Managing a successful prepaid program involves making a lot of decisions. Some are easy. Others not so much. Some of the toughest decisions involve the allocation of resources. Where should you focus your efforts to make the biggest impact on profitability? Data is key to understanding how your program is performing, who your best customers are, and where you should concentrate your limited resources. Canned transaction reports just won’t cut it because, as you will see from today’s post, it’s not really about data per se. It’s about intelligence.
To illustrate the point, think about what you can learn from those one-dimensional transaction reports. They are just lists of account numbers, amounts, and transaction types. There are good transactions (like POS purchases & reloads) that help you make money and there are undesirable transactions (like cashing out a balance at the ATM) that can hurt profitability. But how do you tell from a normal transaction report how to get more of the good and less of the bad? You can’t. To get to a point where you can actually learn from and act upon data, you need to turn data into intelligence. You need access to a plethora of data points, which you can slice and dice and layer on to of each other to see patterns, trends, and clusters.
Here is a simple example of what I am talking about. If you are able to pull a list of all POS transactions and group them by merchant name, you will be able to make a list of the top merchants for your customer base. You can then take that knowledge and drill into it by overlaying other information, such as demographic data, frequency of purchases, and time of purchases. This is where you begin to uncover information that can be used to grow your business. In this example, you could potentially use this intelligence to create co-promotion, distribution or loyalty plays to drive incremental revenue for your program.
Data intelligence can also help you begin the process of developing profiles of your ideal customers. Once you understand this profile, it becomes easier to identify specific groups of customers that you can communicate within strategic ways to move them toward your “model” profile. Customer profiles can also be used to create actual models for controlling costs or predicting the impact of making certain adjustments to your program. One of our clients, for example, was able to build a profile of the consumer that is most likely to enroll for and activate their card. They then used this intelligence to more effectively target their marketing efforts, which substantially reduced their acquisition costs.
So how can you bring a more data-driven approach to managing your prepaid program?
Consider these three steps:
Gather data and information
Your prepaid processing system should be giving you the opportunity to gather from multiple sources a vast amount of customer data ranging from reloading data and balance snapshots to usage records, servicing profiles, billing information, and more. The ability to integrate external data sources is also important, as is the ability to see real-time data and sort it any way that you wish. Unfortunately, many processors fall short in this area, so if you are in the position of evaluating processors, be sure to take a close look at their reporting and analytic capabilities. Once you have access to the data, let data exploration and pattern discovery reveal unique insights into your program.
Use the data to analyze behaviors
I would venture to guess that the customer profiles you’re currently employing are static (if you even have access to the data necessary to craft profiles). By leveraging analytics that takes into account every event in a customer’s relationship with you – status changes, reloads, purchases, balance data, usage transactions, marketing interactions & responses, customer service & support interactions, etc., – you will gain a more holistic picture of your customer base. This kind of insight will aid you in developing a customer engagement strategy that will optimize your program.,/p>
Look at individuals in addition to segments
Too many prepaid marketers and program managers never think about personalization at the individual level. Perhaps it’s because they don’t have the technology in place to be able to execute a personalized experience or they lack the intelligence about individual customer behaviors & preferences. Having the capability to monitor behavior at the individual level will help you understand customers and craft an experience they will find truly engaging. Getting data intelligence is one part of this strategy. Having the ability to engage with customers in real-time, based on or in response to their behaviors, is the other part. The power of real-time enables you to act upon behavior insights at the right time and place, creating a unique and personalized experience for your customers.