Customer Behavior Analysis
to Boost Online Purchase Rates

customer behavior analysis to boost online purchase
overview of customer behavior analysis


Analyzing your customer correctly can boost your revenues tremendously as it informs you about your customers' interaction with your business. A customer behavior analysis gives insights into the different factors that influence your users. This analysis helps your business understand the customers' perception of your company which helps you make better decisions in the future. HData Systems helped our client, one of the biggest CPA networks in Eastern Europe, analyze customer behavior on the web pages, forecasting and reducing revenue losses.

Client Requirement

Our client was facing a struggle to reduce revenue losses that his business was facing due to a gap between the payment from the CPA to affiliate and the payment from the customer to CPA. This gave the customers sufficient time to change their purchase decision, ultimately leading to suppressed conversion purchase rates. Therefore, the client approached us with his problem to reduce these revenue losses by analyzing the customer's behavior on the website, predicting and preventing such losses.

client requirements of customer behavior analysis


  • The deep learning model enabled our team to understand customer behavior and model the possibility of purchase based on users' web-surfing experience.

  • Giving recommendations after detailed research and hands-on experience leads to more revenues and profits while delivering top-notch services to the customer.

  • Incorporating Apache Spark, Tensorflow architecture with clients Elastic + PostgreSQL + RabbitMQ


We have built a thorough event tracking plan of customer activity and later tested its implementation against the past data. This helped measure crucial behavioral patterns connected with the customer purchase.

Deep learning technologies helped our team discover the unintuitive connection between customers' activity and purchasing results, which were difficult to find and interpret.


Forecasting the possibility of the purchase intent and actual purchase helped our client prioritize calls queue and prevent bad traffic on the business by 16%.

Moreover, the solution also helped to enhance the customer journey on the web pages to reduce revenue losses from unrealized purchases.



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