DOWNLOAD THE CASE STUDY:
Telco companies have access to huge quantities of first-party data, which is valuable for driving innovation, as well as, segmenting and marketing to subscribers.
However, this owned data is limited to their direct relationships with subscribers and the information that can be captured through internal systems. While this first-party data is crucial to their success, there are significant gaps – particularly around household data, which is considered one of the most predictive features of the propensity of acquisition, retention, churn, and average revenue per user (ARPU) expansion.
Read this case study to learn how:
High quality data and predictive features were used to better identify and understand households
To construct households through data enrichment and predictive modeling algorithms
Enriched household insights were applied to up-sell and acquisition campaigns as well as competitor analysis.
Fill out the form to access the case study and learn how data enrichment and feature engineering can drive your customer acquisition strategies.