How a Bad Decision Process Ruins Customer Experience
Let's look at customer experience scenarios that can be improved by advanced analytics and how CSPs could and should take a more customer-led approach.
Communications Service Providers are competing on customer experience powered by data, advanced analytics and connected decisions. In this second article of my series, we’ll look at customer experience scenarios that can be improved by advanced analytics and how CSPs could and should take a more customer-led approach.
The landscape has shifted for CSPs, and identifying competitors is more difficult than it used to be. Looking at direct businesses is no longer the whole story, as a number of companies in other sectors provide exceptional customer experiences that drive consumer expectation. When a consumer gets used to technology, interface and journey that makes their life easier, it raises their expectation of how their interactions with all companies should be.
So, not only are CSPs competing with one another, they are competing with the over-the-top (OTT) services that use their infrastructure, and also competing with Amazon, Neflix, Spotify and other businesses that their customers love.
The math for investing in customer-based decisions is straightforward: Satisfied customers spend more and stay with you for longer. Recent research from Analysis Mason shows that for every 1% increase in Net Promoter Score (NPS) there was a 4% decrease in churn. AT&T’s research shows Customer Satisfaction (CSAT) ratings of 90% have around $10 higher ARPU and longer tenure compared to CSAT of 75%
Yet we know CSPs’ aspiration doesn’t always match the operational ability to achieve this.
What's Going Wrong
Here's an example of where customer experience begins to unravel because decisions are not connected and the CSP is not proactive:- Customer has been with CSP for a number of years and usually upgrades every two years
- Customer comes toward end of current contract
- No proactive upgrade offers forthcoming from the CSP (customer does not feel valued)
- Customer decides to keep the device, not much difference to the latest model, and move to a SIM Only plan to reduce the monthly cost, does so in the shop
- Due to the complexity of the billing platform, moving to the SIM Only plan changes some back-end settings and suddenly customer does not have access to international roaming when next overseas
- There is no communication to the customer about this
- Customer contacts CSP contact centre to be advised that they need to pay a deposit before they can have roaming switched back on, there is no way to override the system
- The customer is told they can contact the CSP in 3-6 months to have this deposit refunded
- Contact centre advises the customer that this should all have flagged up and been explained in the shop
- Customer subsequently receives an SMS with an upgrade offer to the latest device
This type of scenario is not unusual and is a classic case of user experience being designed around existing system limitations, rather than truly being designed around the customer.
It exposes the lack of consistency between different channels, teams and departments, and reveals that the CSP is not using real-time data to drive the right offers at the right time with the right context. The decisions made are not connected to one another, they are not optimized and there is little to suggest that any analytics undertaken are at an advanced level. In short, a more personalized and joined-up approach is more likely to foster a strong and enduring relationship.
In my third and final article in this series, we will discuss how embedding analytics into the operation enables CSPs to improve their customer experience capabilities.
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I further broke this down by looking at the characteristics of the youngest 15% in each group, which occurs at age 29 for the 750-799 group and 43 for the 800-850. We used FICO<strong>®</strong> Score 9 for our analysis, and examined typical variables of the categories that go into the make-up of the score.</p> <p><a href="http://www.fico.com/en/blogs/wp-content/uploads/2016/10/FICO-Score-High-Achiever-table.png"><img class="alignnone size-full wp-image-29367" src="http://www.fico.com/en/blogs/wp-content/uploads/2016/10/FICO-Score-High-Achiever-table.png" alt="fico-score-high-achiever-table" width="715" height="747" /></a></p> <p>Since there’s a lot to dissect in this chart, I’ll highlight a few findings that struck me: <ul> <li><strong>Credit history.</strong> Higher scores are undoubtedly associated with a longer time on file. What’s striking is the higher average time on file for the 800+ group, both overall and for revolving accounts (the most common trade line). 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