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Client can predict the conversion of customer hence design better marketing strategies for improved sales

 

Client Background

The client is the leading all-in-one website service for growing businesses around the world. Client also provides application hosting services and third-party integrations like Salesforce, Google Analytics, Facebook ads API’s etc

Challenges

  • As the project is multi-tenant e-commerce application, the content in the pages should be configurable by the tenant
  • Improve performance and the reliability of the solution
  • Improve application responsiveness across multiple devices
  • Ability to predict the conversion of prospect into customer based on the prospect data
  • Further development of new features to ECOM, CRM, invoice and service connect modules.

Solutions

  • Migrated the views from ‘haml’ to ‘liquid’ format, which helps the tenants to update the page contents dynamically from the admin pages
  • Liquid was used in storing to also enable rendering dynamic views in Ruby
  • Identified bottlenecks and root causes for critical defects and fixed them to drastically improve the performance and reliability of the platform
  • Used NLU, NLC services for predicting the potential customers.

Tools & Technologies

Solr, Rails, Mongo DB, SQL Server

Key benefits

  • Tenants can manage website content with minimal development and deployment effort
  • Improved user experience which, in turn, reduced the user enablement training time and businesses were able to adapt the platform quickly
  • Client can predict the conversion of customer hence design better marketing strategies for improved sales
Key Benefits of Predictive Analytics in Ecommerce.

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