prudsys RDE | Recommendations

prudsys RDE | Recommendations

The world’s most powerful recommendation engine

The prudsys RDE | Recommendations module personalises sales processes at all customer touchpoints, without manual intervention. The range of solutions covers optimal product recommendations and the personalisation of content in online shops, newsletters, mobiles and stores.

Advantages for you     

Most recommendation engines generate product recommendations that users most likely would have purchased anyway according to their profile. The calculation of recommendations in this case is reduced to a statistical forecast Although this approach functions without a doubt, the question remains as to why recommend something to a user that he would have probably purchased anyway. In contrast, the prudsys RDE learns directly from the recommendations and the calculation takes place via the theory of reinforcement learning. The result is a new grade of recommendation calculation that has become the most powerful approach in this field in the world. 

How it works

The RDE | Recommendations module bases its recommendations on an evaluation of historic transaction data and on realtime learning from the ongoing interaction with users and visitors. It offers numerous different types of recommendations and covers virtually all areas of personalisation application. It is also possible, if needed, and in accordance with data protection guidelines, to incorporate facebook data (posts, likes, check-ins) into the calculation. 

Result

Maximum acceptance of recommendations, increased long-term customer retention and best possible use of sales potential. 

Usage areas

Online
Newsletter/Print
Mobile
Retail Store

Key features

Benefits: 

  • Maximum Increase sales
  • Optimal customer experience
  • Maximum use of cross and up-selling potential
  • No down-buying or topseller problems
  • Fully automatic 'Install-and-Forget' procedure
  • High-value recommendations even for small shopping baskets, in long tail and for new products or content
  • Includes environmental factors (e.g. channel, time, weather)
  • Inclusion of Facebook data (e.g. likes, posts, check-ins) possible

Technology:

Integrated success rate measurement:

  • Support for A/B tests and multivariate tests
  • Many indicators (e.g. clicks, conversion rate, total sales, sales through recommendations) including confidence intervals to estimate their stability

Functions of this Module

category-to-banner

Category to Banner

category-to-categories

Category to Categories

category-to-products

Category to Products

category-to-sorted-productlist

Category to Sorted Product List

category-to-topcategories

Category to Top Categories

category-to-topseller

Category to Topseller

ordered-together-generalized

Ordered Together Generalized

ordered-together

Ordered Together

product-master-variation-to-products

Product (Master/ Variation) to Products

product-to-products

Product to Products

productlist-to-products

Product List to Products

productlist-to-sorted-productlist

Sort Product List

searchterm-to-product

Search Term to Product

searchterm-to-sorted-product-list

Search to Sorted Product List

topcategories

Global Top Categories

topseller

Global Topseller

user-to-banner

User to Banner

user-to-categories

User to Categories

user-to-products

User to Products

user-to-userhistory

Transaction History

Latest press releases

  • 27. September 2016
    Maximization of value across all sales channels with prudsys RDE’s Major Release 3.10.0
    read more

  • 17. August 2016
    Personalization you can touch: prudsys with showroom at the dmexco 2016
    read more

  • 07. July 2016
    Recommended: prudsys personalization summit 2016 meets with great approval among visitors
    read more

  • 04. July 2016
    Using print successfully in the online age: KLiNGEL Group receives “Personalization Award 2016”
    read more

  • 30. June 2016
    UC Davis students win DATA MINING CUP 2016
    read more

Questions?

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