Reducing customer churn through data analytics
Over 90% of adults in the UK have a mobile phone, and two-thirds of the total population owns a smartphone, according to Ofcom’s 2015 Communications Market Report – meaning the market for new mobile customers is quite small.
And with such a small pool of potential customers, it has become extremely difficult—and expensive—for telecommunications companies to acquire new customers.
The saturated mobile market may be the reason some providers try and poach customers from their competitors – we have all seen the commercials. The issue is strengthened by the ease of moving from one network to another: Customers can switch providers instantly, and keep their phone numbers. These factors contribute to annual churn rates between 10 and 67%, according to the Database Marketing Institute, says David Hall-Tipping, solutions manager at Logi Analytics.
Surprisingly though, the number one reason people switch providers isn’t cost, but rather a perception of poor-quality of service — perception being the key word, as service doesn’t have to actually be poor for a customer to switch providers.
In order to reduce customer churn, telecom companies are shifting their focus to retaining the customers they already have, which requires the ability to see the user experience through customers’ eyes. Telecom companies must gain an understanding of where customers are perceiving issues and what improvements can make them happier.
Using business intelligence (BI) and analytics applications, telecoms providers can closely monitor usage data and see the service experience through the customer lens. In turn, they can use this information to proactively improve services and boost customer loyalty.
Defining the customer experience: QoS vs. QoE
Customers base their decisions on everything they see. Just one negative experience, while seemingly insignificant, can completely change their view of a telecom provider. For instance, when streaming a video, factors such as buffering can have a negative impact. Likewise, when making a voice call, if a poor signal causes the call to drop or offers a bad connection, a customer will become frustrated and may consider changing networks.
To improve the customer experience and reduce customer churn, telecom companies must monitor all of these aspects and more – but this is more challenging than it sounds. Historically, most telecoms have looked at their networks at a Quality of Service (QoS) level. Providers were looking at whether the networks are operational and identifying any problem areas in the systems. However, this only looks at one perspective.
To reduce customer churn rates, telecoms must also look at Quality of Experience (QoE) data. QoE is how a customer perceives the quality of the network connections, and is ultimately dependent on QoS. Telecom companies build up their customer experience metrics using service-related factors like latency and bit rates. In order to elevate experience data up to the level of service metrics, telecoms need a single view of the end-to-end customer experience.
Harnessing the power of data
Telecom systems have grown increasingly complex over the years. In order for providers to see data from a variety of sources and monitor everything in real time — from operations and call centres to billing systems — they should consider an integrated data analytics or BI solution.
As telecoms move to packet-switched networks, each part of the system is producing IP data based on its location. With a BI solution in place, telecoms companies can see where problems arise because the same packet of information moves all the way through the network from start to finish.
Even when different companies provide different pieces of a single network, analytics solutions can aggregate the data to give providers a complete picture in real time and provide customer service representatives actionable insight to solve problems before they are recognised by the customer.
Data integration becomes trickier when telecom providers acquire new companies, and need to add new sources to their data streams. One of the biggest challenges is matching data from multiple sources and getting different databases to speak the same language. As part of the BI process, data cleansing solutions can be very valuable in matching and normalising data from multiple sources.
Increasing satisfaction to improve retention
With a scalable BI system in place, telecoms are able to see all of their information on one screen. They can gain a complete, end-to-end picture of the service experience through their customers’ eyes in order to improve service and customer satisfaction. In turn, providers can increase customer loyalty and retention. Data monitoring is a particularly cost-efficient way to meet this challenge and eliminate the high churn rates so many telecoms are experiencing today.
The author of this blog is David Hall-Tipping, solutions manager at Logi Analytics.
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