RecommendTM is a powerful ecommerce product recommendations engine that utilizes machine-learning to select the most relevant, data-driven personalized product recommendations for each customer interaction. RichRelevance customers enjoy significant conversion rate improvements and revenue uplift through deploying the RecommendTM ecommerce product recommendations solution.
UNIQUE TO RICHRELEVANCE
BEHAVIORAL DECISIONING
Our patented technology identifies which of our 125+ pre-built recommendation algorithms is most impactful for each customer interaction.
BUILD YOUR OWN RECOMMENDATIONS
Leverage your customer expertise to build algorithms with exact blend of data or strategies that perform best for your unique goals.
CUSTOMER PREFERENCE CENTER
Empower your customers to specify their category, brand, and product preferences and use that data to tailor their experiences.
ADVANCED MERCHANDISING
Build ensemble recommendations to cross-sell and upsell by leveraging product attribute and compatibility data.
DASHBOARD REPORTS
Gauge effectiveness and performance for each product and its respective category relationship with multi-KPI based reporting.
MERCHANDISING RULES
Designed with retail and brand merchandisers in-mind, our rule engine offers a fine balance between auto-optimization and manual merchandising.
Powerful Personalization
Recommend™ is a powerful ecommerce product recommendations engine equipped with the most merchandiser ready set of optimization tools and configurations in the market. Recommend™ combines the power of ensemble learning with 125+ algorithms that learn and respond in real-time to individual customer behaviors, affinities and activity, resulting in highly personalized product recommendations for ecommerce providers.
RELEVANCE IN ACTION
The Book People Case Study
Find out how Book People created highly innovative, engaging and personalized experiences for their customers while also leading to improved ecommerce conversion rates.
Additional Resources
How to Get Shoppers to Log In
WEBINAR
Learn tips on how to get your shoppers to log in by demonstrating the value of a more individualized experience.
5 Types of User Matching Challenges
WHITE PAPER
This paper shares how you can leverage user ID matching and RichRelevance features to identify users and motivate shoppers to log in.
Homebase Utilize More Data
CASE STUDY
Homebase works with RichRelevance to optimize their website experience and guide customer conversion.