Common sense tells you that no two customers will react to what’s in your branch in exactly the same way. But predicting who will like a new service requires a look at a customer’s self-service style and situational objectives. Research from two industry experts offers surprising findings on engineering a banking experience that resonates.
By Stephen Onufrey and Howard Moskowitz, PhD. Onufrey is retail banking solution executive for the SRO Group, LLC. He spent 38 years with IBM and two with Unisys working on retail banking solutions. Moskowitz is president of Moskowitz Jacobs, Inc. A pioneer in the field of psychophysics (the study of perception and its relation to physical stimuli), he was inducted into the Hall of Fame of New York’s Market Research Council in 2006.
Demographics are only part of the story. How customers react to a series of vignettes helps banks get inside the customer’s mind, heart, and emotions. Here’s how the process was applied at one large retail bank
In their seminal work The Experience Economy, Joseph Pine and James Gilmore identified Customer Experience as the emerging key differentiator in today’s services economy. That was almost a decade ago. Yet a positive, differentiated, memorable and engaging customer experience continues to remain an undefined and elusive goal for most banks. More than ever, banks recognize that their products and services are viewed as commodities. Bankers, vendors, technologists, consultants, customer advocates and industry pundits all have opinions on what the key elements are of an exceptional customer experience. But how are those opinions validated with the customer who will actually have the final vote? Usually, it is done with a series of focus groups that fine tune financial products and services after they already have been built, when the major decisions are cast in stone.
We present in this article a new approach to solving the issue of creating an exceptional customer experience in banking. The predictive analytic techniques are not new. They have been proven in successful use in the consumer goods and manufacturing sectors for over 25 years. What is new is the application of these techniques to the banking and financial services industry, and to the realm of experience engineering. And, they deal with the newly emerging notion of “addressable minds.” Knowing the ‘mind’ of the individual customer lets the bank create the exceptional experience for that customer.
The article is based on our work with a large retail banking company. The work focused specifically on questions relating to customer acceptance of new technology-based services.
The chief technology officer of that bank was faced with the task of recommending new technologies that will be cost justified and will also provide an exceptional customer experience. A predictive analysis study was performed in order to determine the potential impact of specific new technologies (including RFID—radio frequency identification) to the customer experience.
The resulting data is useful in its own right, but more important, we feel, is the methodology and approach to customer experience research. Other banks can measure their own efforts against the approach used here.
Here are four broad findings from the project:
1. No future experience really strongly appealed to or repelled the average person. The “average person,” as we will see, is a myth. Experience can be engineered, but not by looking at everyone in the aggregate. In fact, the average reaction to “new ideas,” the substance of the new experience, was neutral to somewhat negative. Scratch winning ideas for everyone! We have to dig deeper to engineer a better experience.
2. With the traditional subgroups—sex, age, income—we saw some differentiation. The new, technology-based ideas appealed more to men under the age of 40 who had an income in excess of $40,000 per year, for example. Still, there was something missing. It was clear that going about dividing people the way we’d always done it just wouldn’t give us the big hits for the future that we needed.
3. We began to hit some pay dirt with self-explicated groups who defined themselves as technophiles and technophobes. The technophiles, as you might gather, liked the new tech-based experiences. But still there was something missing.
4. Response-based segmentation—where we divide the group into smaller segments based upon how they react to future ideas—was where we found the real pay dirt; things that really excited people. We uncovered windows of desire for different customer experiences, and groups of people who would relish them. As described later on, we found four radically different groups, for which we could develop different experiences.
The customer survey results were eye opening. A new offering would create a customer advocate in one market segment, yet that same offering could become a customer detractor to another market segment. For example, using cell phones to identify customers when entering a branch received the highest vote from one group and the lowest from another. The important thing was the combination of specificity—to know exactly the feature to offer, and to know precisely the response from the segment. That allowed the prediction of the optimum customer experience, or experiences.
The key to using this predictive analysis technique is to reflect each bank’s own corporate DNA. Surveying existing and target market segments and using bank-unique questions will help the bank to not only define its exceptional customer experience but also to help ensure success of these initiatives.
Now let’s move to the details of predictive analysis and addressable minds in the banking industry.
Customers design the future
In this particular case we were not dealing with physical products, nor were we focused on the world of today. Rather, we were dealing with the near-future world of banking as people would like to have it, but at the same time a world so full of new technologies that it’s hard for people to say what they want.
At an early point in the development cycle the issue on the table was simply how to get into the mind of a bank customer to find out what was appealing. It was pretty easy to define customers by their banking patterns, and even by the way they described themselves when it comes to technology in banking (e.g. bank by internet). What wasn’t so clear was whether lurking in the background were unexpected mind-sets.
The team turned to systematics—a disciplined experimentation with ideas using an approach called RDE, or rule-developing experimentation.
RDE shows the ‘algebra of the mind.’ The goal was quite simple—learn the rules of the bank customer’s mind, when it comes to bank-related technology. Furthermore, it was important to get it right—not just get politically correct answers that are often obtained when bank customers go through batteries of questions asking ‘would you like or dislike this feature.’ Instead, we presented bank customers with a variety of vignettes containing descriptions of a banking experience as the customer would encounter it. We could then discover what particular features in a vignette drove acceptance of the experience.
For the bank in question, we created 24 tech-related service options (experience ideas that the bank could feature), falling into six different broad customer categories (e.g. “Online collaborative”). The 24 elements were the basis for an online survey that presented one or more elements as a vignette (see Figure 1). Each of 267 participants saw different vignettes and rated each one.
Note the rating question at the bottom of Fig. 1: “Thinking about your current bank experience how would you feel if your bank offered these expanded services?” We put the question as a response to an actual combination of features. We didn’t ask the customers, “Would you want it or not?” because most people will say they want most things.
The vignettes describe a complex situation, often with some elements that appeal, and other elements that don’t appeal. So the vignettes force the participant to integrate all of the information and make a judgment. Even though the combinations looked random, they were not. Rather, the combinations were developed in a systematic way so that the 24 elements really appeared as independent agents. Statistically we could discern what each of the elements contributed to the rating.
Further, in the rating question we hinted that this vignette would be a set of expanded services. The participants are reacting to something that could be, not saying whether they would like it to be. That is, in the interview we’re acting as if the services already exist, and the participant is rating the set of services, rather than selecting from a “wish list.”
Finally, rather than having the participant grade degrees of “goodness,” we have the scale move from less satisfied to indifferent to more satisfied. We actually allow the new ideas to be far worse than the current ideas, which happened in some cases. Further, we ask the participants to compare the new vignette implicitly to what they currently are experiencing.
Different strokes for different folks
To keep things simple, we divided the 267 participants into four different segments or groups, looking at the patterns for each.
(Don’t divide people into more groups than is absolutely necessary, because when it comes time to create new services, fewer segments are better from the viewpoint of operations and marketing). Individuals in a specific segment showed relatively similar patterns in the specifics that appeal to them. Individuals from different segments showed relatively dissimilar patterns.
Whenever we divide people by their “revealed mind-sets” (i.e. by how they react to things, not by what they say about themselves), we have to keep three things in mind. First, we want to be able to work with mind-sets that differ radically from each other. Second, we want to be able to interpret these mind-sets. Third, and most important, we want to find opportunities to create a stellar banking experience by discovering which mind-set a particular customer has, and optimally addressing that mind-set.
The four segments for this particular research project (again, focused on technology-related services) are as follows:
Segment 1
(self-reliant online banking seekers)
This segment comprised around 40% of the participants. They really didn’t respond to much. About the only strong element is the real-time feature (“We will answer all your requests in real time by email, instant or text messaging”). It’s important to realize that not everyone wants the next-gen bank. This first segment provides us with a dose of reality—and cautions us not to think that everyone is waiting for this new bank.
Segment 2
(technology and high security seekers)
This segment was about 20% of the participants. They respond strongly to security, and to security backed up by technology. Thus they will really feel that they have an improved experience if the bank can facilitate transfers safely and electronically (e.g. “Securely access and manage accounts or funds transfers by PDA, Internet or automated telephone”). They also feel strongly about security.
Segment 3
(collaborative online seekers)
This segment comprised about 20% of the participants. They like working with the bank’s staff, in a collaborative mode—e.g. “Faster loan application process.”
Segment 4
(personal touch with technology seekers)
This segment also comprised about 20% of the participants. They want some feeling of connection with the bank, but also want a feeling that they are recognized as individuals. This idea appeals to them, for example: “Manage all you banking needs with self-service state-of-the art kiosk and be confident that live help is available if needed.”
The segments liked different things, but it’s important to realize that each segment except “self-reliant online banking seekers” can be truly delighted by the correct choice of offerings from this next-gen bank. This is what we were looking for—the breakthrough ideas that touched some of the customers, if not all of them. Now we had the building blocks, which could be assembled in any way we wished. Plus, we had an advantage—we had a real sense of how the world works in the customer’s mind for these features.
Dialing a bank opportunity
We’d like to end this piece with a vision of how a bank might engineer the future using the knowledge obtained from this and other similar projects. Let’s do an exercise that this bank’s planner might follow, to create three features, which in total appeal to our three responsive segments—segments 2, 3 and 4, respectively. (We won’t bother trying to satisfy segment 1 because there was nothing in this particular project that really appealed to these people.)
To do this, we use a “concept optimizer,” a tool to sift through lots of ideas, and find combinations that work together well. Then, we’ll finish by developing a “typing tool.” The objective is for a bank representative to sit with a new customer, figure out which segment the customer belongs to, and then look on the computer to find out what features, what messaging, what “tonality” appeals to this segment. This is where the notion of addressable minds earns its keep. The bank representative speaks now to the customer in the way the customer wants, addressing the mind-set of this particular individual. Thirty minutes later, the customer and the bank representative should be deep in conversation about the cross-selling offerings that appeal to the segment to which the customer belongs.
Keep in mind we’re not creating an average experience. Instead, we are creating a far-better-than-average experience, knowing that our target customer groups are looking for different things. The bank plays the role of master blender of these different needs.
Table 1 (p.30) shows the results of sifting through the data. The top row shows the three elements which together drive the response, and which attract the different mind-set segments. We see immediately that, in this case, there are no big hits that appeal to everyone, which prevents wasting time looking for a magic bullet that does not exist.
We see that each of the three elements does either well or poorly in a particular segment. Now that we have chosen these three elements we can take their utilities or impact values and add that to the base interest. The total represents the proportion of people who would say that they feel more satisfied.
If we didn’t have to satisfy all three segments, but rather only two, we might feature a different, even better combination of elements. We wouldn’t worry so much about satisfying everyone. In fact, when we look at Table 2 we find that the more we focus on one segment, the more likely it will be to create far more spectacular experiences because we will have isolated a group with a specific mind-set, know what appeals to them, and not need to worry about the other segments that may be less satisfied. That is a business decision—to appeal to a larger group with a good experience, or a mind-set segment with a great experience.
Final step: “Typing” a new customer to create an “addressable mind”
Let’s now fast forward a bit, say three weeks after the experiment has been run, the data analyzed, the segments determined, and the selling messages developed. We know from looking at Table 1 that we can select a product offering and experience for any segment, or any combination of segments.
When a new customer comes in, the bank can “type” this new customer as belonging to one of the four segments, and then “dial up” the offer for the customer, once it is known to which segment the customer belongs.
To continue the example, let’s use the actual data to create four questions to type the customer. We see these questions in Figure 2. Each question comes from the original experiment where we discovered the hot buttons, and the segments. The typing engine calculates the composite score and discovers the segment to which that customer belongs. The customer has just turned into the “addressable mind,” whose responses to new offerings can be predicted.
Depending on the segment, the appropriate products and services are presented to the customer with the selling messages which were previously determined Ultimately, the bank representative now knows what to offer and how to present the offer.
What comes next?
It is clear that those banks that can differentiate themselves with an exceptional customer experience will set themselves apart from the perception of commodity that customers have of banks.
Banks can change their advertising, marketing and branding, but without the individual customer experience to drive those changes, the customer will see through the facade and vote with their feet by leaving. Today through systematic measurement, experimental design, customer typing, and creating addressable minds, it is possible to create that wonderful customer experience which incorporates the customer needs with the bank’s unique DNA. BJ
For more information about the techniques described here, read the full white paper on www.ababj.com (Follow: Content Central/Retail Banking/ “Inventing the future of retail banking”). For further reading, try Selling Blue Elephants: How to make great products that people want before they even know they want them, by Howard Moskowitz and Alex Gofman (www.SellingBlueElephants.com)
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