Calling all CSPs: Reduce and prevent churn with analytics
Brittany Detamore 270006ARTU firstname.lastname@example.org | 2013-06-11 13:45:58.0 | Tags:  dig-data csp analytics sogecable smarter-analytics xo-communications | 0 Comments | 4,256 Visits
Follow Blythe on Twitter at @bhchou
With customer churn rates as high as 30 percent per year in some global markets, identifying and retaining at-risk customers remains a top priority for communications service providers (CSPs). Markets are saturated, unhappy customers defect or downsize their service usage and a class of professional churners is beginning to emerge.
For CSPs, applying Smarter Analytics to daily decision making offers a tremendous opportunity to uncover insights about customers, network performance and market trends – if they can harness it.
Improvements don’t just happen at the flip of a switch, however. They require strategic changes in culture as much as people, processes and technology. The good news is that communications executives are recognizing the power of analytics to drive better outcomes.
Perry McDonald, global communications sector executive for IBM Business Analytics, spoke recently with me about how CSPs are using analytics.
Based on your customer discussions, what trends are you seeing among CSPs?
The biggest trend emerging in the industry centers on realizing the full potential of big data. Operators are uniquely positioned to aggregate and learn from vast amounts of traditional and new sources of information from their customers, their networks and the services they offer.
How can CSPs improve retention with analytics?
We all know it costs a lot more to acquire customers than retain them, and with the universe of potential net-new subscribers ever diminishing, reducing churn remains one of the top considerations for our CSP clients. CSPs have been using advanced analytic platforms to predict churn propensity for some time now.
What's exciting about our new capabilities is that CSPs can apply predictive modeling on a massive scale—on a variety of disparate data sources, in a near real-time environment—using the results to make tailored offers to individual subscribers. We've evolved from a time when we modeled for groups or segments of subscribers to one where we see CSPs using analytics to model to a universe of ONE. Every consumer wants to be treated as an individual, and advanced analytics enables a one-to-one conversation, which leads to better retention and improved engagement with the customer.
Can analytics help CSPs gain value from social media data?
Social media is a great example of unstructured big data, and CSPs are gaining significant value by applying text and sentiment analytics to blogs, discussion forums and every thread of commentary that's in the public domain. Listening to subscribers on a massive scale across a broad range of social media changes everything. Measuring sentiment towards a brand, a particular product offering or device in near real-time, for example, gives marketers a powerful new way to gauge the effectiveness of campaigns and product launches.
Listening to how subscribers experience network performance in a given location provides network engineers with new insights on quality of service from a customer perspective. Call centers can better anticipate call volumes and be informed of issues with a particular device. Social media analytics can be applied to call center interactions to provide a quantified view of what customers are really saying—so CSPs are now able to hear the voice of the customer and respond accordingly.
What are some examples of best practices?
Two excellent examples are XO Communications and Sogecable.
XO Communications uses analytics to identify at-risk customers, helping client services agents to focus their proactive outbound “health check” calls. As a result, the provider reduced customer churn from 1.9 percent to 1.4 percent in the first year, and increased retention rates by 60 percent. The company’s new ability to pinpoint and preempt customer churn delivers a 376 percent annual return on investment. The project paid for itself within five months, and provides an annual net benefit of over $3.8 million.
Sogecable wanted to optimize its customer call center interactions by enabling agents to conduct personalized conversations with clients instead of using traditional standard scripts. Using an analytics solution, the company was able to recognize segmentation of inbound calls — ultimately improving its customer acquisition and retention in only two months.
These are just a few examples where we’ve seen analytics have a significant impact.
Interested in learning more? Download our latest white paper, Minimize churn with analytics, and discover how CSPs can understand better who’s likely to churn—and take action.