Karmasphere Use Cases for Jumpstarting the Value of Hadoop
Big Data Analytics for Hadoop
Use Big Data Analytics Insights to Optimize Your Customer Engagement Lifecycle
Each and every interaction with a customer makes up a company’s Customer Engagement Lifecycle. To delight customers and thrive in the era of Big Data and digital business, every phase of the Lifecycle must be optimized making it more cohesive, integrated and relevant.
Below are use case ideas for applying Big Data Analytics to optimize ways customers purchase, use and receive support —the key phases of the Customer Engagement Lifecycle.
An expected benefit of the use cases is to increase the key business metrics of Customer Lifetime Value (CLV) and Customer Likelihood to Recommend (LTR).
Customer Purchase Interactions
Enable richer and highly-personalized cross-selling and upselling
Use Channel Analytics on Big Data for:
- Customer micro-segmentation
- Dynamic product categorization
- Personalized and auxiliary product recommendations
Customer Usage Interactions
Ensure highly-competitive products and services
Use Telemetry Analytics on Big Data for:
- Product usage patterns
- A/B feature testing
- Failure detection and diagnostics
Customer Support Interactions
Deliver proactive and cost-effective customer service
Use Response Analytics on Big Data for:
- Churn reduction
- Self-service help
- Customer loyalty improvement