One of the top 3 US-based telecom providers wanted to migrate from an Oracle data warehouse to a Cloudera Hadoop-based data lake to take advantage of advanced analytics. The existing analysis mechanism was unable to increase net new and upgraded conversions. They were looking for a partner to analyze their customer journey and set up a modern Cloudera -based data lake that would help them:
- Reduce the cost of data management and analysis
- Effectively utilize their marketing budget
- Get better insights to grow their B2B lead generation
- Improve the effectiveness of marketing campaigns and channels
- Increase business revenue
6% increase in customer acquisition for omni-channel data
The Impetus team analyzed the existing data from RDBMS and external systems like Salesforce and Marketo and created a Hadoop data lake on the Cloudera (CDH) cluster for lead generation. These datasets were mined and mapped to enhance lead generation and conversion.
The solution involved implementing cross-sell/up-sell, continuum, lead-generation, and multi-touch-point attribution models to enhance marketing campaign effectiveness. Audit-trail policies were also applied to monitor and handle failovers.
- Used Kerberos on CDH cluster for authentication and authorization
- Added email notifications to all the ML models to monitor data ingestion workflows for failovers
- Tested all ML models and ingestion workflows
- Enabled optimization by tuning the hyperparameters in the property files without any change in code
The solution helped develop an end-to-end customer-360 journey, migrated data and ingestion pipeline, and modernized the existing lead generation models.
- Increased revenue by lead generation and conversion
- Effectively utilized campaign budgets
- Reduced cost of data storage
- Increased capability to store and analyze data