Manage Your Customer Portfolio for Maximum Lifetime Value

How converting customers to closer relationships, leveraging them, and defending them can drive future revenue and lower costs.

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Traci Daberko/

Many companies have embraced the importance of creating closer, more valuable relationships with customers. But most do little to actively manage their portfolios of weaker and stronger relationships, other than keeping them diversified. They’re missing significant opportunities.

When we wrote about customer portfolio management (CPM) and our research into customer portfolio lifetime value (CPLV) for this publication in 2005, we emphasized the need to balance a “large, leaky bucket” of weaker customer relationships alongside closer and higher-value customer relationships.1 But according to our latest research, there is much more that businesses can and should be doing to drive future revenue. These actions depend on both market conditions and a company’s resources.

Growing a company’s customer portfolio requires continual investments across a range of weaker to stronger relationships. Our updated CPLV model shows that a clear understanding of when and how much to invest in, leverage, and defend different customer relationships is an essential determinant of both current and future revenues and costs.

Most companies lack a basis for developing this understanding. Business leaders seeking to optimally manage the ecosystem of customer relationships face a complex problem — and for most, de facto CPM practices are more likely to focus myopically on either current sales or their most valuable customers. However, our model shows that what’s really required is to integrate multiple dimensions (not just scale, but also variances in customers’ needs and wants) and tactics (relationship conversion, leverage, and defense) across the whole customer portfolio.

Our CPM framework and CPLV model enable executives to answer the following key questions as they seek to grow and optimize their company’s customer portfolio:2

  • How central is developing customer relationship strength to our strategy and competitive advantage? More specifically, when and how much should we invest in converting weaker relationships to stronger relationships?
  • How do we leverage these investments once relationships are created?
  • How do we protect the relationships we have created to minimize customer churn?

The CPM framework we’ve constructed and applied over the past two decades rests on a fundamental principle: It’s in a company’s best interest to view its market strategy as a long-term investment in the strength of relationships over an entire portfolio of current and future customers. Its core element is the segmentation of customers by their relationship with a brand — progressing from strangers to acquaintances to friends and, finally, to partners.

Our CPLV model illuminates how these relationships relate to the value proposition of a company by predicting a seller’s future revenues from and costs associated with the different relationship segments. These predictions are based on a set of parameters that includes market growth over the course of a product life cycle, unit cost over time, the cost and probability of deepening relationships, relationship premiums, and switching costs and probabilities. By running extensive simulations within the model, we have identified three explicit goals for an effective CPM growth strategy: relationship conversion, relationship leverage, and relationship defense.

Relationship Conversion

Customer relationship conversion is the process of turning strangers into acquaintances, acquaintances into friends, and friends into partners. It accomplishes two important goals. First, customer loyalty and profit per customer improve, thanks to an increase in strong relationships. And second, the addition of weaker relationships to a portfolio provides both a source of future loyal customers and economies of scale.

Customers’ perceptions of brand value develop along with relationship strength. (See “Different Relationships, Different Brand Value Propositions.”) Acquaintances view a brand as offering similar value to competing brands, and their purchase decisions are based mostly on a brand’s availability, familiarity, and price. Friends have a stronger preference for and connection with a brand, based on its perceived quality and uniqueness, and will make repeat purchases even at a higher price than competitive brands. Partners have an active relationship with a brand. They are willing to work with the brand to develop customized solutions and to adapt their own behaviors to the brand’s systems, services, and processes to obtain its value.

Growing a customer portfolio requires conversion strategies at all levels. Strategies for converting strangers to acquaintances follow the well-established process of creating awareness, encouraging the trial use of a product or service, and driving repeat purchases. Advertising and distribution are the keys to this early in a product life cycle. As markets evolve and become more heterogeneous, market segmentation, differentiation, and positioning become important practices, especially when attracting customers who are acquaintances or friends of a competing brand. Brand extensions help to add customers and build market share later in a product life cycle.

Converting acquaintances into friends requires building a brand’s qualities, communication strategies, and an effective customer relationship management (CRM) system to enhance differentiation, brand choice (share of wallet), and profit margins. This process may involve some forms of adaptation on the part of customers, such as a willingness to use a brand’s apps and loyalty programs. Converting acquaintances to friends is aimed at changing the customer’s perception from “The brand has equal value” to “The brand has more value” compared with competing brands. To convert acquaintances to friends, brands must develop a relevant value proposition that connects with customers’ underlying needs. This requires a deep understanding of the heterogeneity of customer demand — that is, the degree to which customers in any given market or point in time have different needs or wants.

Friends are converted into partners by incentivizing customers to adapt and invest further in their relationship with the brand. This is done by customizing the value proposition and/or reducing customers’ costs, thus creating a stronger defense against competing brands and a foundation for brand extensions. This process is increasingly important as products and services are delivered via digital means, and it often requires customers to share information. Partnerships foster knowledge sharing that promotes more successful innovation and customized value. A company’s investment in customer-friendly and highly functional IT systems and applications plays a large role in this process.

While stronger customer relationships tend to be longer lasting and more profitable than weaker relationships, it does not necessarily follow that companies should seek to convert all customers into friends or partners. Rather, the value of relationship conversion is closely tied to the heterogeneity of customer demand and a company’s ability to tailor its product and service offerings to that heterogeneity. The foremost need of business travelers, for example, is a comfortable hotel room and place to work, while leisure travelers seek more amenities and services.

As demand heterogeneity increases, so do the opportunities to create closer customer relationships. Such relationships have well-documented positive effects on a company’s performance, including market share protection, price premiums, lower transaction costs, lower marketing costs, and greater overall market value.3 The result should be a more valuable portfolio of customers that generates greater cash flows over time.

The experience of large hotel companies that serve a very heterogeneous population of travelers, who vary by country, culture, location, frequency of travel, sophistication, and usage occasion, bears this out. Until recently, digital intermediaries, such as Expedia and Kayak, and alternative providers, such as Airbnb and Vrbo, accounted for more than half of room bookings. While these intermediaries provided hotel companies with more distribution channels, the unintended consequence for the hoteliers was an erosion of customer relationship strength and a loss of control over inventories and pricing. In short, the entrance of digital intermediaries reduced friends and partners to acquaintances.

Hilton and Marriott, the market leaders, responded in two ways. They created larger portfolios of brands and locations, largely through consolidation, to meet the demands of a very heterogeneous global market. Through its merger with Starwood, for example, Marriott now boasts 30 brands tailored to very different market segments. Importantly, the hotel companies also created better online systems and loyalty programs that offer customers the benefits and experiences that foster relationship conversion (Hilton’s Honors program and Marriott’s Bonvoy program, for example). The result has been quite remarkable: Both Hilton and Marriott have more than doubled bookings by loyal customers through their websites and apps. These strategic moves improved inventory control, pricing power, and financial performance by not only restoring weakened customer relationships but also converting them to stronger relationships.

But what happens to the value of relationship conversion when demand and the resulting supply are relatively homogeneous, as they are for commodities like grain and natural gas? In this scenario, a company’s economies of scale and its ability to compete on price are the keys to profitability (versus differentiation, customization, and closeness to the customer), and that suggests that a larger portfolio of weaker relationship segments will be more profitable than a smaller portfolio of closer relationships.4

When we incorporated high versus low levels of demand heterogeneity and high versus low levels of economies of scale in our CPLV model, it confirmed these effects on customer portfolios.5

The accompanying table, “How Market Conditions Affect Customer Portfolio Lifetime Value,” shows that demand heterogeneity and scale have comparable impacts. CPLV more than doubles when heterogeneity increases and scale is low (from 100 to 212), and when scale increases and heterogeneity is low (from 100 to 224). The value more than triples when both heterogeneity and scale are high (from 100 to 332). This highlights the importance of both differentiation and cost as overriding market strategy considerations.

When demand heterogeneity and economies of scale are both high, acquaintances provide the primary source of CPLV early on, while friends and partners become the dominant contributors over time. All the results underscore the value of relationship conversion as heterogeneity grows.

Relationship Leverage

There are opportunities to leverage investments within each relationship segment. Investing in developing some level of brand awareness or familiarity for strangers, as through advertising, lays the foundation for establishing a relationship. Superior distribution and pricing strategies enhance purchase frequency and scale for acquaintances. Innovation and the continuous improvement of products and services enhance differentiation, purchase frequency, and margins for friends. Brand extensions and bundled offerings enhance the speed of innovation diffusion and lower marketing costs for partners.

The conventional view of the benefits of brand extensions and bundling is focused on the leverage they offer with regard to production costs, such as the ability to use an existing production line or service process to deliver a new product or service. But companies often overlook and thus underleverage the marketing benefits associated with closer relationships and, particularly, partnerships.

These benefits accrue from the greater willingness of partners and, to a lesser degree, friends to purchase brand extensions and bundles connected to an existing brand compared with strangers and acquaintances. Amazon has successfully leveraged its customer relationships to market and sell a growing array of product and service categories. Satisfied, loyal Prime customers are, for example, inherently more likely than new customers to follow Amazon’s recommendations and purchase additional products, at a lower relative marketing cost within a larger solution space.

To better understand the value of leveraging all customer relationships, we further extended our CPLV model to incorporate a brand extension three-quarters of the way through an initial product life cycle. We varied the probability of customers adopting the brand extension in a given market period, setting the probability lower in conditions of low heterogeneity of demand (where weaker relationships are more common) and setting the probability higher when heterogeneity is high (where stronger customer relationships are more common).

Even loyal customers will leave if their needs, preferences, or situations change — but defections are higher than they should be for many companies.

The table shows the resulting CPLV values for the focal brand across market conditions when adding a brand extension. While CPLV improves in all conditions, the brand extension has its greatest impacts when heterogeneity is high. The percentage of CPLV coming from acquaintances, friends, and partners in these cases is 26%, 29%, and 45%, respectively, underscoring the importance of both relationship conversion and leverage.

Relationship Defense

The use of CRM systems to continuously improve customer relationships and limit defections is commonplace. Nevertheless, we find that executives continue to be surprised and dismayed by high levels of churn in their customer portfolios. Some customer defections are clearly unavoidable: Even the most loyal customers will leave if their needs, preferences, or situations change. Nevertheless, defections are higher than they should be at many companies.

A key reason for this is an underinvestment in the information systems and data analytics required to understand the factors that affect customer satisfaction and relationship strength. Many companies do not completely understand why customers purchase their products and services or why customers leave. They also are unable to track how customers behave in response to changes in product and service performance. As a result, they do not know when or how to protect customer relationships.

To defend against customer churn, companies need two key inputs: impact and performance.6 First, they must be able to identify the statistical impact of variances in product and service qualities and costs on customer satisfaction and behavior, as well as financial performance. Second, they must be able to determine how well their products and services perform on those qualities and costs, both in an absolute sense and relative to competitors.

Moreover, companies must understand how the drivers of satisfaction and their relative impacts vary not only by relationship segment (friends versus partners, for instance) but also by sub-segments within a given type of relationship (such as business traveler partners versus vacation partners). An impact-performance analysis by relationship segments will reveal the following:

  • Competitive advantages that must be continuously maintained and improved to retain and convert relationships (high-impact, high-performance qualities).
  • Competitive vulnerabilities that require immediate attention to avoid defections (high-impact, low-performance qualities).
  • Product and service qualities to be maintained and/or investments to be reduced to lower costs (low-impact, high-performance qualities).
  • Product and service qualities that can be ignored or eliminated (low-impact, low-performance qualities).

A granular understanding of the variance in performance qualities and its consequences enables companies to pinpoint the root causes of customer defections. When these causes are known, companies can undertake product and process responses, which often span functional and operational boundaries.

When Sector Alarm, a supplier of home alarm systems across Europe, saw a significant and unexpected increase in customer churn, it took a close look at its customer feedback. The data revealed that the defections were directly related to a particular alarm system that suffered from frequent false alarms. The company used that knowledge to communicate the issue throughout the organization, improve its alarm systems, align incentives from manufacturing to sales to service, and bundle services (adding an automated system to notify customers when to change batteries, and a battery replacement service). The result was closer, more profitable customer relationships.

We investigated the effect of an increase in defensive retention activities in our CPLV model through the customer retention probability from period to period. In our baseline scenarios, the focal brand has the same probability of losing customers in a given period as its competitors. The table shows the impact of a 20% increase in the focal brand’s investment in relationship defense (retention activities), which decreases the probability of losing a customer from one market period to the next. Relationship defense improves CPLV in all conditions.

The greater the heterogeneity of demand in a given market, the greater the long-term value of closer relationships.

It’s hardly surprising that defense increases CPLV as demand heterogeneity grows, given relationship management’s focus on retaining loyal customers. What is interesting is that defense has close to the same impact on CPLV as economies of scale grow. This is perfectly logical within the integrated framework of CPM. When CPLV is more reliant on a larger number of weaker relationships (low-demand heterogeneity) and scale economies (volume) to reduce costs, retention has a large impact. The negligible impact of retention when both demand heterogeneity and economies of scale are low is a function of low margins for each customer (predominantly acquaintances) and marginal cost advantages with higher volumes.

In the end, CPM boils down to investing in building relationships with current and future customers. Setting specific goals regarding relationship conversion, leverage, and defense is a natural place to start, but it requires a clear understanding of the heterogeneity of customer needs as they emerge over time and of economies of scale. The greater the heterogeneity, the greater the long-term value of closer relationships. The greater the economies of scale, the more important it is to include weaker relationships in a portfolio to both lower costs and provide a basis for future loyal customers.

Companies need two things to inform and act upon this understanding. They need customer information systems capable of revealing the impact and performance of a brand’s qualities and costs to guide relationship conversion, leverage, and defense. And they need organizationwide alignment around the basic principle of CPM to ensure that production, marketing, and sales strategies are viewed as an integrated investment in relationships across an entire portfolio of current and future customers.

CPM enables an integrated approach that balances competing priorities, most importantly the future revenues from investments in closer customer relationships versus the economies of scale from current sales. Such an approach requires a careful consideration of market conditions and company resources. Do this work well, and it will pay off both now and in the future.



1. M.D. Johnson and F. Selnes, “Diversifying Your Customer Portfolio,” MIT Sloan Management Review 46, no. 3 (spring 2005): 11-14.

2. M.D. Johnson and F. Selnes, “Customer Portfolio Management: Toward a Dynamic Theory of Exchange Relationships,” Journal of Marketing 68, no. 2 (April 2004): 1-17.

3. A.S. Otto, D.M. Szymanski, and R. Varadarajan, “Customer Satisfaction and Firm Performance: Insights From Over a Quarter Century of Empirical Research,” Journal of the Academy of Marketing Science 48, no. 4 (May 2019): 543-564.

4. Johnson and Selnes, “Customer Portfolio Management,” 1-17.

5. The parameters set for the CPLV model affect its estimates, but the estimates are consistent with results realized when applying the CPM framework in companies. Details regarding the model’s parameters are available from the authors.

6. M.D. Johnson and A. Gustafsson, “Improving Customer Satisfaction, Loyalty, and Profit: An Integrated Measurement and Management System” (San Francisco: Jossey-Bass, 2000).

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Stuart Roehrl
An exceptionally solid and thorough explanation of the subject of Customer Portfolio Management.  An outstanding reference guide.
Stuart Roehrl