Cloud Computing

Predicting Customer Churn Using Salesforce Data and AWS Services

We're living in the Age of the Customer, in which customers expect personalized service. Customer retention is a major issue for various service-based organizations. Retaining our existing customers or at least reducing customers' churn rate should be easier than acquiring those customers.Reducing churn is extremely important in competitive markets since acquiring new customers in such markets is very difficult. Identifying customer behaviour and discovering hidden insights and patterns in Salesforce CRM databases, which typically contain thousands or millions of customers’ information, is a challenging and difficult task. 

Companies can successfully generate business value from their data. A prediction is a forward-looking estimate based on historical data. Today, businesses are using

artificial intelligence (AI) and machine learning to generate predictions and embed those in their

business workflows. We have developed Predictive models for observing the behavior of customers are one of the great instruments in the customer retention process and inferring the future behavior of the customers from Salesforce CRM. We will extract data from Salesforce CRM ang bring it into AWS S3 using Amazon connect. We prepared and transformed data using Amazon Glue to key it into machine learning algorithms. We have used Amazon SageMaker to build, train, and deploy high-quality machine learning models and push the result to Salesforce CRM for further review of the Sales team and recommend the best action, offer, or engagement.

Listed below few benefits of using this solution

• Identifying the negative customer experience trends and reducing attrition levels
• Churn Prediction Can Improve Your Business
• Businesses may decide to focus on products and features that need improvement to reduce customer churn.
• Brands can also focus on making the already existing features better that retain the customers.