Overview - Predictive Segmentation Using Amazon Pinpoint and Amazon SageMaker


Given the ever-increasing number of brands competing for a finite amount of customer attention, maximizing customer engagement is vital. In today’s digital marketplace, it is critical to keep your users coming back to your applications and products.

One method that can help improve customer engagement is to deliver personalized messages to your users based on attributes, activity, and stages in the customer journey. Personalized messaging can help solidify the relationship between your brand and your customers, increasing loyalty and conversion rates. Amazon Pinpoint helps you engage with your customers by sending personalized emails, SMS and voice messages, and push notifications. With Amazon Pinpoint, you can place your customers in segments based on demographics, behaviors, or other key performance indicators that are important for your business, and send personalized, timely, and relevant messages to those groups.

Machine learning (ML) can also help you improve your customer engagement by analyzing your customer activity, identifying patterns, and making recommendations to help you convert users. However, it can be a challenge to integrate ML models with messaging tools for companies without deep, in-house ML expertise.

To help you more easily combine segmentation in Amazon Pinpoint and machine learning, AWS offers the Predictive Segmentation Using Amazon Pinpoint and Amazon SageMaker solution. This solution combines Amazon Pinpoint with Amazon SageMaker, an ML service that enables you to build, train, and deploy machine learning models quickly.

With this solution, you can easily build an architecture that automates the collection of customer data, predicts customer churn using ML, and maintains a tailored audience segment for messaging.

This solution includes an example dataset you can use as a reference to develop your own custom ML models with your own data. For more information, see the appendix.


You are responsible for the cost of the AWS services used while running this reference deployment. As of the date of publication, the cost for running this solution with default settings in the US East (N. Virginia) Region is approximately $140 per month. This cost estimate assumes 100,000 customer endpoints stored in Amazon Pinpoint with 1 GB of other customer data in Amazon Simple Storage Service. Prices are subject to change. For full details, see the pricing webpage for each AWS service you will be using in this solution.