How are Campaign Analytics techniques used to control churn in telecom

Changing customer expectations push telecom companies to respond through more attractive deals, packages, and price cuts. Given these difficult dynamics in the market, the management of the customer base to minimise churn should be among the highest priorities of any senior telecom executive. Worldwide research shows that companies adopting a systematic, analytical-based approach to base management can minimise their turnover by as much as 15%. One of the top-level goals of telecommunications companies is the study of customer data in an effort to recognise and reduce customer churn. Having the right method to conduct this analysis and get ideas about how to reduce churn coefficients in such a challenging market.

Intelligence Gathering Using Big Data

The holistic view of your client that marketers could only dream of in the past can now be developed. And this should be their objective: to have a way to aggregate and use all the various datasets you have for individual customers to their benefit. This includes your data warehouse’s transaction data, which informs you how much each client spends on your services and when. It also provides service call information that helps you to understand how good or bad things are going for individual customers; and information that relates to network efficiency or web logs that can tell you about delays and downtime. All this information can help you create a rounded image of each customer.

Micro-Segmentation

All this information can be used by Telcos to build micro-segments of customers, which can help you personalise your products and services to small groups of customers with a high risk of leaving. A library of 50+ deals was generated by one leading telco, targeting such a micro-segment with marketing offers, and slashing their churn rate over 18 months by 10-15 percent. The secret to improving customer churn behaviour is to be able to recognise and rapidly evaluate fresh deals on individual micro-segments, understand, and adapt different aspects such as value, messaging, and delivery mode.

Implement a Data Deep-Dive

In order to discover hidden patterns and better understand consumer behaviour, telecom companies should look to implement cutting-edge analytical techniques that apply sophisticated algorithms to their aggregated data sets. This is especially helpful in forecasting why consumers would want to quit. To define over 50 variables that contributed to customer turnover, as well as their relative value, one leading operator used an analytical technique called ‘function discovery’. Relevant variables, such as combinations of phone forms, data use, and call-center contact history, were among these variables. If any of these combinations were hit by a customer, the programme could accurately predict that the client was on their way to leaving.

Rise of Robots

Advanced analytics such as campaign analytics also helps you to conduct AI-driven predictive analytics through advanced approaches such as predictive behaviour modelling, a mathematically intensive approach that can reliably predict churn in a particular micro-segment of the consumer. Another is the study of customer retention (aka ‘survival analysis’), which can show how many new consumers over time will remain customers. Thirdly, the suggestion of the next best deal (NBO) will foresee what the customers want before they do. NBO will help you put together a highly tailored deal and direct your client to it at the right time, using the most convenient platform for them, and they can find the most cost-effective and appealing solution. Lastly, you can use sentiment analysis to text in social media comments, reviews, emails, and web chats using Natural Language Processing (NLP). This can identify the positive, negative, or neutral emotions customers feel regarding products and services.

Benefits of Predictive Analytics

Collective Data: Telecoms can connect to all of their marketing data sources, compile all of their information in one place, and prepare it for review.

Reports and Dashboard: Telecoms can create reports and dashboards to get a full picture of their marketing channels’ results.

Proactive Solutions: Predictive Analytics platform analyzes data and provides proactive ideas on how to improve your campaigns and increase ROI.

Safety: All data is completely safe. The analytics platform offers the best data security and adheres to stringent data protection standards.

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