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Reduce service work and get information about the reasons for calls

Learn how we built an enterprise data platform in the cloud and implemented AWS AI integrated services to better understand and meet customer expectations.

Context

The call center of a large health insurance company wanted to drastically reduce the agent's after-call work and find the best solution to get detailed information about the reasons for calls.

Challenges

Given the rapidly changing health insurance market, this health insurer wanted to leverage its data to create more business value. Specifically, it needed to: 

  • Move from a traditional descriptive BI to a predictive or even prescriptive approach.
  • Deploy an agile data environment to implement advanced analytics.
  • Actively support the digitalization of the company and the new CRM approach.


They also asked us to advise them on :

  • How to transform the organization to support new ways of working with data.
  • Choosing the right technology for traditional BI and new advanced analytics use cases.
  • The definition of a roadmap for implementation, taking into account organizational and technical changes.

Methods and Solutions

We first looked at the current organization (as is) and the target organization (as will be) and made a series of recommendations for setting up the new data and advanced analytics team, redefining the change, build, and execution processes, and introducing a data governance approach to the organization.
 

In a second phase, we deployed the new cloud-based data environment and quickly implemented a series of traditional BI use cases (using an agile methodology) as well as innovative new AI and ML use cases, such as automating the processing of call center recordings using the Speech-to-text and NLP technologies available on the cloud environment.  

Their new data platform is now rapidly ramping up and is a key component to dramatically improving the customer experience and implementing their digital transformation.

The Project

1
Amazon S3

The central input layer.

2
Amazon Kinesis

Real-time integration.

3
Amazon Redshift

Data Warehouse.

4
Amazon DynamoDB

Optimize your monthly AWS bill.

5
Amazon SageMaker

Machine Learning.

6
Amazon API Gateway

API for external access.

Technology solutions

Amazon Web Services (AWS) is a comprehensive and widely adopted global cloud platform that enables companies to reduce costs, increase agility, and innovate faster. 

In the digital age, the cloud offers many future opportunities for businesses. Lucy's mission is to help companies, regardless of their size or industry, with this transformation.

Turn your data into a strategic asset with Lucy