Increase engagement and AOV with real-time personalized recommendations

Predict and curate products for shoppers in session with AI-driven and contextually aware recommendations algorithms, ready-made templates, easy-to-use merchandising controls, and actionable shopper intelligence.

AI-Powered recommendations engine

Transform clicks into conversions with hyper-personalized product suggestions. Guide shoppers to relevant choices and support the discovery of new products at every stage of the purchase funnel.

Personalized for each buyer

Provide 1:1 personalized recommendations with proprietary AI that interprets hundreds of signals to understand shoppers' intent and affinities.

Context-based suggestions

Convert browsers into buyers with recommendations that match shopper cues and interactions.

Real-time shopper understanding

Instantly understand and interpret shopper’s behaviors to generate personalized and engaging recommendations within the same session.

Amplify catalog visibility

Utilize advanced algorithms and data analysis techniques to improve product exposure. Gather data on shopper interactions to identify individual preferences and behaviors.

Self-learning algorithms driven by intelligence

Develop and train recommendation models using historical data. Identify products that appeal to specific shoppers based on their profile and actions.

Shopper interactions

Boost engagement with personalized suggestions that match browsing preferences. Recall recently viewed items for an elevated experience.

Wisdom of the crowd

Suggest related purchases based on buying habits. Elevate sales by recommending products that align with similar preferences.

Top and trending

Showcase popular products and highlight top sellers across categories and brands for an enhanced shopper journey.

Product affinity

Suggest alternatives and cross-sell complementary combos with insightful logic to elevate the shopper experience.

Reach direct to customers

Combat cart abandonment and recover sales. Extend engagement beyond the site and re-engage shoppers with targeted messages.

Email recommendations

Send personalized product recommendations in email to engage shoppers, rekindle interest, and motivate purchases.

App push notifications

Push notifications of relevant products and promotions by leveraging shopper interactions and preferences.  

Fallbacks for cold start

Lack of pre-existing data? Manually configure algorithm-based and product-based fallbacks for superior user engagement and personalization.  

Merchandise Recommendations

Curate personalized product suggestions, fostering engagement and boosting revenue effortlessly.

Mix and match algorithms

Choose any combination of algorithms and decide what shoppers see in each product slot with zero coding effort.

Customize algorithms

Tweak algorithm parameters and create rules to add expertise and business logic to core algorithms.

Use ready-made templates

Choose from a library of customizable UI templates or upload custom-created templates to build business-friendly shopper experiences.

Omnichannel reach

Be it B2B or B2C, show recommendations across all channels, including but not limited to desktop sites, mobile sites, and mobile apps.  

Personalized shopping hub

Provide a social media-like interface with a cross-category selection of products personalized for each customer.  

Reliable infrastructure

Easy and fast feed ingestion

Implement recommendations with the same feed used for search and remove all additional work.

Seamless integration

Configure Unbxd Recommendations for multiple frameworks using APIs, SDKs, and front-end libraries.  

Reports and Insights

Decipher shopper behavior and unearth hidden revenue streams with advanced analytics and comprehensive reports.

Key metrics dashboard

Get critical metrics on recommendations performance and visually compare KPIs to measure the impact of strategies.

Page-level insights

Analyze how the recommendations perform on every page to improve shopping journeys.

Widget-level performance

Measure the performance of each recommendation widget and optimize algorithms and placements to improve conversions.