Bill Gurley has a great post about monetizing social networks. He analyzes TenCent, a Chinese IM company, and uses virtual world examples to demonstrate how social networks could monetize their huge base of users. The model has a few different names: freemium, digital item, micropayments. The New York TImes also has an recent article on digital goods.
Bill writes:
It is my perception that most U.S. executives have trouble conceiving and believing in the digital item model. For starters, they simply think it’s strange. “Why would someone buy clothes for their virtual avatar? That’s weird.” What they fail to realize is that U.S. consumers pay for “virtual” things all the time.
And he gives a good example of consumers buying brands that are basically virtual, i.e. non-functional. For example, the willingness-to-pay for a pair of Channel sunglasses drops significantly if the Channel logo is removed. “People are buying an image” because they “care greatly about how they want to be perceived.”
So yes, customers do by products that project an image about themselves in both the virtual and real worlds. In other words, they have emotional jobs that they want to get done in both worlds (and these jobs can be personal or social).
The crucial distinction is between the functional and the emotional jobs, not the physical and the virtual worlds. In both worlds customers will need to get functional jobs done to accomplish goals and complete tasks, and they will need to get emotional jobs done (personal jobs to improve how they feel about themselves and social jobs to improve how they are perceived by others).
If social networks want to analyze the opportunities for monetization, they need to focus on the functional jobs for two reasons. First, because these are the jobs that customers are more likely to have a willingness-to-pay for, and second, because it is much harder to consistently build solutions to satisfy emotional jobs (think about how fast brands and trends come and go).
It would be interesting to look at all the virtual products that have been sold by TenCent, Second Life, and ChangYou and divide the revenue and margins into functional and emotional job buckets (i.e. how much revenue has been generated by functional jobs vs. emotional jobs).
I suspect that the opportunity for solutions to functional jobs is much higher than that for emotional jobs.
In 2014, I calculated that Apple’s equity value would be $3 trillion, which it is today. Apple’s platforms have created even more equity value for its developers, who generated over $1.1 trillion in revenue in 2022. Using the same analysis, method, and theory, that I used in 2014, we can analyze the equity value creation potential of the Vision Pro today.
In short: the Vision Pro will be one of the most successful products in history measured by revenue, profits, customer satisfaction, and equity value creation for Apple and its developers. The reason why is simple: because it will get more customer jobs done faster, more accurately, and yes, less expensively than any product in history.
Equity value can be created in only two ways: (i) growth or (ii) financial engineering (i.e. the use of debt, cost cutting, stock trading, or arbitrage).
All growth that creates equity value results from helping people get jobs done better, in other words, from helping them solve real problems, which are known today as Jobs-to-be-Done or JTBDs.
As humans, we evolved to survive and reproduce on a planet flying 20 miles per second around a giant nuclear reactor called the Sun. In our physical reality, there are categories of JTBDs: food, shelter, clothing, health, education, transportation, energy, and leisure. All categories of JTBDs require optimization, planning, design, engineering, assessment, analysis, maintenance, revision, and investment.
And these JTBDs all exist in reality in three dimensions. The Vision Pro will be a success because a 3D platform and interface is a much faster and more accurate way to get these jobs done. It is hard to imagine this, in part, because we have been locked in 2D interfaces for decades. But developers, will create applications that unlock human potential with the Vision Pro because humans and our JTBDs are three dimensional. We evolved and live in a three dimensional physical reality.
But we also live in a virtual world: television, movies, games, social networks, books, media, art, music, finance, information, and the internet all exist today in digital form as 1s and 0s. These categories of JTBDs exist in the digital (virtual) world and they can be two, three and even multidimensional (for example analyzing business or medical data that includes multiple variables that change over time).
So what is the size of the market for the Vision Pro? Meta has sold 20 million Quests at about $500 each. Using the traditional definition of a market, this a tiny market for Apple, which has about $400 billion in revenue. But to define a market using by calculating (i) the products sold times (ii) the price of the products is a classic investment mistake because customers are not buying products, they are hiring them to get jobs done at a price they are willing to pay.
For example, we all switched from records to cassettes to CDs to iPods to streaming apps because the new products got the job of “creating a mood with music” done faster and more accurately. This is true in any consumer, business or medical market throughout history: the customer’s JTBD is stable, but the products and technologies will change. The JTBD is the true market.
The Vision Pro’s market is extremely large because it includes customers’ willingness to pay to get expensive and time-consuming jobs done better. It will help more people make more money by reducing the total cost of getting jobs done in the physical world today. And it will create new opportunities to make money in the virtual world, creating human-centric virtual 3D spaces that enable us to create, collaborate and hopefully communicate in much better ways than we do today.
The equity value creation potential of the Vision Pro for Apple and its developers is tens of trillions of dollars.
I am proud to announce thrv publicly. thrv is the first and only product management application based on jobs-to-be-done innovation theory. We have been developing thrv over the past two years, but it is really the culmination of my 25 years of working with Fortune 500 companies, private-equity sponsored companies, and start-ups.
Over two decades, I have repeatedly seen the same growth problem: launching successful products that satisfy customer needs and accelerate revenue growth is exceptionally hard.
Jobs-to-be-done is the most effective and proven way to satisfy needs and grow. It has been used to successfully launch new software applications, hardware products, and medical devices that have generated billions of dollars in new revenue (with much lower risk). JTBD has an exceptional track record across B2B, B2C and medical markets.
So why isn’t every company using JTBD? Because historically it has been very hard to use. Customer jobs are very complex. Using the customer’s job to identify competitor weakness, create a product roadmap, and launch a product is very difficult.
Until thrv, the best JTBD tools were Excel and PowerPoint. This made aligning a team around the customer’s job very hard. Using modern software and cloud tools, we built thrv from the ground up to make the customer’s job the central focus for your product team. thrv makes using JTBD easier, faster, and more effective.
The benefits of JTBD are profound because getting a customer’s job done better positively impacts every key business metric from top line revenue growth to profitability to return on invested capital.
Using thrv and JTBD, your product team can (I) reduce your risk of product failure, (ii) exploit competitor weaknesses to accelerate your revenue growth, (iii) get to market faster by focusing on the top unmet needs first, (iv) save development costs by avoiding the wrong features, (v) lower your customer acquisition costs with better messaging, and (vi) increase customer retention by increasing your customer satisfaction.
JTBD almost sounds too good to be true. And I have seen CEOs, executives, and product teams use JTBD poorly in ways that still result in horrific failure. When Excel and PowerPoint are the only JTBD tools, the HiPPO (the “highest paid person’s opinion”) wins. And if that person isn’t Steve Jobs, even with JTBD, the risk of product failure is still very high.
Jobs-to-be-done is an instrument, like a guitar, and it takes practice to play like Jimi Hendrix.
This was our goal with thrv: to make a JTBD instrument that is much easier to learn and play. Ultimately your team is like a band, and they each have a role to play. thrv helps them make hit music. And launch very successful products.
Click here to see a demo of thrv with a complete set of customer needs in a job-to-be-done, a full competitive analysis, and a complete product roadmap designed to win by getting the customer’s job done better.
Apple just released impressive quarterly results: $57.8 billion in revenue, 51 million iPhones, 26 million iPads, 4.8 million Macs, and 6 million iPods sold. So how should we value Apple? How much is a share of Apple really worth?
To put this into perspective, if Apple had Google’s P/E, it would be worth $1.2 trillion (yes, trillion with a “t”) instead of the $452 billion it is worth today. So why is Apple valued with a multiple so much lower than Google?
The Buffet model is important because it will tell us what assumptions we should analyze to determine Apple’s value and ultimately its multiple. The model is straightforward: a company’s value is based on its ability to generate future cash for its owners (what Buffet calls “owner earnings”). We can analyze Apple’s owner earnings by taking its net income plus depreciation and amortization less capital expenditures. This number was $34.7 billion for the 2013 fiscal year.
The key to the Buffet model (and any valuation model, really) is projecting the growth rate of this owner’s earnings number. If we assume a future growth rate we can determine the company’s value. All of the future owner earnings are discounted back to today’s dollars to determine the value of the company. The trick, of course, is being accurate about these growth assumptions, which is where disruption theory and jobs-to-be-done theory can help us.
If we assume that Apple will grow its owner earnings at 5% for the next 10 years, and then 2% for all years after that (with adjustments for cash and debt), Apple’s market cap wouldn’t be $453 billion. It wouldn’t even be $1.2 trillion. It would be $3 trillion. This is a share price of $3,275 in contrast to today’s share price of $506. At just 5% annual growth for Apple.
Here is the math behind this valuation:
Let’s put this in perspective: from 2004 to 2013, Apple grew at a compound annual growth rate of 74% (meaning it grew owner’s earnings basically 74% every year, see the chart above). That is impressive, but not likely to continue forever. So how do we determine if this historical growth rate will slow to 5% then 2%? As Horace Dediu and Jesse Felder have noted, the market is undervaluing Apple’s ability to produce future cash flow, so understanding this growth rate assumption is critical to our assumptions.
Disruption helps us analyze Apple’s future growth rate because (i) Apple’s recent growth has been based on the premium iPhone and (ii) disruption ends up displacing the premium players in a market.
A quick review: Clay Christensen first described disruption as the “process by which a product or service takes root initially in simple applications at the bottom of a market and then relentlessly moves up market, eventually displacing established competitors.” (Christensen somewhat famously analyzed the iPhone’s disruptive power incorrectly, but the theory of disruption is still correct).
So will Apple be disrupted? If they were, their growth rate would clearly slow, and thus their valuation would fall as well. The market seems to be saying that Apple will almost certainly be disrupted.
But let’s look at an interesting chart tweeted by Jason Snell. It shows Apple’s percentage revenue by product.
If we simplify this a bit, it looks like almost exactly like the classic disruption theory chart explaining how incumbents over-serve the market at the high end, while a low-end entrant starts at the bottom of the market, but takes over to become the dominant player.
Here is the simplified Apple chart:
And here is the disruption theory chart:
But there is a fundamental difference between the two. In disruption theory, it is a new entrant who disrupts the incumbent. But in Apple’s case, the iPhone and the iPad are an example of self-disruption. Apple disrupted the Mac (and the PC) with the iPhone and iPad. While the Mac continues to be a healthy high-end product, Apple absolutely destroyed its own iPod. Six years ago, the iPod was almost half of Apple’s revenue. In the latest quarter, iPod sales fell by 50%.
MG Siegler noted that Apple “wants to be the ones to disrupt themselves… But never with stakes this high…”. But I would argue the stakes were incredibly high when Apple decided to disrupt the Mac and the iPod (both about 100% of their revenue) at the same time. And history is a good indication that Apple is probably thinking about disrupting the iPhone, even now. A truly disruptive product to the iPhone might not emerge for years, but I can’t think of another company that would prepare for and execute a self-disruption strategy like Apple. It is in their culture to do it, as long as the new product is insanely great. As a result, Apple deserves a higher future growth rate than the market is currently giving it.
Disruption theory is a good tool to analyze what happens to companies, but it is not a good tool to help companies figure out what to do. How do you respond to disruption? When is the right time to disrupt? How do you disrupt yourself before a competitor does? These are the really hard questions.
The answer is jobs-to-be-done (JTBD) theory, popularized in Christensen’s Innovator’s Solution. In short, JTBD theory shows that markets should be defined not by products, which change (and are disrupted) over time. Markets should be defined independently of any product. They should be defined based on the job the customer needs to get done. Products change, jobs are stable.
The iPod is a great example. Microsoft made the mistake of targeting the “iPod market” with the Zune. But JTBD theory shows us that there is no such thing as an iPod market, just as there isn’t a cassette market, an LP market, or a CD market. Companies get disrupted because they define the market based on their product, not on the customers job-to-be-done, e.g. the markets for listening to music and discovering new music.
And even simple jobs are extremely complex. Every job has 50 to 150 different customer needs that are independent of any product or solution.
This is the real reason Apple succeeds: they focus on jobs and the customer needs. In the recently discovered Lost Interview with Steve Jobs, we get a look at how Jobs thought and how I think Apple as a company innovates. Jobs says designing a product is a process of “keeping 5,000 things together in your brain” and getting them to fit together. In addition, while people frequently think Jobs said “customer’s don’t know what they want”, he actually never said that. What he did say was: “you can’t just ask customers what they want and then try to give that to them. By the time you get it built, they’ll want something new.” And second he said, “you‘ve got to start with the customer experience and work back toward the technology – not the other way around.”
So this is how Apple innovates: they don’t ask customers what product they want, they focus on the job they are trying to get done (the customer experience), the hundred of needs required to get the job done (the details of the customer experience) and the different technologies and solutions to get the job done best (the “5,000 things” are the 50 to 150 needs combined with an almost infinite number of possible product solutions).
I have worked with a lot of companies over 25 years, and almost none think like Apple and are organized to focus on the customer experience like Apple. And I have been an Apple customer continuously since 1979. If Apple is acquiring new customers today that have even a tiny percentage of my loyalty to Apple products (and I buy them because they help me get important jobs done better in my personal and professional lives), then they will almost certainly be able to sustain at least a 5% growth rate.
Finally, let’s look at Apple’s product success rate vs. Google. This is another important number, like a batting average for a baseball player. Who would you rather bet on? A player with a .175 average or one with .400?
I am sure my list isn’t complete, but if you look at the Google Graveyard of products and the history of Apple launches (from the new Jobs era), Google has about a 7% success rate and Apple has about a 90% success rate. My quick analysis is here (Download Apple vs. Google), and while I am sure it isn’t entirely accurate, it is generally correct.
So in summary, this is Apple:
1. A company with a track record of growing at 74% per year.
2. A company that knows how to disrupt its own products better than any other company.
3. A company that knows how to focus on the customer job-to-be-done.
4. A company with a 90% product launch success rate.
It is a good bet that Apple will beat a 5% growth forecast over the next ten years…
Pivoting is all the rage in startup land. But it is a concept that I believe is extremely harmful to entrepreneurs. Pivoting (and “failing fast”) is exactly the wrong approach to launching a new company.
The problems with “pivoting” don’t get enough attention. Venture investors and successful entrepreneurs love to tell the stories of the early days of their startups.
And this is understandable. I have been there, and the early days are exciting. You start with what seems to be a great idea, you raise venture capital, you start hiring a team willing to take enormous risk to build something new.
Fred Wilson recently posted about startup creation stories. And there are lots of lessons to be learn from these stories.
But there are many, many more lessons – and better lessons – to be learned from startup failures.
And my conclusion from seeing many startup failures is that the entire innovation process for startups (and larger companies) is fundamentally broken.
So the answer to the innovation problem is absolutely NOT to pivot. Here’s why. In the mind of the enterpreneur, this leads to launching before he/she really understands the market opportunity and the customer needs.
The lean startup movement would seem to be a solution to this and Steve Blank’s customer development model is an improvement over traditional product development.
But both lean startup and “customer development” are based on the idea that customers don’t know what they want, i.e. they have latent needs.
So if customers don’t know what they want, it would make sense to launch quickly, fail fast, pivot, and hope for the best.
Seesmic is the latest example of the pivot method. And Seesmic shows that pivoting doesn’t work.
I was amazed at the number and types of pivots Seesmic has taken. From All Things Digital:
Since it launched in 2007, Seesmic has been a video platform, then made Twitter clients and other social tools, and last year tried to make a go with Salesforce CRM products… In February, the company announced it would be changing and expanding the free Ping.fm social media cross-posting tools it bought in 2010 into a paid service called “Seesmic Ping.”
This is absurd in the extreme. But it is also very common with startups. In fact, this type of behavior is encouraged by venture investors.
Ultimately it is harmful to entreprenuers who are dedicating their lives and souls to their startups, often at the expense of their personal lives and their families.
A much better approach is to spend the necessary time to understand the market, the customer needs, the opportunities and to innvotate only when you know all of the unmet needs in a market.
Mark Suster has a nice post about the “fail fast” method. He rails against fail fast, and rightly so. He writes:
I have met so many young entrepreneurs who tell me, “we don’t need business plans anymore, there a waste! We’re going to put our product out there and fail fast!”… or they tell me, “we’ll launch a bunch of products and see what works.” That is the old “throw spaghetti against the wall and see what sticks” approach. It’s intellectually lazy and I doubt many great companies are born this way.
I definitely agree with Mark’s view. In fact, business plans are extensive and they take time and money to create for one reason: the goal is to never fail by reducing as much risk as possible before investing in development. Of course most of the venture community (and the broader innovation community) thinks this is impossible, but jobs-to-be-done innovation has shown it is possible by using scientific methods to understand markets and customer needs and significantly reduce venture risk. The problem is not with the idea of creating a business plan, it is with the inputs to the plan. The inputs (i.e. the definition of a market and a customer need) have to change, otherwise creating the plan will not result in a higher chance of success.
A better, lower risk model would be a “zero burn” model. In the traditional model capital is invested in overhead and development (“burn”) to build and launch a product idea. The fail fast model just tries to accelerate this by launching multiple products with less capital, but the process is fundamentally the same.
As Peter Drucker said, “There is nothing so useless as doing efficiently that which should not be done at all.”
In a zero burn model, you do the work of selecting and sizing markets, uncovering all the customer needs (which is possible contrary to the mistaken “latent needs” school of thought), prioritizing all the opportunities, picking the right strategy and generating and validating a solution idea (i.e. a platform, business model and feature set). All of this work is one before development and before any investment in recurring burn.
Why does this work? Because it uses a different unit of analysis (the customer’s job) and rigorous quantitative techniques that can predict if there is product-market fit before the product is launched. It takes a lot of time, hard work, and some capital to get it right. But it is essentially a business planning process designed to significantly reduce the failure rate. And it works.
I wanted to continue my analysis of Marty Cagan’s Top 12 Product Management Mistakes. I already analyzed the first two mistakes here, and I included an introduction to jobs-to-be-done terms. I think it is helpful to look at the rest of the mistakes and offer ODI-based solutions.
Mistake 3. Confusing Yourself With Your Customer
Marty identifies the third mistake as thinking “of yourself as more like the target customer than you are.” This is a good mistake to avoid, but there are two dimensions to this mistake. The first is the functional job that the customers are trying to get done. Without a detailed understanding of the job, all the process steps in the job, and all of the needs in the job, it is almost impossible to make sure that your solution will meet the customer needs. The second is the consumption chain jobs (install, interface, learn-to-use, maintain, etc.). In this mistake, Marty is really talking about the consumption chain jobs (the “usability” in Marty’s terms).
Confusing yourself with your customer is only part of the reason usability testing fails to uncover flaws in the product. The real reason is because the product does not satisfy the functional job and the needs. Customers don’t buy product to interface with them or to learn to use them. They buy products to get a functional job done. So it is no surprise that usability testing, no matter how much of it you do, fails to prevent a flawed product launch. What is needed is testing of the features against the needs in order to validate that the feature satisfies the functional job’s needs. And because needs in the job are metrics, satisfaction levels can be measured accurately.
4. Confusing the Customer with the User
Marty correctly identifies that “The person who buys the product to address a business requirement may have very different concerns from the people that sit down and use the product every day.” In jobs-to-be-done terms, this problem can be structured as different people in the value chain with different jobs to get done. The reason this is a better way to frame the problem is that each of the jobs for each of the different people can be known and quantified. In other words, a “business requirement” is a job to get done.
In any value chain, there is a core functional job that needs to be accomplished. And that job has directly related jobs and indirectly related jobs. So the jobs of the purchase decision maker need to be analyzed as well as the jobs of the core job executor (who is performing the functional job). Only with a full understanding of all of these needs in the jobs can a company be sure that a customer will make a purchase and be satisfied with the solution.
5. Confusing Features with Benefits
Marty writes, “Your product simply must have a crystal clear, simple and compelling value proposition.” And “There are several possible reasons for poor value propositions. The most common is that the product is not solving a significant enough problem.”
I would be surprised if any serious entrepreneur didn’t know that their product had to have a compelling value proposition. VCs and entrepreneurs say this all the time. But what does it mean? What is a value proposition? The problem is not that entrepreneurs don’t know they need to have a value proposition – it is defining what a value proposition is.
And from the customer’s point of view, there is only one value proposition: helping them get a job done better. The only reason a customer will buy your product is if it helps them get an important and unsatisfied job done better.
The good news is that using the job as the unit of analysis, entrepreneurs don’t have to guess if they have a “compelling” value proposition. They can measure the value their solution creates for customers. A “compelling value proposition” is an almost useless term. But satisfying a need in a job is value that can be calculated between 0-100%. In other words, using the job and the needs to analyze value is much, much more accurate because this is how customers think: does your solution help me get the job done better.
And a feature has only one purpose: to satisfy a need in the job. And that satisfaction level can be validated with customers. This is why jobs are so powerful. Unlike other customer requirements that are vague and variable (e.g. “easy-to-use”, “reliable”, “convenient”), needs in the job are measurable (minimize the time it takes to…, minimize the likelihood of…, ). So with jobs-to-be-done, value add is knowable and measurable.
I’m reading Amar Bhide’s The Venturesome Economy and he mentions Apple’s iPod as an example of “the venturesome spirit of U.S. consumers”. He quotes a WSJ article about Apple:
“Steve Jobs can introduce ‘clumsy, overpriced, 1.0 versions[s] and trust that the army of several million Apple true believers will rush out and buy. That is the crucial, often overlooked, key to Apple’s continuing success.”
I could not disagree more. Apple’s success is not based on clumsy 1.0 versions at all. This is a simplified explanation of why their products often define new categories, and this type of thinking is why entrepreneurs and venture investors think the “fail fast” strategy will work. Focus on the early adopters and iterate the product until it is ready for the mainstream.
The problem with this analysis is it does not focus on the job that Apple helps consumers get done. Consumer jobs are complicated and each one has 50-150 different metrics (needs) related to performing the job with speed, efficiency, and predictability.
So why does Apple succeed? Because it focuses on the job the customer is trying to get done, and it is exceptionally good at identifying underserved jobs and satisfying the metrics (the needs) related to getting the job done. Think about the jobs they addressed with the iPod: storing music, listening to music, finding music, organizing music. The reason iPod v1.0 was successful was not because “true believers” bought it. It was because it got those music related jobs done better.
I still use my v1.0 iPod as a music storage system for my car. And in 2009 it still works as well as it did when I bought it because Apple helps me get the job done better.
Apple’s winning streak over the past decade (OS X, iPod + iTunes, iPhone) is based on helping customers get jobs done better. Of course, their user interfaces are legendary, but customers don’t buy products to interface. They buy products to get functional jobs done.
This iPhone ad is a great example. The focus is on the jobs you can get done.
Traditional startups are constantly iterating their strategy to find one that works. So it is no surprise that business plans are a waste of time for fundraising. VCs are really investing in the people, as they will readily admit. But it turns out business plans are a waste of time for product development as well. I have been looking for data to support this, and I finally found it.
A study done by Amar Bhide, found that 93%(!) of successful startups reported that “the strategy that led to their success was largely different from what they had originally planned.”
So now we know: a strategic plan won’t get you funded and it won’t lead to a successful product. What is an entrepreneur to do? There are two possible conclusions.
First, get rid of planning altogether and just wing it. This is the fail fast strategy: build and ship quickly and cheaply to see it anything sticks. By definition this strategy will only work if you can make more bets and hope that a few win. In other words, this strategy doesn’t change the success rate, it just changes the number of bets and hopes a very small number of successes make up for all the losses. It is basically a lottery. See Y Combinator and Tech Stars.
The second option is to fundamentally change the way strategic planning is done. From the perspective of the entrepreneur, this is the only option because starting and running 20, 30 or 100 companies is not possible. The starting point has to be a different unit of analysis for strategic planning. And that unit of analysis has to be the job the customer is trying to get done.