Advanced Telco Analytics
For Telco companies to build a sustainable, competitive advantage, it is vital to have an in-depth knowledge of customer attitudes, behavior and actions. This data is pivotal in deciding on steps to improve customer retention and optimize operational efficiency. In order to understand the entire customer life cycle, Telcos need to leverage and integrate huge amounts of customer data from a range of sources – like Call Data Records (CDR), customer care, product/service portfolios, network service quality, and cost and billing.
Optimize Networks for Maximum Revenue
CUBE integrates heterogeneous, multi-source data that can be easily scrutinised using advanced analytics tools. It is capable of analyzing an entire subscriber base, defining unlimited business parameters and segmenting rules. Its prediction model uses the latest machine learning and sampling techniques enabling Telcos to forecast prospective tendencies and so take relevant, immediate actions.
CUBE’s descriptive analytics help Telcos to understand the relationship between subscribers and products. Our analytical engine identifies and examines patterns in subscribers’ product and service consumption. In this way companies can utilize knowledge of the past to inform future decisions.
CUBE offers predictive analytics with high levels of forecasting accuracy through machine learning, clustering and data mining. Telcos are provided with vital actionable insights through predictions on three important aspects of customer behavior:
Propensity to Churn – Predict the probability to churn within the next 3 months with 75% accuracy. Telcos can identify specific subscribers and reward them via personalized campaigns.
Propensity to Collect – Predict the probability of payment receivable potential for charge sheets sent at the end of the billing cycle, with an accuracy of 85%. Telcos can target these charge requests and so save on costs.
Propensity to Buy – Predict the probability of each subscriber making a purchase within the next 3 months with 85% accuracy. Telcos can activate special applications and service plans for these customers.
The diagnostic analytics of CUBE helps Telcos with root-cause analysis, data discovery and exploration. Starting at the descriptive analytics phase, it uncovers patterns and correlations from millions of customer data, moving into the predictive analytics stage, offering Telcos insight into the reasons for negative performance variations that can drive internal optimization and strategy development.