From the birth of civilization until 1900, beneficial knowledge doubled every hundred years approximately. Following World War II, these intellectually fertile periods shortened to spans of 25 years. Now, well into the 21st century, we can say that knowledge doubles within a year on average. The fact that the information produced by humankind will double in less than a year makes it difficult to predict the future in today’s fast-paced work environment, and it is a reality that makes a difference for companies that can predict. Companies serving individual customers need to effectively measure and predict not only the industry but also customer behavior. But how? This question ushers in a new phenomenon: Predictive Customer Analytics
A Quantitative Approach to Predictive Customer Analytics: Net Promoter Score
Net Promoter Score (NPS) is a measurement method used by a company to measure loyalty in customer relations. As an alternative to traditional customer satisfaction surveys, it is highly correlated with revenue growth. NPS is used by more than two-thirds of Fortune 1000 companies today. Let’s continue with the example of a Financial Services Company, which we’ll call FSC. This company is trying to measure and estimate NPS with the help of a predictive analysis tool. So, FSC prompts customers with a satisfaction question after providing services. The customer sees the prompt on a screen as pictured below:
How satisfied are you with the service we provide? (0 lowest, 10 highest)
FSC provided this customer with detailed information about credit opportunities and gave 6 points. The call center agent answered all the questions very well. However, they made the customer wait too long on the first call. It’s a huge waste of time if it’s going to be like this every customer contact. Moreover, the transaction fees are very high. This makes the potential applicant indecisive about whether to use a loan or not.
Suppose all these scores are added together and the average NPS measures 69.8. What does this tell us? If this score was 74.49 in the previous 10 months, what’s the significance of this decrease? Where should the company look for a drop in customer satisfaction? And more importantly, finding out the root causes after the fact is not helpful. So, how can it predict NPS for the future and understand which “moments of truth” will have the greatest impact on NPS results based on historical data? If a customer experience management tool leaves CX teams with more questions than solving NPS-related questions, we cannot say it is a good example of customer-focused approach.
Alterna CX’s NPS simulator utilizing predictive customer analytics
Let’s take a look at a new analytics screen to see what predictive NPS is and how predictive customer analytics works when set up correctly:
We can see the NPS drop on Alterna CX’S simulation screen. But seeing this decline doesn’t mean anything by itself. In order for the company to prevent this decline, observers need to know about services that are not going well within the company. Management also needs to know how much of an improvement is required to affect NPS for any particular service.
Alterna CX’s NPS prediction simulations provide these insights, providing an example of a useful predictive analytics tool. In the breakdown by topic on the right, we can see what the average NPS is for each topic. Obviously, our customers are experiencing serious dissatisfaction with “Pricing/Fees.” Well, let’s say the Customer Experience team has an action plan for this, so what will the total NPS be when this topic’s NPS score changes? All you have to do for this calculation is slide the bar of “Pricing/Fees” to the right.
Now FSC can identify which issues bring out their customers’ negative opinions. Then they can predict how future improvements may affect the overall NPS result on a topic-by-topic basis by simulating the results of change on future CX metrics and the customer experience quality and this capacity entitles FSC to better prioritize investments. Thus, the power of predictive NPS enables this company to design and execute Customer Experience processes with an optimized effort.