Cosmos is imagined as addressing open challenges in the customer 360 paradigm:

• Data is siloed, and the lack of connected data leads to poor customer insights.
• Lack of comprehensive customer strategy and the need for deeper customer insights like preferences, headroom, CLTV, journey, and hobbies for advanced personalization strategies
• Inefficient data models & poor workflows led to low analyst productivity and a heavy dependency on technology experts.
• Companies that are not able to move past the "one size fits all" strategy result in suboptimal experiences and eventually lose customers to their competition. Dated segmentation leads to prioritizing customer segments that are already engaged.

Tredence’s Customer Cosmos is an enriched Customer 360 data model that provides omnichannel visibility into profile, behaviour, preferences, attitudes, and deeper customer insights by integrating 1st and 3rd party data. The Cosmos solution will enable you to unlock the following value from customer data:

• Customer Data Model and KPI Stores—Verticalized and Sub-Verticalized Cosmos Feature Stores across Retail, Telecom, Media, Insurance, and Health Care
• Pre-built Data Engineering and Transformation Notebooks: SQL Pipelines to Get 360 Customer Attributes from Source Systems
• AI/ML notebooks prebuilt with modularized parameter tuning for predictive and preference customer attributes

It has 70% pre-built code deployed on AWS, which helps accelerate the development and deployment of the solution. Cosmos uses native Glue (PySpark) and runs on Spark clusters that easily scale to process millions of records in minutes. It uses various AWS services like S3, Redshift, DynamoDB, Athena, IAM, Kinesis (real-time), etc., required to develop, deploy, manage, and maintain the necessary predictive models and leverage the potential of AI and ML.

The combination of Tredence’s customer experience domain expertise, AWS’ data processing speeds, and AWS SageMaker ML capabilities provides a winning combination.