8
Revenue Models for Connected Strategies
The average American spends $384 per year on dental care between out-of-pocket expenses and insurance copays. That’s about $10,000 on dental care over three decades, on top of the hassle of scheduling appointments, getting to them, waiting, and the pain of the care—a pain point if there ever was one.
Now, imagine that you are the CEO of an oral care or medical device company. You invent an amazing toothbrush that detects plaque and cavities before dentists or patients do. Using the insights from this book, your company makes it smart and connected. It guides the patient in the brushing process and schedules a dental appointment if needed. Your toothbrush, let’s call it the Smart Connect XL3000, keeps customers’ teeth so much cleaner that it cuts dental care costs in half and reduces time spent in appointments. Let’s assume it costs $300 to produce and lasts five years, as long as the toothbrush head is replaced every six weeks. At what price would you sell the Smart Connect XL3000?
Before pondering your pricing proposal, be it $500 or $5,000, be it with a 50 percent gross margin or 20 percent more than the competition, note that the issue is about more than price. As far as our connected toothbrush, or any connected strategy, is concerned, the big-picture task is coming up with a revenue model.
We define a revenue model as one or several mechanisms that will compensate a firm by capturing some of the value that its products or services generate. In the case of our Smart Connect XL3000, customers benefit from healthier teeth, increased convenience from fewer appointments, and long-term savings on out-of-pocket costs and copays. If you sell the toothbrush for $400, almost all this value stays with the customer. Customers might love you for that, but you will only make a small profit that may not recover all the R&D investment you made to create the XL3000. If you price it at $5,000, however, very few will buy, destroying a lot of potential value.
Consider the following alternatives to selling the toothbrush with a fixed price:
You could sell the toothbrush for $300 and then make your money by selling the replacement heads with a healthy profit margin, a model familiar to anyone using Gillette razors.
You could offer a subscription model: for $10 a month, a new brush head is automatically shipped to the customer. In men’s facial care, this is the revenue model that led to the emergence of the Dollar Shave Club, a startup later purchased by Unilever for $1 billion.
Both revenue models might be innovative compared to just selling at a fixed price, but they have nothing to do with connectivity. As can be seen by the examples of Gillette and the Dollar Shave Club, both strategies are used by the (poorly connected) existing razor companies.
As a firm with a connected strategy, you have a long-term relationship with the customer, including a high-bandwidth information exchange. What revenue models can you design that could not be replicated by a company relying solely on episodic interactions? Consider the following options:
You could charge the customer ten cents per minute of brushing time. Because of the connectivity, your firm measures this so you can use this information as part of your revenue model. (That creates a financial disincentive to brush, an issue that can be handled by making your guarantee contingent on certain minimal use.)
You could launch an optional app that helps the customer in her brushing behavior for a one-time fee of ten dollars or a monthly subscription fee. Such a coach behavior connected experience might alert the customer when the toothbrush has not been used for twelve hours, or when the right-handed customer brushes too much on the left side of the mouth and too little on the right side, or when the customer exerts too much pressure (note that such apps already exist for Bluetooth-enabled electric toothbrushes from Oral-B, for instance).
You could have a sensor at the brush head that automatically detects its deterioration and reorders a new head as needed, resembling the printer toner example from chapter 4.
These revenue models allow you to appropriate some of the extra value that your product creates for the customer (beyond the value that the customer is currently getting from using normal toothbrushes). Are there more alternatives? So far, we’ve only looked at dividing the value between your company and the customers. But what about other parties? Let’s continue brainstorming other forms of revenue models:
Some dentists might not be happy about the Smart Connect XL3000, but others might pay you a referral fee if your toothbrush makes an appointment at their practices. How about insurers? You could give the toothbrush to the insurance companies for free and then ask to be paid a percentage of the savings relative to past patient expenses.
You could also collect data about brushing behavior, including what time your customer gets up in the morning and when (or what) he eats. You could sell this data to Starbucks (which could provide coffee just when customers are in their wake-up routine) or to the customer’s life insurance company, alerting it that its customer seems to be on an unhealthy diet or is smoking, creating a strong incentive for the customer not to engage in these activities.
Finally, through your connection to the customers’ bathrooms (not to mention their mouths), you could become a trusted partner in oral hygiene and have the Smart Connect XL3000 be the platform on which other oral care transactions are organized, earning referral fees when customers make purchases for toothpaste or dental floss.
The breadth of these models is already spreading across various industries, as the following real examples illustrate.
In the medication adherence domain, PillsyCap has developed a forty-nine-dollar pill bottle that reminds patients to take their medications or supplements. The bottle has a simple sensor to detect when it is opened and is connected to a cloud-based server. At AdhereTech, another startup with a similar technology, the pill bottles are given to the patient for free. Pharmaceutical companies and pharmacies benefit from the technology by selling more pills, and hospitals benefit from reduced readmission. Thus, a price of zero to the patient maximizes adoption and increases the value that can be shared among insurers, pharmacies, drug companies, and health care systems. But how can we be sure that the pill has been taken after the bottle is opened? Smart pill bottles have no answer to this question. The schizophrenia drug Abilify, a pill with an embedded sensor that tracks whether the medication has been ingested, has solved this problem. The pill’s sensor is connected to a wearable patch that feeds data to a mobile application.
Similarly, consider Fitbit. Fitbit has emerged as a powerful brand for its wearable devices. Given millions of Fitbit users, the company has access to remarkable data. For example, it has access to 105 billion hours of heart rate data, six billion nights of sleep, and two hundred billion minutes of exercise. Even though all this data is depersonalized, it is still of enormous value. Fitbit is preparing to launch digital health tools for the detection of atrial fibrillation, sleep apnea, and other conditions.
The purpose of this chapter is to discuss revenue models for connected products and services. As you likely have noticed, we are using the health care space as a case study. Entire books have been written about revenue models, so our focus is on the unique opportunities for connected strategies. We do this in four steps:
- We first provide a brief overview of revenue models and point to some of the key limitations resulting from episodic interaction.
- We then discuss what is unique about connected relationships that could be used as part of a revenue model. We point to the increased value that is created by connected relationships; the higher dimensionality of the pricing mechanisms, which reflects more data availability; and the different timing of payments that result from the longer relationship.
- We then link these idiosyncrasies of connected relationships to the revenue models and propose a framework to explore alternative revenue models.
- Based on this framework, we articulate a set of guiding principles for choosing a revenue model and illustrate those with examples from other industries.
We conclude the chapter by discussing challenges related to privacy, an issue that is particularly relevant in revenue models in which customers pay the firm not with money but rather with data.
Revenue Models: A Brief Overview
Consider the history of pricing in four episodes. The first episode is haggling, still common at many bazaars. The vendor does not preannounce a price and haggles with each potential customer.
The second episode is posted prices, such as those printed on items in a supermarket, listed in catalogs of mail-order companies, or displayed on billboards. Posted prices simplify transactions, increasing convenience and efficiency. However, they enforce uniformity across customers. If Selena is willing to pay $500 for a phone but Jackson is only willing to pay $300, price discrimination between the two is difficult. Similarly, if a retailer has only one phone left in stock, it might make sense to raise the price, but this is often impossible if the price is posted.
With the arrival of the online marketplace, we entered a third episode. It became feasible to adjust prices dynamically and intelligently. As consumers, we are most familiar with, and sometimes annoyed by, airlines doing this. A flight from Philadelphia to Boston might go from $99 one day to over $400 the next, reflecting seat availability and the airlines’ ability to identify us as a likely business traveler given our travel time. The internet also facilitates more complex pricing schemes, such as customer loyalty programs or group buying.
Yet despite these variations, from haggling at the bazaar to dynamic online pricing, traditional revenue models retain three limitations:
- Limited information: Given the episodic nature of the traditional (nonconnected) business transaction, there comes a time when buyer and seller have to agree on a price, be it for a toothbrush or a medication. The problem is that the value the buyer will derive from that transaction is still unknown at that time. Will the new toothbrush really reduce my need for dental services?
- Limited trust: One solution to dealing with limited information is to delay the final pricing decision until more information is available. For example, the toothbrush manufacturer could require the customer to pay another $500 if his teeth remain healthy. The problem with that solution is that in the case of a cavity, the customer will blame it on the toothbrush and the manufacturer will blame it on poor brushing behavior. Short of any monitoring data, the conflicting interests of buyer and supplier will erode trust between them.
- Transactional friction: Even if we could overcome the limited trust and find a way to determine whether the customer’s degradation of teeth is due to poor brushing or poor product performance, we still face the problem that the customer derives value from the toothbrush every day. Yet, traditionally, paying every day is a very costly practice. Every transaction requires an administrative overhead for payment processing, which likely will separate the customer’s timing of payment from the timing of deriving value.
With advancements in connectivity and the resulting emergence of connected relationships as discussed throughout this book, we have now entered a fourth episode of pricing.
What Is New with Connected Strategies?
In this fourth episode of pricing, the three limitations just discussed are overcome by longer-lasting, connected relationships facilitated by high-bandwidth information exchange. It is possible to use a whole range of additional variables as part of the revenue model. In other words, the price can now depend on factors that previously could not be used to influence the pricing decision. This includes information about the following:
When the product was used
Where it was used
Who used it
What benefits were derived from using it
What problems occurred while using it
In short, the resulting revenue models can now be tailored to the particular use case. As a result, the connected relationship allows the firm to eliminate the three limitations discussed earlier in the following ways:
The problem of limited information can be overcome by delaying payments until more information becomes available. The most common revenue model that results from this is referred to as pay-for-performance. Payments are delayed until more information about the user benefits are known.
The problem of limited trust can be overcome as constant information flow allows for the monitoring of actions taken by two parties with conflicting interests. Such verification is also necessary for the pay-for-performance model.
Because of low transaction costs, there is no reason to lump all financial transactions into a single payment, as is common in episodic relationships. Instead, we can use revenue models such as pay-per-use (pay every time the product is used).
Thus, connected strategies allow us to create completely new revenue models. For our toothbrush, we can make the price a function of how many minutes the brush was used per day, how many different customers used the brush (hopefully with different brush heads), or the degree to which cavities could be avoided. In other words, the constant connection and associated information flow allow us to increase the dimensionality of the pricing space. No longer is there a single price printed on the box; there now exist many different options for revenue models, including different ones for different segments.
The increased dimensionality is appealing at first because it provides us with many levers that we can pull to increase profits. But, just as would be the case for anybody going from the driver’s seat in a car to the pilot seat of an airplane, too many levers can be overwhelming. This raises the question, What are the general rules on how to form new revenue models, especially those that take advantage of connectivity? The following six guiding principles will help you answer this. Each is written as an action item and illustrated with our toothbrush example in the sections that follow, as well as with case studies from other industries:
- Think value creation first.
- Make pricing contingent on performance.
- Remember the ecosystem is broader than the supply chain.
- Get paid as value is created.
- Reinvest some of the created value into the long-term relationship.
- Be cautious when replacing cash payments with data payments from users.
Let’s look at each principle in turn.
Principle 1: Think Value Creation First
Consider the payments received by ophthalmologists for performing eye exams on patients with diabetes—a practice generally recommended annually to prevent diabetes-related blindness. Patients don’t particularly like these examinations because they require a time-consuming eye dilation for a retinal photograph to be interpreted by the ophthalmologist. The dilation can leave the patient with blurry vision for several hours. Patients who could otherwise get back and forth to the doctor on their own often need someone to take them home. Adherence rates for exams are low, no doubt contributing to the high incidence of preventable blindness among diabetics.
A recent study showed that a commercial insurer would typically reimburse $254 for an in-office examination involving retinal photographs—about $26 for the photographs plus some facility fees and the professional service. The same insurer would reimburse a total of only $16 for the photographs when the service was performed remotely, with no payment allowed for the interpretation of the images.
This example shows that many business relationships are destroying value because of poorly aligned incentives. For example, in health care, the payer is not the consumer. Insurance companies, short of information, are concerned that patients consume too much and physicians provide too much. In the diabetes case, insurers apparently liked the higher price, pain, and friction of the traditional exams because they deter patients from having them. (Whether such preference would backfire because of higher costs down the road is a matter for debate.) Thus, they were comfortable with high reimbursements for an office visit but would only pay a small fraction for an equally effective remote service.
Before we think about how to build a revenue model for any business, we should ask ourselves what actions maximize the value in the system. Once we know the desired actions, we can think about a revenue model that rewards people for those actions. In the foregoing cases, we want diabetics to get their eyes examined and everyone to brush their teeth.
Rather than just replicating the old relationships—in the eye case, the insurers being concerned about fraud by doctors and overuse by patients—we should use connectivity to ensure that every actor makes value-maximizing decisions. For example, in the construction industry, contractors and customers are often at odds from an incentive perspective, where contractors get paid through costs-plus pricing, including an allocation for time worked. This incentivizes contractors to take more time to complete a project, harming the customer both by delaying the project and by charging a higher rate. Because customers often interact with contractors only once, the reputational loss of such behavior for contractors is low. This hurts both customers and the contractors who are actually doing a good job. Now, connected market makers such as Angie’s List connect users via crowdsourced reviews to create transparency in a contractor’s practices. Contractors who repeatedly exploit their customers will receive lower ratings, which translates into fewer opportunities. This aligns contractors’ incentives more closely with the customers’ incentives because their future business depends on their reputation.
Principle 2: Make Pricing Contingent on Performance
When deciding to buy a product, customers face uncertainty about how good that product or service will be. Whether they are consumers or firms, customers don’t like uncertainty, and avoiding it can kill a value-creating transaction.
Pay-for-performance is one way to overcome the problem. Customers don’t pay for the product or service; they pay for (some of) the value it creates for them. This is possible in a connected world because we have good data about the customer.
In the toothbrush example, connectivity allows us to observe the health of the teeth. This enables us to give the customer a form of performance guarantee (“If your teeth are not in good health, you will not pay a penny”) while also aligning the customer’s incentive (“If you do not brush, our performance guarantee no longer holds”), thereby avoiding the incentive inefficiencies mentioned earlier.
In general, we define pay-for-performance revenue models as revenue models in which fixed transaction prices are replaced by payments contingent on achieving certain objectives. The following examples help illustrate their use in a wide array of industries:
As we noted in chapter 1, Rolls-Royce offers jet engines and accessory replacement services on a fixed-cost-per-flying-hour basis to airlines (“power-by-the-hour”), linking revenue with performance. This is aided by onboard sensors to track on-wing performance.
Power purchase agreements (PPAs) are widely used in the solar industry. Rather than asking customers to buy the solar panels, pay for installation upfront, and wait for energy savings to trickle in, PPAs allow customers to lock in the energy produced by the installation at a fixed cost per kilowatt-hour over the term of the PPA, without owning the equipment or paying upfront.
Some consulting firms are moving from a billable-hour model to a fees-at-risk model, where a portion of the consulting fee is linked to their clients’ results. This is in response to corporations’ increasing desire for impact and outcomes over pure insights.
Principle 3: Remember the Ecosystem Is Broader Than the Supply Chain
As a manager of a business, you often think about your supply chain. You buy components, manufacture your product, and sell it to retailers who sell it to consumers. Unfortunately, there are only so many degrees of freedom in this supply chain—only so many parties you could go to for revenue. Or are there?
Recent research in strategic management has moved the focus from the supply chain to the ecosystem. The ecosystem is much broader and includes all firms or other organizational and individual entities that have some interest in your product. To figure out which entities are in your ecosystem, ask yourself, “Who else would derive value from our connected toothbrush?” For this product, the list might include entities such as the following:
Insurance companies paying for dental care
Dental practices that understand that the new brush means potentially fewer cavities and the need to be on the toothbrush’s list for referrals
Toothpaste companies
Parents who are concerned about their children’s brushing habits
Consumer product companies that would love to learn about the habits of consumers
Comcast, Verizon, and other carriers that are happy about almost anything that consumes bandwidth
Many of these companies would benefit if the Smart Connect XL3000 succeeded. In other words, they might be willing to share with us some of the value they get from our existence.
There have been numerous examples in which firms provided a connected product or service to their customers and made their revenue from other sources besides charging the customer. Examples include the following:
Many of the peer-to-peer network apps that we discussed in chapter 7 are free to customers. Some companies occupy two positions in the ecosystem: they are the organizer of the peer-to-peer network and the producer of a complementary product that is used in this network (example: Nike running shoes).
In the world of connected security, insurance companies subsidize the installation of advanced fire alarms. Similarly, car insurance companies offer discounts for drivers who are willing to have their driving monitored.
In the world of personal fitness, many gyms now get more revenue from insurance companies than directly from the users sweating on their treadmills.
Principle 4: Get Paid as Value Is Created
For most products or services, customers derive benefit over time. You buy a car and drive it for years. You buy running shoes and run five hundred miles in them. In the traditional episodic relationship, however, payment typically happens upfront in one chunk. You could send Nike fifty cents every time you go running, but it’s likely neither you nor Nike wants to do that. More specifically, Nike would not trust you enough to give you a pair of shoes upfront without a payment guarantee in place. And you might not like the idea of sending Nike a payment every time you go running unless it was automated.
In a connected relationship these problems disappear, and the result is a victory over limited trust and frictional inefficiencies in payment. When your shoe talks to your phone and your phone connects to your bank account, you could pay Nike ten cents per mile. This is the pay-as-you-go model.
The world of hardware and software has seen a big shift from huge upfront transactions to pay-as-you-go models. Many firms no longer buy huge servers anymore, instead paying for “infrastructure as a service” from providers such as IBM or Amazon Web Services, paying on a per-use basis by the hour, week, or month. The key value for customers is a reduction of risk. Customers are never out of capacity, nor do customers have any idle capacity. They also have no upfront equipment or maintenance costs, which may be prohibitive for small companies that need cloud services. Another revenue model option is “platform as a service,” which is priced per application or per gigabyte of memory consumed per hour. Platform-as-a-service providers include Google and Microsoft.
Similarly, software has moved in many cases from a model of purchasing and installing it on local machines to “software as a service,” where customers pay based on features and use. Firms like Salesforce and Netsuite have adopted this revenue model.
Related to pay-as-you-go models are “freemium” models, where firms provide a basic model for free and charge for access to premium versions of their product. Dropbox and LinkedIn are examples. The free version attracts customers, while the premium version (“Ran out of storage space? Upgrade!”) is used to drive revenue. Freemium models must find the right balance between giving away enough features for free to attract customers (especially when customer benefits increase with network size, as with LinkedIn) and retaining significant improvements in the premium versions to persuade at least a fraction of the customers to upgrade. Many newspapers and some magazines with an online presence have gone this route as well. A certain number of articles can be read for free each month, then customers must subscribe to access more content.
What makes many freemium models feasible is the ability to manage micropayments efficiently. With the advent of smartphone apps, in-app purchases have made the micropayment model seamless. Many apps start out as free for users, offering basic services or experiences before prompting the user to unlock premium content by spending a small sum. In China, for instance, Tencent introduced QQ Show, which allowed users to design their own avatar that could be used not only in the instant messenger of the QQ app but also for the group chat, gaming, and dating functions within the app. The customization options included appearance, virtual clothing, jewelry, and cosmetics. These items could also be purchased as a gift for other members. Each item only cost a few RMB (pennies in US currency) but created a significant revenue source for Tencent, given its more than eight hundred million active users on QQ. (For more on Tencent, see the sidebar.)
One of the biggest sectors for micropayments is video game development. Gamers buy virtual currency with real money and spend it to upgrade their characters, buy special weapons, access hidden levels, and speed progress in the game. While individual purchases can be small (as little as ninety-nine cents), aggregate purchases can be staggering. It has been estimated that the free mobile game Clash of Clans has earned more than $3.5 billion through in-app purchases (of products that practically have zero cost of production).
Micropayments also allow peer-to-peer networks to create payments across members. Da shang, or virtual tipping, is an increasingly popular form of micropayment for Chinese netizens. For websites or social media platforms that support this function, viewers can choose to virtually tip content creators when they are wowed by the experience. Places that have adopted this format include blogs, video sites, and various social media platforms such as WeChat. The model encourages content creators to put up quality content for free, hoping to recoup the development cost through tips.
Whether it’s a freemium model or a micropayment method, they both capture one idea: get paid at the same time as your product or service creates value for your customers, because at that time, customers are often quite happy to pay.
Principle 5: Reinvest Some of the Created Value into the Long-Term Relationship
As we have seen, one great benefit of connected strategy is that you engage with your customers in a long-lasting relationship. From an economic perspective, that means the firm does not have to compete for every transaction with each customer. This translates into lower discounts and less spending on customer acquisition costs in sales and marketing. At the same time, value is also generated for the customers who no longer need to engage in costly and inconvenient searches and are provided with highly personalized offerings.
To create a sustainable advantage, it is important that at least some of the value that is created is reinvested, strengthening the repeat dimension of the connected strategy. Rather than taking the value and simply handing it back to the customer, as is done in traditional loyalty programs, the firm should seek to increase the level of customization it can provide. As we discussed in chapter 5, we can use the value created by connectivity to move further up the hierarchy of needs of our customers and establish our firm as a trusted partner.
At the level of a trusted partner, we are granted the authority of handling a broader need, be it oral care (the Smart Connect XL3000), education and career management (recall the example of Lynda.com), or wealth management. This responsibility is coupled with ongoing compensation, as illustrated by these examples:
The original benefit of becoming an Amazon Prime member for a yearly fee was free two-day shipping on many items sold by Amazon. Over time, Amazon has reinvested and increased the benefits to include access to Prime Video (including licensed and original content), Prime Music, Prime Reading, photo storage, and other features. Each of these additional services increased customer value and the information that Amazon received about its customers, allowing it to further personalize its offerings and to increase customer loyalty. In 2018, Amazon Prime exceeded one hundred million members, counting half of all US households among them.
As a result of repeated interactions, subscription services can curate and contextualize based on the learned customer’s preferences. Birchbox, a monthly beauty products subscription service, invests its created value in data and analytics to analyze what customers value most highly in order to better serve them with future products. This leads to lower churn rates, increasing the lifetime value of a customer and the ability to dedicate additional spending, which creates a positive feedback loop.
Principle 6: Be Cautious When Replacing Cash Payments with Data Payments from Users
Several of the most successful connected strategy companies have a seemingly odd revenue model: giving away their product. Google doesn’t charge for searches or Gmail; Facebook and LinkedIn do not charge you to become part of their networks; and TripAdvisor does not charge you to find the most popular attractions in cities around the world. But obviously, nothing is free. Users of these sites do not pay with their money; they pay with their data.
Somebody searching for the term spine surgery on Google is very likely to have back pain. Spine surgery is a very profitable product line for hospitals and private practices alike, so knowing that Joe Miller in Chicago is looking for spine surgeries is something that health care providers are willing to pay for. How much? With the clearing price for most Google AdWords costing pennies per click, it is notable that those concerning medical needs currently stand at around forty dollars per click.
As this example shows, one key revenue stream can come from advertisers, who can use the data to create more targeted and more effective advertising campaigns. For instance, navigation apps such as Waze do not make money by charging their users. Instead, they harvest user location data to display the most relevant location-based ads within the app. This determines what shops, restaurants, and other small businesses you see on the map as you drive.
Another key revenue stream can come from referral fees. For instance, Mint offers the convenience of managing all of a customer’s personal finances in one place. While it is free to use, Mint generates revenue based on referrals made to consumer product companies or financial institutions that sell financial products or credit cards. It also derives revenues from the aggregation and distribution of user data. Although unique identifiers are removed to preserve individual confidentiality, the pool of real-time financial data has tremendous value in assessing consumer trends.
The almost irresistible psychological attraction of free products, coupled with the opacity of what data is collected and how it is used, often obscured in long terms-and-conditions statements—“click here to accept”—has led to a veritable gold rush of firms trying to collect as much data as possible through whatever means available. Firms often collect data with the sole purpose of reselling the information. It seems like the Wild West out there. To us, this development does not appear sustainable in the long run … and we would be very glad if that turned out to be the case. It is not hard to imagine that rising societal concerns over privacy, coupled with technological solutions that provide customers with much more control over their own data, will create a higher burden of proof for the feasibility of revenue models that are solely based on paying with data. We can imagine that in the future, privacy settings will be moderated and negotiated by customer-owned software that sits between the customer and the various data-gathering apps, rather than being hidden within the various apps. At that point, customers will have the ability to release their personal data slice by slice if they see true value in doing so. Until this technological solution is available, we can only caution firms that want to use the reselling of data as their main revenue stream. To create a truly sustainable revenue model will require firms to navigate a minefield that is constantly shifting.
First, as we have discussed before, the goal of a connected relationship is to become a trusted partner to the user, requiring a much higher degree of trust than necessary in a traditional episodic interaction between customer and firm. For this, we propose, a firm needs to help customers understand the price they pay, even if this is not a monetary price but rather only in the form of data. Paying through data can yield value to both parties, but it has to be transparent to the customers what happens with the data they provide.
Second, several technology experts recently have proposed to replace the pay-with-data revenue model with a pay-for-data model. The argument is that customers should not only be rewarded for their user-generated content, such as teaching Google how to recognize the human voice and collecting traffic data in the connected car by getting a free product or service, they should receive a cash compensation on top of this. Though the price of data ultimately should be shaped by market forces, the almost unlimited appetite for data of artificial intelligence–based businesses makes the idea of paying customers for their data at least an interesting twist to the revenue model. For instance, it has been estimated that Facebook’s Instagram is worth some $100 billion and that its users have uploaded twenty billion photos. The following calculation is not meant to be scientific, but the numbers tell a story: a $100 billion valuation for twenty billion user-generated pictures—that equates to $5 per picture. Shouldn’t those who took these pictures get a part of the pie? True, Instagram has done much more than just accumulate photos. Nevertheless, more and more technology experts have raised the question of to what extent users should be compensated for the data they provide.
Third, when customers pay with their wallet, jurisdictional questions—for example, tax implications of such transactions—are fairly clear. When customers pay with data, this becomes much more complex. Suddenly, questions such as where the data is processed and where it is stored matter a lot, as reflected by the 2018 implementation of the European Union’s General Data Protection Regulation, which applies to all companies processing the personal data of customers residing in the European Union, regardless of the company’s location.
As you are creating your connected strategy—whether selling data becomes part of your revenue model or data collection is used purely to extend your own relationship with your customers—you need to deal with these issues actively. Given how quickly this field is changing, you have to keep abreast of rapidly changing regulations and update your answers frequently.
Six Principles for Designing Revenue Models in a Connected Strategy
We opened this chapter by asking you about the right price for a connected product. Our discussion in the remainder of this chapter emphasized that creating a good revenue model is more than what is suggested by the word pricing. Instead, designing a revenue model is based on identifying the various players in the ecosystem, understanding their (typically conflicting) objectives, and leveraging technology, all with the objective of maximizing value.
Value is maximized when the corrosive forces of limited information, limited trust, and transactional friction are overcome, which plays to the strengths of a connected relationship. In this chapter, we have articulated a set of principles that will help guide you in the design of your own revenue model:
- Think value creation first.
- Make pricing contingent on performance.
- Remember the ecosystem is broader than the supply chain.
- Get paid as value is created.
- Reinvest some of the created value into the long-term relationship.
- Be cautious when replacing cash payments with data payments from users.
How can these principles be implemented? The workshop that follows the next chapter will provide you with exercises to help you use these principles to create the revenue model that’s right for your business.