Clearly, a firm needs to earn the trust of the customer before it is permitted to manage a more fundamental need. This is why we put this at the fourth and highest level of how the repeat dimension transforms customer experiences into customized, connected customer relationships. There is an interesting circularity here: Only if you have a deep connection with a customer—relying on intensive data exchange—will you be able to address more fundamental needs. At the same time, unless you are able to address more fundamental needs, customers likely won’t want to engage in a deep relationship with your firm in the first place. Deep, embedded connections can be intrusive; customers will have serious and justifiable privacy concerns. Unless the value delivered to the customer is high, customers will not want to engage deeply or may feel that their data is being exploited without their consent. Thus, you won’t be able to jump straight to level 4 of customization. Level 4 is achieved in stages. The customer allows you access to a certain amount of data. Once you have proven to the customer that this data enables you to make the customer’s life better, the customer might grant you access to the next slice of data.
As you can see, the repeat dimension at all four levels of customization helps a firm to shift the efficiency frontier. A better understanding of customer needs, a better ability to translate those needs into specific product requests, and a better assortment of products that fulfill those needs precisely all increase the willingness-to-pay of customers. At the same time, a better understanding of demand allows the firm to avoid inefficiencies. Table 5-1 summarizes the four levels and their impacts on willingness-to-pay and fulfillment costs.
The Importance of the Repeat Dimension for Creating Sustainable Competitive Advantage
The repeat dimension of connected strategies moves the relationship from episodic transactions to a continuous relationship. Once the individual transactions are woven together into a customer-centric, unified experience (level 1), a firm has set itself up to serve its customers better and more efficiently. This improvement, and the associated shift in the efficiency frontier, is made possible by two learning mechanisms, summarized in figure 5-5.
TABLE 5-1
The four levels of customization created by the repeat dimension
Level
Impact on willingness-to-pay
Impact on cost
Level 1: Create unified customer experiences across episodes
Customer is treated as one person across channels and transactions
Avoids manual weaving together of experiences
Level 2: Improve customization based on past interactions
Ability to identify offerings that address the willingness-to-pay drivers most important to the particular customer
Avoids costly iterations in case of failure to fulfill the need
Level 3: Learn at the population level to enhance product offerings
Higher-valued offerings based on inferring customer needs
Data-driven approach to innovation
Level 4: Become a trusted partner to the customer
Addressing more fundamental needs allows for alternative solutions and early interventions
More efficient use of resources, as solution space is broadened
The first mechanism plays out at the level of the individual. As a firm engages in more interactions with that customer, the firm better understands the customer’s current needs and what products or services would best fulfill those needs. This is level 2 in our framework. For respond-to-desire customer experiences, the firm also can help the customer in understanding and expressing his or her needs more precisely. Thus, the first mechanism across levels 1 and 2 strengthens the dimensions of recognize and request.
While it is wonderful to have a deep understanding of your customer needs, this information is not very valuable unless you have the products or services available to satisfy those particular needs. The second learning mechanism operates at the level of the population (or the segment) by analyzing metadata. This learning creates a feedback into the assortment of products or even creation of new products in the first place: “Given what we have learned about customers of varying types, what would be the optimal assortment to carry or products to create?” In short, this learning mechanism improves the dimension of respond. This is level 3 in our framework.
FIGURE 5-5
The positive learning feedback loops created by the repeat dimension
Together these learning mechanisms allow a firm to enhance the personalization of its offering. The firm can create a better fit between the needs of the customer and the product (or service) that responds to this need. The more Netflix knows about Samantha’s viewing habits, the kinds of films her friends are tweeting about, or perhaps her upcoming vacation plans, the better Netflix is able to personalize her viewing recommendations (“Flying to Italy? Watch Tuscan Wedding to get into the mood!”). At the same time, as Netflix learns more about entire customer segments, it can optimize not only what kind of content to license but also what kind of content to produce. The data Netflix is able to gather from its more than one hundred million subscribers worldwide has allowed it to create more than twenty-seven thousand genres, including genres such as 20th-Century Period Pieces Based on Classic Literature, Absurd Opposites-Attract Comedies, and Biographical Fashion Documentaries. This fine-grained categorization, combined with viewer feedback and observed behavior at both the individual and the population levels, gives Netflix deeper insights into its audience than any movie studio could ever hope for.
Eventually, Netflix or other firms will be able to use this information to move up the hierarchy of needs of their customers and achieve level 4 of customization. Yes, a customer wants to watch a movie at certain times, but the deeper need might be entertainment. Once a firm understands a customer deeply, not only can it suggest movies, but it can also arrange for tickets to live concerts, automatically record sporting events, and play the customer’s favorite music in her house and car.
What makes the repeat dimension so powerful is that it involves positive feedback effects that over time can create a tremendous, sustainable competitive advantage for a firm. As we see in figure 5-5, the tight fit between customer needs and available products—that is, the high degree of personalization—leads to more value created by the firm, either in the form of higher willingness-to-pay by the customer or by higher efficiency. This allows the firm to provide more value to current customers, creating more future interactions with these customers, which increases the individual-level learning (the top feedback loop in figure 5-5). At the same time, the increased value allows the firm to attract new customers, thereby enhancing the population-level learning (the bottom feedback loop in figure 5-5). With more learning at the individual and population levels, the firm continuously improves the recognize, request, and respond dimensions, creating ever-increasing degrees of personalization. It is a process that feeds on itself and can allow a firm that gets ahead of its competitors to continue to expand its competitive advantage.
Moreover, as a firm is able to improve its knowledge about its customers’ needs and its ability to service these needs, it has the ability to move up the hierarchy of needs of its customers. Once the firm has transformed a series of customer experiences into a true relationship, customers will be much less likely switch to other firms. Firms with established connected relationships with their customers do not have to compete transaction by transaction for the business of their customers because they have created an effective lock-in. To woo customers away, competitors have to work much harder than simply offering an occasional better deal. As a matter of fact, if you are able to reach the status of a trusted partner, customers are quite likely to become advocates for you, telling their friends about the great service they receive.
In our foregoing discussion, we stress the learning feedback loops of the repeat dimension, as they have been most underappreciated and underexploited in our experience. As a firm gains more customers, three better-known posit
ive feedback loops can also arise that will further strengthen a firm’s competitive advantage.
First, as a firm attracts more customers, it will enjoy economies of scale: fixed investments can be spread over a larger customer base. For instance, Amazon’s investments in recommendation engines, website design, and technological improvements in Alexa can all be spread over its millions of customers, giving it a cost advantage over firms with fewer customers. Economies of scale allow a firm either to offer increasingly better products without having to raise prices, or to lower its prices to its customers—or both.
Second, as firms attract more customers, network effects can arise. Network effects exist when the willingness-to-pay of customers increases with the number of other users. For instance, the more that people use Facebook, the more likely it is that the next user will pick Facebook because all his or her friends are on this platform. That, in turn, increases Facebook’s user base even more.
The third positive feedback loop is a two-sided network effect that exists when more participants on one side of a transaction increase the value for the participants on the other side of the transaction, and vice versa. For instance, the more customers Apple is able to attract to its App Store, the higher the incentives for software developers to write apps and post them in the store. At the same time, the more apps that are available, the more customers are attracted. Likewise, the more that customers use a ride-hailing service like Lyft, the easier it is to attract new drivers; and conversely, the more drivers a ride-hailing service has, the shorter the wait times and the more likely that a customer will choose this particular service. All of these positive feedback effects create ever-increasing advantages as a firm grows faster than its competitors.
As we noted at the end of chapter 2, creating new and superior connected customer experiences is only the first step of building a successful connected strategy. If you can utilize technological advances to create a better customer experience, so can your competitors. But if you can go through the recognize-request-respond loop more often and learn more than your competitors each time you repeat the cycle, you can indeed create a competitive advantage that is sustainable. While all the firms we use as examples in this book have been innovative in creating new connected customer experiences, only those that are able to utilize the repeat dimension thoroughly, and create and exploit the various positive feedback loops, will be successful in the long run.
The Data Trust Challenge of Connected Strategies
As we depicted in figure 5-5, two feedback loops are at the heart of a connected relationship: by repeatedly having interactions with one particular customer, the firm is able to better and more efficiently serve that customer; and by obtaining information about many customers, the firm can better position itself for the future.
The resulting competitive advantage can lead to market share and profitability. That is great for the firm, but is it great for the customer? As firms perfect their service to a particular customer (upper part of figure 5-5), two investments have to be made. One investment is the data-collection and analysis effort of the firm—listening carefully to the needs of the customer and learning from one episode to the next. The second investment is made by the customer, who has to share information with the firm, be it actively by answering questions and expressing preferences (“Siri, wake me up every Monday at seven o’clock and order my coffee from Starbucks”), or by permitting passive monitoring by the firm (e.g., allowing a fitness app to track sleep patterns). So, the value that is inherent in a successful connected relationship, the force that allows the firm to shift the efficiency frontier, is coproduced by firm and customer.
This coproduction concept is not just a matter of semantics; it raises customers’ expectations of how much value they should receive from the relationship. Unless customers think they are getting a fair share, they may want to quit the relationship and you will never reach level 4, becoming a trusted partner.
More generally, firms will not be able to maintain the repeat dimension if they lose the trust of their customers. Because a rich information flow from the customer to the firm is central to a successful connected strategy, data privacy, data security, and transparent data use are absolutely essential.
Both the regulatory space and user attitudes toward privacy are likely to change over time. As a result, guidelines will evolve. Still, privacy guidelines from the Organisation for Economic Co-operation and Development and the European Union’s General Data Protection Regulation are good starting points for your considerations. To build a connected strategy, you will have to have policies that address these guidelines, including the following:
Collection consent: Whenever you collect data, it should only be with the knowledge and consent of the individuals you collect it from. Customers should have the right to withdraw this consent subsequently.
Data quality: It is your responsibility to keep data accurate and up to date for the purposes for which it is to be used.
Purpose: You need to state clearly the purpose for which data is collected before collection starts, and that purpose should not be changed unless you notify the customer.
Nondisclosure: The data you have collected should not be disclosed or made available to others except with the consent of the individuals it is collected from.
Safety and breach notification: It is your responsibility to protect data against unauthorized access or disclosure. Should a breach occur, it is your responsibility to notify your customers in a timely manner (within a few days).
Openness: Your customers should be able to easily understand who is collecting data and for what purposes.
Access: Your customers should have the right to access the data that you have collected and to have corrections made if the data is not accurate.
Data portability: Your customers should have the right to receive their data in a commonly used and machine-readable format and have the right to transmit this data to another firm.
Data erasure: Your customers should have the right to have their data erased and to stop further dissemination of their data.
Accountability: You must commit to being held accountable for following the foregoing principles.
Four Levels of Customization to Become a Trusted Partner
The repeat element in a connected customer relationship can often raise a chicken-and-egg problem:
To provide a customer the level of customization that fulfills her deepest needs requires a strong connection, including large amounts of data from prior interactions.
But to obtain the permission of the customer to collect large amounts of data requires that the firm is capable of providing a high level of customization and fulfilling the deepest needs of the customer.
How do you break into this seemingly closed loop? In this chapter, we have proposed that connected customer relationships get deeper and deeper over time by moving through four levels of customization:
Level 1 is about creating a unified customer experience by weaving together previously unrelated episodes. Taking a customer-centric view, potentially across channels, can create efficiency gains by eliminating data reconciliation, is more convenient for the customer, and increases the amount of information that a firm has available on a particular customer.
Level 2 uses the data from past interactions to improve customization and to learn which products or services are the most important drivers of willingness-to-pay—that is, to determine what is truly requested by the customer.
Level 3 is about developing the capability of delivering on those drivers when and where desired by the customer. Responding to customer requests in an efficient manner requires the firm to aggregate information across many customers. This population-level learning improves its assortment of product or services.
Finally, level 4 corresponds to a move of the firm to tackle more fundamental needs, evolving from offering rental cars to becoming a mobility solution or from being a prov
ider of accounting courses to becoming a source for business knowledge.
As a firm moves from one level to the next, it shifts the efficiency frontier and strengthens its relationship with its customers, thereby creating a competitive advantage. Even at the higher levels, the firm still needs to provide a more attractive option to its customers than its competitors, but it is freed from competing for every individual transaction. As we will see in chapter 8, this allows for revenue models that truly focus on long-term value creation.
6
Workshop 2
Building Connected Customer Relationships
This workshop will systematically guide you in applying the content of the previous two chapters and assist you in building connected customer relationships. It has three parts.
In the first part, we help you diagnose the customer experiences that your firm currently provides. This will formalize some of what you already did in the workshop of chapter 3 by using the recognize, request, and respond dimensions of connected relationships discussed in chapter 4. More specifically, we will break up this diagnosis into three steps:
Map the current customer journey of one customer experience.
Identify customer willingness-to-pay drivers and pain points.
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