In this guest post from IBM's Catherine Frye, she will showcase a customer, C Spire Wireless, discussing how their Predictive Customer Intelligence use case for “pinpoint personalization” using analytics acted as the catalyst for a company-wide initiative to deliver a transformed customer experience. This solution includes optimized actions during every customer interaction allowing for maximized revenue opportunities and a clear reduction in customer churn in very short order.
As background, C Spire is the largest US based privately held wireless communications company, providing wireless services and premier mobile communications devices to over 1 million consumers and businesses in four states and through approximately 100 retail locations .
This is an outstanding example of an organization who understands and executes successfully to move analytics to the front lines at point of impact with their customers. C Spire embraces with laser-like focus the creation of a single, 360 degree view of their customers, and then, using analytics, specifically churn modeling combined with decision management, to further refine their ability to deliver the best decision or actions for their front line employees at that point of contact.
The result? C Spire is able to understand during each customer interaction how to best service and meet the needs of customers at risk – with the best “action option” delivered to their frontline agents via their customer operational systems in real time. C Spire understands that by automating and optimizing the frontline decision making process – moving analytics to point of contact -- they can ensure a consistent and integrated customer experience across all engagement channels.
Let’s hear from Justin Croft, Manager of Brand Platforms and Analytics at C Spire Wireless, directly:
C Spire Wireless was able to see the effectiveness of their retention campaigns with an increase of 50% within three months and an increase in sales of certain accessories by 270% over the same time period. Marketing was able to obtain precision control over the customer experience and frontline agents were able to precisely tailor their responses during customer interactions to help deliver both incremental revenue from successful cross-selling as well as have a significant impact on customer churn in weeks.
Finally C Spire noted that predictive analytics really helped them by looking through the lens of customer interactions understand what the customer wants to buy rather than what C Spire wanted to sell the -- delivering a more positive experience for both sides – and better outcomes.
Catherine Frye is IBM's Marketing and Customer Service agendas Leader, Business Analytics solutions.