Capture 100% of a Buyer’s Potential Value
On today’s episode, we have we have recurring guest Gary Beck 30 year marketing veteran. Damian and Gary cover Share of Wallet. For those who do not know what share of wallet is well it is simply calculated as the amount of money spent on your products versus the total amount spent on the category.
After Gary gives his definition of share of wallet, he answers the question “Why is this important to marketers?” Gary gives two very good reasons as to why share of wallet is an important metric, 1. if it’s less than a 100%, this indicates that there’s more marketing opportunity for this particular consumer and 2. It helps us understand the loyalty of the customer.
Damian brings up the idea of customer loyalty as a potential metric to help you get an idea of your share of wallet. Gary brings up an example of coffee shops and how there are heavy users with large potential values. Damian asks the logical question “How do you find out peoples purchasing behaviors.?” Gary says the simplest way and the most obvious is just to ask them.
Next, Gary and Damian discuss another example. They jump from coffee to airlines.
The next two questions Gary answered are probably why you are here.
- “How do you capture more potential value?”
- “If you are only getting a small share what do you do?”
Listen to the episode to hear Gary’s in-depth answers to both of those questions.
After Gary answers those two questions Damian has one last question. “Is size of wallet a thing?” Damian brings up the great point that a small share of a very big wallet, could still be valuable even if you’re not getting all the potential.
If you are going to skip any of this podcast (which we hope you don’t) don’t miss Gary’s great wrap up of this topic at the end of the episode.
What follows is a lightly edited transcript of Episode 11 of the Inevitable Success Podcast with Damian Bergamaschi and special guest Gary Beck.
Transcript
Damian: Welcome to the inevitable Success Podcast, sponsored by BuyerGenomics where our goal is to help you, the marketer, make success inevitable. Each episode will discuss the craft of data-driven marketing, helping you uncover new and profitable ideas. You will also learn what works and what doesn’t work from top marketing professionals and thought leaders. I’m your host: Damian Bergamaschi and inevitable success starts here.
Yeah, so today we’re going to speak a little bit about share of wallet and what it means. It’s a pretty common term, and it’s part of the overall marketing equation. So, why don’t we kicked that off? Gary, share of wallet, what does that typically refer to?
Gary: The definition that I commonly hear is that share of wallet is calculated as the amount of money spent on your products versus the total amount spent on the category.
Damian: So at a high level, why is that important to me as a marketer?
Gary: Well, for marketers there are a couple of key reasons that it’s very important. One is that if I’m only one-third of your share of wallet, then that means that there is an opportunity to sell another two-thirds of that share to you. So, in other words, share of wallet, if it’s less than a 100%, indicates that there’s more marketing opportunity for this particular consumer. So that’s the first reason. The second reason which is a really important reason is it helps us understand the loyalty of the customer.
So if the customer is spending 100% of their disposable income on your particular product.
Damian: …for that category.
Gary: Right, in that category. So, what that means is that the customer is very loyal to your product, and loyal customers are exactly what we strive for. We want to have as many loyal customers as we can, of course. And that refers both to our, what we’ll call heavy users– the people who buy the most of our product– versus our moderate and light users of the product. For those customers who are only giving us some share of their wallet, and perhaps let’s call it less than the majority share of their wallet. Well, those customers are buying somebody else’s product for a reason. And as a marketer, we want to understand what that reason is so we can address it.
And when I look at those people who perhaps offer the most opportunity to us are those who are the de-loyal heavy users. So those people who are heavy users in our category, but they are purchasing perhaps from many other retailers, many other websites. They are customers who choose to purchase from people other than us, and it’s our goal to try and change those behaviors to convert the de-loyal heavy user into a loyal heavy user.
Damian: This is a really interesting topic to me. As I thought about it, the idea of potential value as a metric to help you gauge how successful you’re being at loyalty, it’s kind of different than– because normally you’d look at your loyalty program, and you’d say alright yeah, I’m increasing the value. But what should it be? What could it be? And unless you know the potential value by actually taking a metric like share of wallet, you don’t really know: are you getting 80 out of 100 as a score? Or are you getting 100 out of 100 on your loyalty metrics?
Gary: Yeah, it’s a great point, and I think there are so many good examples here, but let’s talk about coffee for a minute. Some people will drink one cup of coffee a day, and some people will drink three or four cups of coffee a day. So potential value for the person who is drinking four cups of coffee a day is four times that of the consumer of coffee who only has one cup a day. Understanding consumption patterns is very important. And of course, then understanding these specific brand affinities and purchasing patterns is a second component that helps us begin to get our arms around potential value.
Damian: So, how do you–is it primary research? How do you get this data?
Gary: Well, it’s a great question, and one of the simplest ways of getting the data is just to ask the consumer if you have the opportunity to do that. So, if there is a relationship with the customer, if they are filling out brand surveys, asking them provides surprisingly strong information about our consumption patterns. Now of course, particularly for large brands with tens of thousands, hundreds of thousands, millions of customers, typically you can’t ask everybody. That would be an overwhelming task.
So, another opportunity and perhaps the most common opportunity is to look at the data that you have– the actual transaction data that you have from a customer. So, we’ll go back to our coffee example, and somebody who purchases at a grocery store and who is typically buying a one-pound bag of coffee every week and shows that pattern week after week after week, we might look at that customer from a retail perspective and say that his potential value is on a trend to purchase 52 pounds of coffee in a year. And from that, based on the profitability of each bag of coffee, we can quickly assign a value to that customer in terms of what our current share of wallet is for that customer.
So we know that that customer is spending the equivalent of 52 pounds of coffee with us every year, and we have a metric. We have a number. Now, what we don’t know from that grocery store example is, how much coffee he might be purchasing elsewhere. But if we have survey data on even a small portion of our universe, we can then look at consumption behaviors from that survey data, match it up to the transaction data to help us provide an estimate on what our share of wallet is for that particular customer.
Let me jump to another example, and this one is very similar in the sense that we try to close the loop using our own transaction information. So I’m going to jump from coffee to airlines, and if I am an air-traveler who lives in New York City– Let’s say that American Airlines is trying to figure out the value of our air passenger, and Damian we’ll use you as our example here. So, if Damian travels to California one week. But we only see a one-way ticket to California, and then the following week we see Damien traveling from New York to Florida and then back from Florida to New York. We know that there is one segment that was missing, and that segment was American Airlines did not see a return trip from California back to New York. But the following week you were in New York, and you were flying to Florida.
So, in that example, we have a share of wallet where Damian flew three out of four segments with American Airlines, but one segment he did not. Potentially he took another airline. In fact, that’s probably the most likely explanation. And American Airlines can go through the process of looking at all of those travel events where there are missing segments that would help us understand how Damian, how you made it to your next flight event– your next travel event. So when we have that kind of information, we can quickly close the loop and say, Oh gee, American Airlines is getting 75% of your travel or whatever the percentage might be.
Damian: Right, At best. Right? cuz I could have just booked another trip entirely.
Gary: Absolutely. So there is the opportunity to understand loyalty. It’s the opportunity to understand the value, and then, if we’re lucky enough to have other research information about you- the customer- it gives us the ability to do some data analysis to make the best guess of how many flights might not be in our transaction records, and what your potential value might be based on that composite picture that we can build about your travel habits.
Damian: So, now that you know or have a sense as to what the potential value is or the share of wallet of your customer is, how do you go and capture that potential value?
Gary: Well, there are a couple of different things that we can do. We can start with our loyal customers. So, for our loyal customers, we want to do a couple of different things. One: we want to understand what that relationship is with that loyal customer. So what is it that makes us so desirable to those loyal customers today? And what seems to be the cadence of that customer in terms of purchasing events with us?
So on the first point, what makes us so valuable to that loyal customer? Why are they so loyal to us? Well, we want to look at the offers that they’ve purchased from us in the past. What is it that seems to appeal to them most? Is it purchasing our product when it comes to special sale or is it purchasing our products on a regular basis regardless of sales? So, those are the kinds of things that I would be looking at there.
Damian: let’s say you identified that you are not doing as good as you’d like to be around share of wallet. Let’s say you identify that you’re only getting a very small share of wallet. What do you do?
Gary Well, if you’re getting a small share of wallet, at that point you want to look at- I think I always start with offer analysis and transaction analysis. So, I want to see what appealed to that customer in the past. And perhaps what appealed to them in the past was a clearance sale. Well, a clearance sale customer shows us that they’re in the category, shows us that they’re willing to purchase a good deal, but it might also tell us that they are a very discriminating purchaser. And if we’re unable to sell them full-priced merchandise, it gives us some sense of their elasticity- their likelihood to purchase from us.
So, maybe for that particular customer, if we’ve tried repeatedly to give them our typical offering of goods and services, and they have shied away from us but only purchase on a deal, then we market to them accordingly. We save our communications to them for those special events where we can offer them good deals. So, that is the one thought that I have there. Just going back to our loyal customers for a second, for those customers who consistently purchase from us, they offer us a great opportunity to upsell them to other goods and services. So, going back to our coffee example, while they might be buying a pound of coffee every week, we might be able to sell them new coffee makers. We might be able to sell them other related coffee flavorings that they haven’t been exposed to before, but they are more receptive to just because they’re so loyal to our brand.
Damian: You made me think of– to use a different example. What if you’re a fashion company and all you sell is shirts or tops, and your share of wallet in the category may actually be pretty small because you also need to buy pants, right? So, you literally could not get to 100% share because you don’t– you know, one of the ways you can do that is to maybe offer more diverse products or let that customer know that you do offer other products as they only buy in one particular product category.
Gary: Right. Right. And if your offerings are limited that there’s always the opportunity to do some sort of affiliate marketing or partnership arrangement with another company. There are multiple ways that we can monetize our brand relationships. Always focus on brand equity, of course. We don’t want to do anything to discount the value of our brand, but if we can offer special arrangements for our customers that are a true value to them, it’s certainly an opportunity for us to work at.
Damian: So, another last question here on this. When I was doing some research on this, I was curious about– because I’m thinking about potential value, and I’m saying, Alright, I’d like to have customers that have a bigger share, but then I’m also thinking not everybody’s wallet is the same size. So is size of wallet a thing? And I’ll caveat, the only thing I could find on google when I looked that up was that the average wallet is 2.5″ x 3″. So, I don’t think that’s what I was meaning.
Because a small share of a very big wallet, that could still be a lot of value even if it’s not materializing as the high– you know, you’re not getting all the potential.
Gary: And that’s a great point. When we look at potential value, we always want to look at the ability of a person to potentially spend more with us, and we certainly can know that from the demographic profile of a customer and from the customers own behaviors. So, towards that end, certainly, potential value needs to incorporate the upside potential with each individual customer. It’s a great point. Absolutely. You’ll see in some equity companies will go out to prospect lists. And those prospects lists are always based on the likelihood of a person being able to take advantage of their services. So it’s a great point, Damian.
Damian: So, bringing it back around, what are the key things that listeners should take away from the discussion around share of wallet?
Gary: I think there are 3 takeaways for listeners. One is that share of wallet metrics can help marketers develop marketing segments and associated strategies for customers in their database. So earlier we talked about loyal heavy consumers and loyal moderate to light consumers, and again heavy consumers are based on the total amount of profit that customer might drive to our bottom line. So when we look at the percentage that they are spending with us, loyal consumers call for one type of marketing treatment versus our de-loyal customers.
Those de-loyal customers, some are potentially heavy category users, some are light category users. The de-loyal heavy category users offer tremendous upside for us, and we can convert them to our brand. So, in terms of segments, we have loyal customers. We have de-loyal customers. Some have high potential value; some have low potential value. Those de-loyal heavy consumers potentially offer us the greatest gain if we can understand what it is that we need to do to bring them over to our side. of the purchasing decisions that they go through. So, segments and value become very valuable to marketers.
And that will bring me to my second takeaway which is that a consolidated view of the customer is essential to support key metrics, and what that means is that from a data perspective, we need to be able to integrate all the information that we have about a customer particularly that transaction information. I come back to this again and again: the actual transaction information from our customers is perhaps the most valuable information that we have.
And that includes how they responded to our offers in the past. Have they purchased? Have they not purchased? What did they purchase from us? So, when we look at their transactions, we look at their data, and then we combine their useful syndicated data– third-party data– that helps us fill in the blanks on that customer. We get a unique view of what that customer is worth to us, and that allows us that consolidated view– that holistic view– allows us to assign customers to segments that give us the highest likelihood of success in marketing to them in the future.
And that brings me to my third takeaway. And the third takeaway is that when we have assigned those customers to segments when we understand what their potential value is when we have this consolidated view that gives us the complete picture that we can possibly have about that consumer.
Then the next step for us is to have ongoing communication efforts that allow us to explore what will work and what doesn’t work in marketing to that customer. So, people frequently refer to those ongoing efforts as customer relationship management efforts. And basically, what we are doing in those efforts is, we are orchestrating an ongoing set of experiments to help us understand: who that customer is, what offers are most successful with that customer, what types of communications are most successful, what timing of those communications is required to be most successful, and as we look at all of that, what channels should we be focusing on for that customer? Is this customer somebody who only purchases on the web or are they somebody who visits retail stores?
Is it somebody who is very responsive to direct mail? Again: which channels make the most sense? The only way for us to optimize our marketing communications over time is to combine that holistic view of the customer with ongoing experiments to help us understand what will work with that customer. And through those experiments, we have the greatest opportunity to maximize the lifetime value and the potential value of the customer over time.
Damian: Welp, I think that I am ready to go out there and find out how loyal the customers are for real by their share and go out there and start taking share of wallet.
Gary: That is what all good business school graduates are taught to do in business school. And it certainly makes our free enterprise system the successful system that it is today.
Damian: That is a great note to end on, Gary. Thanks so much.
Gary: Damian, thanks again for having me.
Damian: If you enjoyed today’s episode, we ask you please leave a rating and write a review. Or, better yet, share with another marketer. Be sure to subscribe to the podcast for new episodes. Also, check out the show description for complete show notes and links to all resources covered in today’s episode. If you’d like to speak to someone about any topics covered in today’s episode please visit BuyerGenomics.com and start a chat with the BG team today.
Host: Damian Bergamaschi
Special Guest: Gary Beck
Gary’s background includes over 30 years of analytics & database innovation for several leading Fortune 500 companies and Madison Avenue advertising agencies. Gary has been a frequent lecturer and author on the topics of database marketing and applied statistics. His articles have been published in DM News, Direct Marketing and the Journal of Direct Marketing. He recently was President of the Direct Marketing Idea Exchange and currently serves on their Board. Gary received his M.S. in Industrial Administration from Carnegie Mellon University.
