The telecom industry is reaching a saturation point for its voice sales and wireless penetration. It can be inferred that there are hardly any new customers to be tapped. Everyone is using the basic telecom services, making it difficult for telecom companies to grow their revenues by recruiting new users. What this means is that the only way to gain new customers is to take away customers from competitors. With easy number porting services and lucrative welcome offers, customers are more willing than ever to leave their current service providers. This poses a significant challenge in the telecom industry, that of managing customer churn. It is evident that competitors are providing exciting bundled offers, price cuts, and packs to lure customers. So in the age of cut-throat competition how can telecom companies reduce customer churn rate?
Get in touch with our experts to know more about reducing customer churn in the telecom industry.
Developing a Comprehensive Customer View
You can only develop activities to retain your customers if you know them very well. So the first step to reducing customer churn is having a clear understanding of your customers in terms of behavior, attitude, and customer journey. It is essential to know how the customer was acquired, on-boarded, and disconnected, if applicable. The knowledge of such parameters includes data like their complete profile, product usage, discounts offered, network experience, feedbacks, and promotions. Telecommunication companies can aggregate such data with external sources to learn about competitive pricing, media spend, promotions, and other factors to get a detailed customer view.
Using Advanced Analytics
Merely collecting customer data doesn’t amount to anything. Telecom service providers should use sophisticated algorithms to mine through the massive pile of customer data. These algorithms are smart enough to identify hidden traits to predict which customers are most likely to churn. Subsequently, companies can then analyze the reasons behind their churn before coming up with solutions to prevent such an event. Hundreds of variables could be examined and compared with customers who churned before. So decision-makers could define a threshold level, which when triggered sends out warnings to the specific team to resolve the issue. For instance, if the customer is discontent about network quality then algorithms can be set to place to alert the customer support team after any user faces more than five call drops within a span of a week.
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Although computer systems have gotten more powerful, it cannot be used to treat each customer in singularity. Such a method is time-consuming and requires an enormous amount of resources. An effective method is to break the customer base into scores of micro-segment. Customers can be classified into different cohorts based on specific traits and behavior exhibited by them. Based on that, different classes of offers can be devised for each segment of the customer to avoid customer churn. For instance, customers who are frequently running out of their data packs can be offered higher data usage packs for a discount.
Test, Learn, and Collect Feedback
Computers are only as good as the humans that handle them is an old adage that still holds true. Sure, predictive analytics can dwell deep into customer insights, but it all depends on the telecom operator who implements changes in order to tackle the churn issue. Identifying customer churn beforehand is only half the battle, correctly segmenting customers and providing a customized solution is equally challenging. Additionally, it is also essential to measure the result of such action to enhance future retention strategies. Finally, telco companies should add a little human touch by asking for customer feedback, so that they gain not only an analytical perspective of the churn problem but also a human input.