Customer Portfolio Management: An Interview with Michael D. Johnson, Marketing Department Chair, Wisconsin School of Business

Interview with Michael Johnson, Marketing Department Chair at the Wisconsin School of Business and the co-author of “Managing the Customer Portfolio”.

At the time it just seemed to make common sense.

Why spend all this marketing money chasing after new buyers while ignoring the customers you’ve already got? Why not redirect some of that acquisition budget toward retention of existing customers and simply get them to spend more with you?

The logic was so obvious that when Leonard Berry presented his paper on “Relationship Marketing” in 19831 he never thought of it as a “breakthrough” idea. His intention was to simply remind marketers that their job was not only to find new customers, it should be to retain the ones they already had. In that era marketers never gave much thought to what happened after the sale. They figured it was the job of customer service to keep customers happy.

Berry positioned “relationship marketing” as a way to create extended value for customers. He urged businesses to shift their marketing strategy from a narrow focus on demand generation to more of a customer orientation. Part of marketing’s mission, he proposed, should be to win “lifetime customers” through enhanced service (what we have since come to call customer experience).

When Berry published his paper it was the first time the term “relationship marketing” had ever appeared in the academic literature. For many years afterward, his idea lay more or less dormant, up against the mass market dogma of the time. By the early 1990s, however, relationship marketing had evolved into a rising school of thought, endorsed and promulgated by such influential heavyweights as Phil Kotler, V. Kumar and Jagdish Sheth, amongst others, who foresaw the impending demise of the classical marketing model due to media fragmentation and the collapse of the mass market.

Relationship marketing got a further boost at the start of the 2000s when the concept of customer equity2 began winning a growing number of proponents. Its central premise was that customers should be thought of as a business “asset” whose value appreciates over time. The true value of a business lay in the future cash flow of its “portfolio” of customers. A bedrock principle underlying this idea was that not all customers are of equal value – some are worth investing in more than others. Thus marketers were urged to pay particular attention to the most valuable customers to avoid losing them.

This new “customer equity” model provided the fiscal framework for relationship marketing. But it never had much chance to enter mainstream thinking, trampled by the rush of marketers to embrace Web 2.0 and the mobile and social media revolution that followed. Even to this day most brands are far more interested in gaining market share than maximizing the lifetime value of existing customers. And that is because most marketers are still conditioned to own as much of the addressable market as possible. So they continue to give disproportionate attention to market growth at the expense of existing customer relationships. Which is why 42 years after Berry published his paper, marketers still lack a cohesive planning framework for “customer portfolio management”. Even more disheartening, they have yet to crack the code on striking the right balance between acquisition and retention spending.

Yet, according to Michael Johnson and Fred Selnes in their book “Managing the Customer Portfolio”, the companies that succeed in future will have mastered the practice of strengthening relationships with customers. In their book they present a systematic framework for converting weak relationships into stronger ones. The key, they believe, is to segment customers into “relationship segments” based on the degree of customer satisfaction, attitudinal loyalty and brand preference along with key behavioural indicators such as retention and growth trajectory.

Michael Johnson is a renowned academic and prolific scholar, having written six books. He achieved early fame when he helped to develop the first customer satisfaction index in 1989. His methodology and econometric modeling subsequently laid the groundwork for the launch of the American Customer Satisfaction Index in 1994.

Stephen Shaw (SS): Is this a good time to be a marketer or a bad time?

Michael Johnson (MJ): Well, I think it’s definitely an interesting time. Marketing has been slow to evolve in some ways but the pace of change is going to be pretty incredible in the years to come. We had an AI symposium last week here at the school and as one of the practitioners put it, AI is not going to replace people in marketing, but marketers who know AI are going to replace those who don’t. So AI is going to have its influence.

SS: For a while there, the CMO title had fallen into disrepute, even being eliminated in some cases. Is that related to the fact that the C-suite doesn’t actually understand what marketing does anymore?

MJ: Yes, but it also gets into what we mean by a Customer Experience Officer and what they do. One of the biggest frustrations today is we have 30 years of research that shows the payback on customer satisfaction but it’s pretty lost. One of the projects I’m working on right now is showing the stock returns to firms with high customer satisfaction and it’s astounding. Over the last 20 years market leaders in customer satisfaction have beat the S&P benchmark by fourfold. But it’s been very hard to get that message across. We tend to want simple solutions and opt for what’s best in the near term. At the end of the day, a market orientation focused on customers is the best long term strategy.

SS: In your classroom, how do students feel about marketing as a career choice?

MJ: Well, I think what we see here at the Wisconsin School of Business is students looking at marketing as part of their overall training. A lot of double majors, we even have some triple majors. One of my very best students in the fall semester is a double major in supply chain management and marketing.

SS: You are a renowned expert on customer satisfaction. What led you to make Customer Portfolio Management the focus of your latest book?

MJ: I was teaching an executive seminar on the impact of loyalty on performance. In the discussion afterward, one of the executives at a large U.S. Telecom company said I’m convinced by Professor Johnson’s lecture, and we should increase satisfaction and lower churn, but I’m only going to want to lower it by 5%. To put that into context, this was back when cell phone contracts were turning over every six months – people were just looking for the best deal. One of the other executives looked at the guy and said, didn’t you just hear what the Professor said? Shouldn’t you lower it more than that? And this Telco executive replied, well, you got to understand what might happen if I do that. I’ve got tens of millions of customers and tens of thousands of employees and hundreds of offices around the country. I wouldn’t have a very big business.

So I used to teach with a guy named Chris Hart3 who was at the Harvard Business School at the time. And Chris used to talk about these “watertight buckets”. He said you want to plug the holes because replacing lost customers with new customers is not profitable. And the firms that did this started focusing on those 10 or 20% of the customers who are 80, 90% of the profit. Fine. But they wake up five years down the line with a smaller portfolio, a smaller business. So the Telco executive was simply saying, I’ll have a smaller business if I try to push this too hard.
So then my co-author Fred Selnes4 and I started thinking about this. We really needed to put satisfaction logic into the broader context of what a business is trying to accomplish. And that led to some work we did with a company called Panfish, a big fish farming company, now part of a much larger company called Mowi5. This company had about 25% of the global salmon and trout market. Really huge. But they had a problem which was they couldn’t control the size and quality of a catch when they were farming salmon in the North Sea, in the fjords of Norway.
So they told us they had three different kinds of customers: Partners, friends and acquaintances. Partners want customized solutions and they’re willing to pay more for them. They need the best salmon in the catch because they were salmon smokers. And the infrastructure which they use to smoke the salmon needs a particular size salmon which also happens to be the best tasting salmon. If a salmon is too big, it tastes old. If the salmon is too small, it doesn’t have enough fat, it doesn’t taste good. So they wanted the medium sized one. And so Panfish needed to come up with a customized delivery system, supply chain, and special product for these partner companies.

They also had these companies that buy in regular large volumes. And these were the “friends” – they’re good customers, they buy high volume, they buy regularly and they will buy much of the rest of the catch – a little bit bigger, a little smaller fish. The rest of the fish they could sell at a much lower price with fewer benefits – mainly transactional customers who were the “acquaintances”.
So we thought this is the way to start thinking about how to manage a whole portfolio of customers. We really have to be thinking about making long term investments in customer relationships. Because the transactional customers are not always poor investments. They can grow over time to become the “friends” and the “partners”. Some of them will always be acquaintances but they also help spread the costs. So that’s what got us thinking about the need to start studying customer centricity from a portfolio standpoint because it really connects with the broader goals of the firm.

SS: The concept of customer portfolio management has been around 20 years or so. Yet it’s never gone mainstream. Why do you think that’s the case?

MJ: The complexity of it. In 2004 we published an article in the Journal of Marketing featuring a model called “Customer Portfolio Lifetime Value”. As opposed to it being an empirical model, a database model, it’s a simulation model. It’s very similar to what finance people do when they’re evaluating any type of investment. You have 100 or so variables you throw into a “what if” model to see what the valuations might be in the years ahead.

So Fred and I found ourselves using that model three years ago, simulating different strategies. What happens if the focus is just on relationship conversion – turning “acquaintances” into “friends” or “friends” into “partners”? Let’s compare that to an offensive strategy where it’s all about generating sales volume. Let’s just put as much water in the leaky bucket as possible. And then we compared that to a strategy where the focus is more on customer satisfaction than on growth per se. And the interesting thing we found through these simulations is that the defensive strategy is the most profitable strategy under most circumstances – that it really was very consistent with what researchers were finding in the customer satisfaction area about the ties to business performance – because it grew the size of the portfolio – adding new “acquaintances”, converting them into “friends”, while increasing the profit margins on customers. So that led us to our conclusion that there’s more value in a large leaky bucket of customers than in a small, watertight one. In the long term, if you don’t continually put some water in the bucket and allow some of it to leak and some of it not to leak, you’re not going to grow the portfolio. The portfolio will end up evaporating over time.

SS: I haven’t heard you mention profitability. Aren’t there so-called “demon customers”6 who are a drain on profitability, who buy on price, who are brand switchers? I presume it must be OK to let them “leak out” of the bucket?

MJ: Well, yes and no, because satisfaction is an optimization problem, it’s not a maximization problem. I was doing a study with Chris Hart on hotels years ago, and it involved working for a brand company, as opposed to the owners. And there’s a big difference between whether you own the hotel or you’re the flag on the hotel. If you’re the flag on the hotel, you want to maximize satisfaction because you’re selling a brand. But if you’re the owner, you want to optimize it. And we said, well, if there’s going to be a payoff in satisfaction, it’s going to be higher at hotels where there is a future revenue stream to capture. There’s going to be business travelers, vacation travelers, who are going to go back to the same location as opposed to the transactional customer, or transient customer, who’s passing through a small town on the only trip they’re going to make and happens to stay in a hotel. So a small market, rural hotels, the optimization point is going to be much lower. And that’s exactly what we found.

But you have to connect satisfaction to a business performance metric that will show you that it is profitable. We do that by understanding the relationship between the loyalty metrics that we capture and actual retention. To go back to your comment about “demon customers”, the relationship segmentation should show you that you’re not going to invest in some “acquaintances” the way you are in others.

So my other colleague Anders Gustafsson7 and I did a big study for Telia which was a big telecom in Sweden. We were using panel data and connecting customer satisfaction with actual retention. And we found it was the customers at the higher end of the satisfaction scale whose loyalty you could increase even more. There were customers at the lower end of the satisfaction scale who were always just going to search on price. So you had to be very careful in your investment in those customers because they weren’t going to pay off as much. So ultimately you have to connect your satisfaction and loyalty metrics to a business performance metric that ultimately gets to profitability.

SS: How do you define your three relationship segments, “acquaintances”, “friends” and “partners”?

MJ: Well, you can think about it in terms of how a relationship grows over time between buyers and sellers. As firms differentiate and provide greater value to the customer, they can start charging a higher price. And this is where you can start to develop a friendship with a customer where you can charge a slightly higher price. The price elasticities are such that you can get more profit from those customers. So those are the “acquaintances”. But you can create a friendship where someone is going to not just see you every once in a while, but will want to come back and visit you more often. But among those “friends” are people who are going to appreciate more customized solutions and want to connect more with you.

So it’s really about do you have a standardized product that’s bought mainly on price, which is the “acquaintances” – or do you have a more differentiated product that you can charge a little more for and customers are willing to pay, which are the friendships? Or do you have a highly customized solution that each side, the buyer and the seller, are willing to invest in to create a true partnership.

SS: When you’re creating the relationship segments, what types of variables beyond current and potential value tend to be key determinants?

MJ: Well there’s a whole list, but there’s a couple of them that we have found particularly valuable. One is brand preference. All things being equal, would you prefer this brand to another brand? The other is share of wallet.

One of our favourite case studies is about a home materials retailer, a Nordic company, that has these 30 stores. We used these two variables, brand preference and share of wallet, and it yielded four groups,. Two of them were “acquaintances”. And so this is important because it shows you can have low volume acquaintances and high volume acquaintances. And the danger with high volume acquaintances is they can switch in a minute if they get a better price.

Once we had those segments, we did a simple plot across all the stores in this chain of what the percentage of “friends” and “partners” was versus the percentage of “acquaintances”. And across the stores the difference was remarkable. There were stores with close to 90% “friends” and “partners”, which happened to be the most profitable stores in the chain. And there were stores with 12-13% “friends” and “partners” and the rest were all “acquaintances”. Yet all these stores had the exact same marketing programs. So what was driving this difference? There was a couple of main things. A big factor was store management. Another was competitors nearby better serving the needs of the customers.

So that led to the management team wondering what lessons to take from the best performing stores and translating them to the weaker performing stores. And that dramatically increased the profitability of the company. But it starts with a simple segmentation scheme by relationship strength.

SS: How do you see needs based segmentation and relationship segmentation working together?

MJ: It really should start with relationship segmentation and underneath that would be the needs based segmentation. So you can think of that as a matrix. One axis is going to be relationship strength – “acquaintances”, “friends” and “partners” – and then under that are the different needs based segments – and then on the other axis is going to be all your brands. And so it’s really about mapping your brand strategy to that relationship strategy.

SS: In the book you talk about a couple of concepts – “cumulative satisfaction” And “impact performance analysis”. Can you elaborate on those two concepts?

MJ: Let’s talk first about transaction specific satisfaction and what we call cumulative satisfaction. Transaction specific satisfaction is based on the common surveys you get when you had the last trip on Air Canada or Delta Airlines, or your last visit to a Marriott hotel: how was your experience? They’re more valuable from a service process design standpoint. They’re part of journey mapping. And journey maps have become more popular as the digital economy has grown. But journey maps have been around for 30-40 years – Disney and SAS Airlines were doing this a long time ago. So the transaction specific measures are good “point in time” measures and they can tell you where the moments of truth are in these process journeys that you can then fix. So very good for service process design, but they’re not going to tell you necessarily what the customer is going to do next.

What you really need to ask is overall, how satisfied are you to date? And that’s, a Bayesian updating function. It’s Bayesian statistics8. You have an impression, it gets updated over time, your expectations adapt. And that’s what’s more likely to determine what customers are going to do next.

The impact performance analysis comes out of the output of satisfaction models where you know what is actually driving that satisfaction. So you have service quality attributes and benefits, you have product quality attributes and benefits, you have price and value, you have all sorts of different things to drive satisfaction. Well, what’s the impact on performance? To be profitable, I have to understand where I’m going to get the biggest return on investment. The biggest return on investment is likely to be those areas where the impact is high and my performance is low. These are my competitive vulnerabilities. This is where I’m going to lose customers. In contrast, the high impact, high performance items tell me where my competitive advantages are. If I can sustain those over time, I have a more sustainable advantage. But they’re not necessarily the things I need to invest in first. It’s those vulnerabilities that I need to invest in first.

So how much effect is it going to have versus where am I? So if the impact is high, but the performance is low, I better fix it. If the impact is high, but I’m actually doing pretty well on that, I may not have to worry about that right away. If the performance is high, but the impact is low, it can mean everyone, including my competitors, perform equally well. So it becomes a non-differentiator. It’s called a “must be” quality. There’s something called the Kano model9, which I’ve always liked, which says ultimately, over time, a surprise and delight attribute becomes a performance attribute. It becomes an expected attribute.

SS: Table stakes, in other words.

MJ: Yeah, you drive the variance out of it. So you have to be careful. The interesting one though is the low impact, low performance one because it goes back to your profitability question. I don’t want to necessarily be investing in these things if it’s not going to have a payback, if it’s not going to have impact. In one of the case studies in the book, we talk about an independent tire retailer and the tchotchkes in the store. Well, the tchotchkes in the store are great, but don’t put too much money in them because there’s no return on investment. Is it a quality tire and is it at the right price?

SS: I do want to talk about loyalty measurement because you don’t mention NPS in the entire book. Was there a rationale behind that?

MJ: No, it’s a good point. The question is, are you measuring loyalty as a behaviour or are you measuring it as an attitude? And there’s been an evolution. A lot of the research over the years has used loyalty as a behavioural intention. And we’ve actually found good ways of translating those behavioural intentions into actual loyalty. But when we can we avoid that step only because we have the actual data, we have the actual retention rather than the attitudinal loyalty. And that is with the emergence of panel data, where we can look at actual churn. That may be the only reason why we’re not measuring loyalty as an attitude.

SS: I thought one of the more intriguing aspects of the book is your brand relationship market matrix. Because I think to some extent it cracks the code on this challenge between managing a product portfolio and brand management. Can you explain how your matrix works?

MJ: Yeah, and we touched on it a little bit earlier, but in companies that have large brand portfolios, for multiple needs based segments, how do I market to different relationship segments? How does a Marriott, for example, take its 36 brands and market them to six different segments in their loyalty program? How does a Delta airline, which I think has four or five levels in their loyalty program, market their partnerships with other service categories?

SS: If an organization embraces the concept of relationship segments, how do you see marketing organizing itself around that new model?

MJ: Well, I think in the simplest way it needs to be flatter. It can’t be a silo in the organization. It needs to cut across everything from supply chain to finance. The CFO needs to understand how this is going to affect long term revenues, and the CEO, the supply chain people, the Chief Operations Officer, they’re going to need to know how what they’re doing is going to be driven by what we’re learning from customers.

You know, it really goes back to one of the first slides I show any class or any executive seminar that I teach is a 71 year old quote from Peter Drucker which says, “marketing is basically looking at the entire organization from the perspective of the customer”. One of the best relationship segmentation schemes I’ve ever seen was a large chemical international chemical company that developed great strategies for their “partners”, “friends” and “acquaintances”. And you know where the whole thing fell down? The sales force. The sales force was still selling on price.

SS: So is marketing going to be called something different going forward that will put it more at the center of corporate strategy than it is today? Is the salvation of marketing to embrace the core principles that you’ve outlined in this book? Because effectively that becomes the strategy of the entire business, not just marketing.

MJ: You may have said it better than I. As I said at the start of this conversation, it is an exciting but scary world ahead. But marketing’s not going to go away. We just need to start thinking of it as a customer market orientation.

1. Berry introduced the term in a paper titled “Relationship Marketing” in a presentation to the American Marketing Association’s Services Marketing Conference.
2. Roland Rust, Valarie Zeithaml, and Katherine Lemon are credited with coining the term customer equity in their book “Driving Customer Equity” (2000).
3. Chris Hart is an adjunct professor of marketing on the executive-education faculty at the University of Michigan’s Ross School of Business.
4. Fred Selnes is professor at BI Norwegian Business School. He is co-author of the books “Customer Portfolio Management” and “Marketing Management: A Customer Centric Approach”.
5. Mowi, known as Pan Fish prior to 2007, is a Norwegian seafood company with operations in a number of countries.
6. The term “demon customers” was coined by Larry Selden and Geoff Colvin in their book “Angel Customers & Demon Customers”. It means a segment of customers who are unprofitable and can even lose a company money.
7. Anders Gustafsson is Distinguished Professorial Fellow at the University of Manchester’s Alliance Manchester Business School (AMBS) and Professor of Marketing at the Norwegian Business School (BI).
8. Bayesian statistics is a method of statistical inference that updates the probability of a hypothesis as more evidence or information becomes available.
9. The Kano model analyzes customer preferences and prioritizes product features based on their impact on customer satisfaction.

Stephen Shaw is the Chief Strategy Officer of Kenna, a marketing solutions provider specializing in delivering a more unified customer experience. He is also the host of the Customer First Thinking podcast. Stephen can be reached via e-mail at sshaw@kenna.