CarSaver: A one-stop solution offering end-to-end customer data insights

Category: Advertising and marketing

Services: Managed Engineering Teams, AWS Managed Service, Contact Center Workflow Design, Custom Integration and Reporting, Security and Compliance, DevOps, Cloud Architecture Design, and review



Improved customer satisfaction by 20%


Achieved 80% of first interaction resolutions


Achieved 85% of customer satisfaction ratings

About CarSaver

CarSaver is a platform offering a comprehensive view of customers, enriching the existing internal data with third-party information from different sources across 30+ automobile brands, including Hyundai, Mercedes-Benz, Mazda, Volvo, and Porsche.

Problem Statement

  • Develop an efficient and secure analytics platform that ensures an enhanced view of the customers across different automobile brands
  • Create an analytics system to segment eligible customers for upgrades, generate corresponding deals, and manage this process efficiently.
  • Implement database architecture that provides reliable information on leads and marketing activities.
  • Create intelligent recommendations for second-hand cars based on customer preferences and transaction history.
  • Ensure data protection compliance and regulatory requirements by securely storing customer data organizationally.
  • Streamline infrastructure management and configurations to ensure high-quality data in real-time for better analytics efficiency.
  • Integrate secure remote access to AWS resources with the existing Single Sign-On (SSO) system.

Proposed Solution & Architecture

  • Developed a system using AWS ECS as the container orchestration service, AWS Lambda functions for real-time calculations, and DynamoDB as the database service to store customer data.
  • Leveraged Amazon Connect contact center to automate recurring marketing tasks, audit incoming network requests, and ensure robust security and compliance.
  • Used Offerlogix as a recommendation engine integrated with the AWS ECS environment to display the best trades for users looking to upgrade their vehicles.
  • Amazon RDS was used to store car trade-related data, and Amazon DynamoDB was used to segment audience data.
  • Employed AWS Lambda functions to perform the calculations for a financial estimate of the car transaction.
  • Leveraged AWS CloudWatch to monitor critical changes in the system and send real-time alerts.

Metrics for Success

  • Achieved a 20% increase in customer satisfaction scores.
  • We achieved an FCR rate of 80% or higher for CarSaver’s platform.
  • Simform achieved a consistent CSAT rating of 85% or higher for CarSaver’s platform.

Architecture Diagram

CarSaver- AMT-Data and Audience Management

AWS Services

  • AWS Lambda: We utilized AWS Lambda ETL jobs to generate leads, nurture, and improve conversions.
  • Amazon Connect:We implemented Amazon Connect for personalized customer interaction with improved managing inbound and outbound communication, enhancing engagement, and optimizing support.
  • Amazon DynamoDB: We used DynamoDB to store customer data, trade info, leads, marketing, configuration settings, and code management.
  • Amazon Aurora:We used Aurora as a database storage solution for database compliance purposes.
  • Amazon CloudWatch:AWS Cloudwatch monitors resources and provides real-time alerts on specific changes.
  • Amazon S3 buckets:We used AWS S3 buckets to store configuration and customer data files.
  • Amazon Elastic Container Service(ECS):We used the Amazon Elastic Container Service for application deployment as a container orchestration tool.
  • AWS Auto Scaling: We used AWS autoscaling to scale up or down according to incoming traffic/load.
  • AWS Config:We leveraged AWS Config to track the configuration history and change notifications for better governance.

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