Recommendation platform with AWS Personalize for

Improve e-commerce sales success rate through the most appropriate recommendation system for your business model.

Clothing, entertainment, food, books, cosmetics, toys, electronics… 

85% of users buy online, this translates into several billion potential customers worldwide. 

But retailers face certain challenges that ultimately lead to two key objectives needed for success:

Increased sales volume 

Increased rate of spending per visit

The ability to match products and customers consists of two main variables:

Product affinity

The affinity of the product to the preference and interest of the customer.

Predisposition to purchase

Act at the precise moment when the customer is most likely to buy.

It is necessary to impact with the most appropriate product at the most appropriate time for a conversion.

The precision in the combination of these variables will also reduce one of the most worrying ratios for retailers: abandoned shopping carts, what means: sales processes that have not yet been concluded.

The solution involves a recommendation platform that uses AWS Personalize and combines:

A solution by Keepler

Product information

Customer information


With this information, we can make an impact on the key moments of the vendor-customer relationship:

Real time recommendation systems on web.
Batch recommendation systems in email marketing.

An e-commerce recommendation platform developed by Keepler is not a standardized service, but offers a differencial value compared to other solutions.

It reduces the time to deploy a recommendation platform based on AWS Personalize by up to 5 weeks of development. 

And it uses a system of ready-made pipelines to test different models and parameter settings and find the recommendation model that best fits your business model

Deploy AWS Personalize


Time reduction compared to a development from scratch

At Keepler, we build your custom recommendation system to improve the e-commerce sales success rates of your business model.

Contact us and let’s talk.

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