof, so nothing gets lost between vendors.
- Clear estimatesa written scope, timeline and price before work starts, and demos throughout the build.
- You own everythingcode, designs and documentation are handed over in full and covered by an NDA.
- Working hours that overlap with yoursMonday to Friday, 10:00–19:00 IST, with extended hours available for clients in the USA, Canada and New Zealand.
How we deliver
Discovery
agree the goal, users, data and how success will be measured.
Prototype
a working version on real examples within the first weeks.
Build and integrate
connect to your systems, add security, testing and monitoring.
Pilot
launch to a small group, measure results and improve.
Scale and support
roll out widely, with ongoing monitoring and updates.
Need people rather than a project? Hire AI developers.
Frequently asked questions
Simple rules and content-based methods work from day one. Personalised models improve as you collect more browsing and purchase data.
Yes. We integrate recommendations into Shopify, WooCommerce, Magento and custom stores.
We run A/B tests comparing recommendations against your current approach and report the difference.
Simple rules and content-based recommendations work from day one; collaborative filtering improves as you collect browsing and purchase history.
Yes. We use popular items, product similarity and context such as category and location until we learn more about the visitor.
Yes, through their APIs, or into custom stores and apps.
Let's Talk!
Have a question about Recommendation Engine Development? Send us a message and our team will reply with next steps.
- Reply within a few hours (Mon–Fri)
- NDA available
- You own the code
Prefer to talk? Call +91-9601965456WhatsApp ushello@webtech-evolution.com
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