Pricing pressures are not new to the telecom industry. However, with little to differentiate between products and services based on handset selection and network quality, price cuts, competitive bundles and offers are becoming the norm. As new subscriber acquisition costs are very high, managing the churn in the customer base has become extremely important. While telecom companies have access to terabytes of data, they need an advanced data-driven solution that can help them achieve timely and accurate insights and help them maximize Average Revenue Per User (ARPU), reduce churn and aid in accurate demand forecasting.
By using advanced data mining and behavioral analysis, we help identify the best subscriber segments, discover and prioritize specific products and services which a subscriber is likely to opt, predict a subscriber’s risk to churn and initiate real-time marketing interventions. We also help telecom companies in new subscriber acquisition by using predictive analytics to create targeted offerings and campaigns.
Churn Analytics & Retention
Companies that implement a comprehensive analytics-based approach to subscriber management can reduce their churn by as much as 15%. We use cutting-edge data science techniques to identify previously hidden variables and their combinations that contributed to customer churn, including factors such as phone type, data usage, call center history etc. Telcos can use this data to find the reasons behind the churn and tweak their retention strategies to come up with personalized solutions that can help retain customers.
Network Optimization and Management
Growing network demands have challenged the telcos’ capability to deliver superior customer service and forecast growth. By leveraging our network optimization analytics, service providers can improve optimize and upgrade their network, minimize outages, simplify the network operations and control, undertake capacity planning, improve customer experience, and drive overall revenue.
Marketing Insights and Channel Analytics
Consumers expect to be able to connect with telcos through multiple touch-points such as telco-owned and third party retail stores, online channels websites, social networks etc. Mastering this multi-channel world will be crucial and this is where we help. By using advanced segmentation algorithms, we identify the segments of retailers and distributors who are giving subscribers with the best LTV. Our solutions also enable you to find out which channel works best for which kind of customers, migrate them to channels that offer the greatest potential for value and increase offer success rates by delivering better data, ultimately optimizing customer cost.
Customer experience is not just a series of touch-points, but goes much beyond that. In order to deliver a superior customer experience, a telco needs to map customer journeys that matter to most key segments mapping how these journeys flow across functions, channels, and devices, and identifying and eliminating the biggest pain points. Our experts will help you in this journey by using advanced data analytics, which will help you to quickly tap emerging demands, test new ideas in real time and mine existing data for compelling customer insights.
Personalized Campaigns and Response Modeling
Most telecom operators spend on promotions that offer very little ROI. We will help you address this lack of efficiency and improve customer experience by using campaign management tools to push targeted promotions to the right set of users based on the subscriber’s usage intelligence using channels such as SMS, Voice, USSD, Web and WAP. Using Business Intelligence, our experts will enable you to map potential users and offer promotions and help retain customers & activate dormant ones.
Social Listening & Sentiment Analysis
Social listening and media monitoring can help telecom brands to increase their engagement with their customers. Our experts will provide real-time insights on customer engagement through social listening techniques such as sentiment analysis and applied clustering. By applying these techniques, we can identify your top influencers, topics of interest among your users and segment groups of users with similar traits. We also help you match different content and ads to the right set of customers by analyzing the content and profiling the consumers using our machine learning solutions.
Using retail analytics on loyalty card data, a leading pharmacy retail company increased transactions by 15% and clocked 30% rise in average ticket size for loyalty card holders.
Sales at a leading US-based marketplace seller soared 1.5 times, while operating margins registered a 50% increase after changes were made to its pricing algorithm.
Retail giant registered 18% revenue growth by using analytics-driven targeted marketing.