Predicting Technology Adoption

Today we see many new ideas and product categories being introduced into the market. We see smart speakers, AI assistants, self-driving cars, wearables, VR headsets, smart homes and many more. Not all of these will be successful and become a part of our future lives. Surely some eventually will, but only after many years of mediocre sales mainly as an enthusiast’s toy. Others will become instant hits, and will be used by the majority of people within a decade or even shorter. Despite all of these sharing a common early enthusiasm, the eventual fates will be very different, and predicting which trajectory each product category will take is not an easy task. However there are some frameworks and theories which we can apply, so here, as an excercise to test my own understanding, I will try to do just that.

Smart Speakers

This is a very interesting product category to test and apply the Chasm theory of Geoffrey Moore and the Disruption theory of Clayton Christensen.

The Chasm theory applies to new category products that require customers to learn and change their behaviour. Essentially, the Chasm theory states that there is a very wide divide between the early adopters and the early majority, due to the lack of connection between these two different types of customer. The early adopters do not act as reliable references for the early majority, and hence technology diffusion cannot rely on word-of-mouth. Thus a deliberate and focused strategy is required to bridge this gap. On the other hand, Disruption occurs when the core appeal of a preexisting product that caters to advanced users is made available to a wider audience through technology or business model advancements. As a result the market share of the preexisting product is significantly reduced (hence the word Disruption), often not necessarily by stealing the preexisting product’s customers, but instead dramatically increasing the size of the pie. Often in Disruption, the benefits of the preexisting product will already have been defined and will be very apparent to the new users, and so there will not be a Chasm to cross. This can make adoption very rapid.

In the smart speaker market, and with the introduction of Apple’s HomePod, we will witness both of these theories simultaneously at work.

For the Amazon Echo and Google Home products, we will see the effect of the Chasm. Both of these products stress the AI assistant features which are new and without precedent in the market. Therefore the companies will struggle to define the must-have value proposition, and to educate consumers as to why they should own one. Geoffrey Moore advocates a whole product approach to overcome this, something that neither company is particularly known for. I therefore predict that both these products will seriously struggle to be widely adopted.

On the other hand, we see Apple’s HomePod taking a more Low-end Disruption approach. Instead of touting AI assistant capabilities, the HomePod takes aim at high-end audio and making that accessible to people who would appreciate high-quality sound, but who are unwilling to invest in the learning and the equipment. Therefore, this approach will not experience a Chasm. Potential customers already know what they are getting and do not need to be educated on why they would enjoy good sound. All they need to decide is when they are going to save up, and therefore we are likely to see a much faster adoption rate with this marketing focus.

As a result, my prediction is that the HomePod will be a hit akin to the AirPods, easily surpassing Amazon Echo sales in revenue and even units. As a result we will see both Amazon and Google changing direction and copying Apple’s approach by making speakers with at least acceptable sound. The smart speaker market will rapidly expand as a result, but only because the marketing approach is not about the AI assistant capabilities but the high-quality music.

Self-driving cars

Self-driving technology is also likely to follow a Chasm trajectory. Without a preexisting product with a similar value proposition, people will have to be educated on the benefits, especially if regulations require that the driver cannot fully delegate the role of driving to the AI, and must be available to intervene at any time. We will see a lot of early adopters, but for a long while, that is likely to be all. Even if full autonomy becomes a reality soon and regulations allow the computers to work without human supervision, I am not convinced that many people will immediately recognise the benefits since there is no preexisting market.


This is product category that we know is in the Chasm. The benefits of the Apple Watch for example have been hard for even Apple to define, and consumers have yet to be educated of the benefits. Apple is certainly the most experienced company when it comes to crossing the Chasm (it was the company that succeeded in popularising the mouse and the GUI), but still it will take time.

The problem for wearables is that there is no preexisting product to disrupt. For example, except for a very limited number of people, tracking your heartbeat is hardly necessary regardless of how expensive or complicated the devices may be. Notifications on your wrist is also something that most people cannot immediately grasp the benefit of. On the other hand, it is also obvious that with only a minuscule screen size, a watch cannot replace the current day smartphone, no matter how powerful it may be or even if it is connected to an LTE network. Without a preexisting product, it’s very hard to understand what a wearable is good for. It is difficult to understand what benefit it can provide to a customer.

Remember that Apple initially positioned the Apple Watch as a fashion item and a high precision timepiece. The significance of this strategy was that they adopted the value proposition of a preexisting product, which enabled them to connect to customers who were not typical early adopters, thereby speeding up adoption and leaving Android Wear in the dust. Also note that while the regular smartphone manufacturers like LG have recently decided to wind down their smartwatch efforts, traditional watch vendors have started to do the opposite. Regardless of whatever tech is included in the product, at this early point in time where most consumers have no idea what tech can do for them, the value proposition of SmartWatches remain mostly the same as traditional ones and therefore the traditional vendors are the ones that have a story to sell.

Smart homes

Again, this is a product category with no predecessor. Even if you were rich enough to employ a maid or a butler, I suspect switching on the lights would not be typically something that you would do via voice commands. What has been much more critical and aligned better with what people typically hired maids for, was cleaning up and vacuuming the floors, something that Roombas do quite well without any need for a voice controlled “smart” UI. This is why we have seen pretty rapid adoption of these vacuum robots whereas Smart homes are still very much an enthusiast’s toy.

Smart homes will predictably hit a Chasm. The benefits are not clear and therefore only early adopters will buy these things. This will continue to be the case for at least several years. Early majority customers will not understand the benefits without a whole product strategy around a key use case, whatever that might be. Adoption will take a long time, if ever. On the other hand, we will continue to see innovations that use computer, sensor and software technologies to make household chores easier and quicker to do. It’s just that switching on lights is not one of those chores that is a recognised burden on our day-to-day lives.


The key framework that I’ve used above is to first identify if there is a precursor to a new product category and to see if that has already made consumers aware of the features and benefits. If so, and if the new product has the potential to dramatically increase the market, then I predict that we will see rapid adoption (whether its will be Disruptive or Sustaining depends on whether the incentives to pursue the new product aligns with the business models of the incumbents). Otherwise, we can expect the new product category to follow the technology adoption life cycle and to hit the Chasm. Since the Chasm can be overcome with a whole product strategy, whether or not the market players have experience in this is key to adoption speed.

With this framework, we can predict the rapid adoption of smart speakers by virtue of Apple’s high-quality music strategy, the relatively good adoption of smart watches due to Apple’s experience in whole product strategies and marketing, and the slow adoption of self-driving cars & smart homes due to the current lack of either.

It is also important to note that the key players during the early adopter phase are not necessarily the ones that will make it through to the early majority phase. The Commodores and Amigas of the early PC market did not thrive when PCs became mainstream. Likewise, it is a fallacy to assume that the companies that are currently “winning” in smart speakers and self-driving cars or even Artificial Intelligence in general will enjoy their early lead as the market goes mainstream. More likely than not, other companies that are better positioned for the early majority market and the specific use cases will take it from them.

Out of the markets that I have described here, the smart speaker market is the one that is most likely to see significant action in a year or two due to Apple’s fresh approach. I expect to revisit this post and review my predictions mid or at the very latest late-2018. Other ones will probably still be stuck in the early adopter market and it will be harder to say whether my predictions were right or not.

7 thoughts on “Predicting Technology Adoption”

  1. I’m always wondering how much is due to theoretical forces like the ones you describe, how much to individual product quality, and how much random fashion factor.

    For example, 2 or 3 Google products don’t quite fit your grid (and incidentally, are missing from it)

    – gGlass replaced and augmented a rather common gizmo. Yet they bombed hard in their original market
    – Chromecast opened up a new category but offered very limited functionality. It has thrived.
    – Chromebooks are doing OK, yet they’re only a more limited and simplified variant of cheap laptops that don’t even cost more.

    I think the abstract product-category based approach “does it create, disrupt, replace” (is that the whole of disruption theory ? ;-p) mostly doesn’t work because it only work in hand-picked cases. If you’ve got to cherry pick situations in which the theory works, it just doesn’t work.

    Maybe a “sexy, easy, network effects (and its evil twin lock-in)” analysis would work better. But it requires a lot more work since instead of being able to pass judgment on whole categories in a broad stroke, it requires looking at individual products in context. I’m fairly sure one excellent product can create a category ?


    1. Both Chasm theory and Disruption theory attempt to describe the limitations that even very skilful companies and teams will run into. They are not an attempt to explain the mediocre companies that fail due to bad management or ideas. Therefore bringing up any number of companies that do not fit the scheme but nonetheless failed, does not invalidate them. What I want to explain here are the products that got the techies excited, but still have a long way to go till general adoption.

      So with regards to the Google products that you describe.

      1. Google Glass never even found its way into the early adopters. It failed before the Chasm.
      2. Chromecast is an interesting product in that it was the successor to a slew of products from both Microsoft, Apple and Google (and maybe more). Initially Microsoft envisioned a full fledged PC to be connected to your TV. Google TV was similar that they thought that you would do PC-things on your TV like surfing the web. Chromecast was preceded by a version of Apple TV that threw this idea away, and focused on streaming either from the cloud or from you nearby smartphone. The idea here is that the Chromecast is a bigger screen for what you are already watching on your tablet or smartphone (videos, games), and the price matches the value that it is providing. It threw away the unfamiliar value proposition and focused on what was already well understood, and provided it at almost the same price as an adapter cable. The streaming Apple TV enjoyed success, and it was inevitable that the Chromecast would do too. In the framework that I proposed, it is clearly a product that built upon a preexisting value proposition (the desire to watch videos and games on a big screen) and that’s why it easily succeeded. On the other hand, the proposition to surf the internet in your living room screen was new and foreign.
      3. Chromebooks require a behavioral change on the side of the consumer. They have to learn to live outside of the MS-Office dominated world. They have to learn to use different software to open Word and Excel files. Therefore, for the general consumer, Chromebooks hit the Chasm and failed to overcome it. Where they did find success was in a focused niche (education). Google not only provided the operating system, but also the Google for Education initiative, thereby providing the Whole Product. This is exactly Geoffrey Moore’s prescription for crossing the Chasm, and this is why Chromebooks managed to do so.
      Chromebooks actually are an ideal showcase of both a success story for crossing the Chasm, and a failure. Education crossed it, but general purpose failed.
      Again, I didn’t pick Chromebooks this time because it’s not a trending topic right now.

      So to summarise, Google Glass didn’t even make it to the Chasm, Chromecast build upon a preexisting value proposition, and Chromebooks are an example of crossing the Chasm in one niche, and failing in all other general market segments.


      1. “Both Chasm theory and Disruption theory attempt to describe the limitations that even very skilful companies and teams will run into. They are not an attempt to explain the mediocre companies that fail due to bad management or ideas.”

        Hum. So the theories’ very first step is to clarify what makes a company “good” or “mediocre” ? Which by the way doesn’t pass mustard in several ways, ie “a company” can have several divisions some good some bad (think MS: OS, apps, peripherals, PCs, xbox…); a company can fluctuate between good and bad over time, probably over regions too; and to top it all we don’t even know what good or bad is (profits ? share ? growth ? … ?).

        Because if these theories don’t clarify that as a preamble, we’re back to my main objection: a get out of jail free card, because “hey, but this is a bad company, it don’t count !” and the reverse” hey, since the theory worked here, of course we have a good company !”.

        As for individual products:
        – gGlass seems to be having a revival. I’m not sure it can be written off yet.Do you get a 2nd chance a chasming, or is it a one-off ?
        – I’m not aware of anything remotely like cCast: with no UI and that reads media from a pointer passed by another device (directly from the source, not through the controlling/UI device). Which devices are you thinking of ?
        – In the end, have Chromebooks failed because weak in Consumer, or succeeded because strong is US edu ?


      2. No.

        Let me put it this way.
        In Newtonian physics, you have the concept of Force. A Force can influence, but will not by itself determine the trajectory of an object. You have to consider the current velocity, inertia, and any number of other forces. What the law of gravity provides, for example, is a detailed description of one kind of Force, which may or may not be stronger than the others.

        Similarly, the theories of the Chasm and Disruption describe market Forces. The actual trajectory for each product or company will depend on the current inertia and a number of other Forces, but the value of these theories is similar to the laws of gravity; they describe Forces that are very potent and often dominating, and which by themselves can often predict a meaningful subset of the ultimate outcome. Nonetheless, the outcome will depend on many things in addition to the Force in question.

        Think of theories as a Force, and you’ll have a better idea of how they relate to the real world.

        Again, relating to Google Glass, their focus on the enterprise is exactly what the Chasm theory would recommend. Focusing on a vertical niche is key.

        As for Chromecast, the second generation Apple TV does just that. It also can work with a UI (although I rarely use it that way).

        And as for Chromebooks, they have failed in consumer and succeeded in education. Whether the total is a success depends on what Google’s ambitions were. I suspect that they were aiming higher than just education.


      3. But newtonian Force applies to all objects, and when studying trajectory, if there’s a discrepancy it means we’ve forgotten some component of that very Force (say an engine, gravity, magnetism, air resistance…). You’re saying Chasm and Disruption only apply to some cases, or can be entirely overridden by other forces. Absent clear objective criterias and a list of those other forces, that makes business theory an even more dismal science than economy ^^


      4. Not all forces were known when Newton came up with his laws of motion. He himself contributed to gravity, but electromagnetic forces or the way aeroplanes fly for example were not yet well known.

        It may have been a nascent science, but that doesn’t mean it was useless. It was useful enough to explain a large number of observations, even without an exhaustive list of all forces, and that’s what Chasm and Disruption theories do as well.


    2. Just to clarify. Disruption theory is not “does it create, disrupt, replace”.

      1. Chasm theory is about how quickly a new, unfamiliar product will be adopted in the market, and what can be done about it.
      2. Disruption theory is about why encumbents are often unable to respond to threats from much smaller entrants. It is a story of how David beat Goliath. I bring it up here because the premise of Disruption theory is that there exists an encumbent with a preexisting product.

      Therefore, to understand whether a new, unfamiliar product will succeed quickly in the market, you can use Chasm theory. If you want to know whether a significant improvement to a preexisting value proposition will succeed, you don’t really need any theory (it will). Disruption theory however will tell you who will win as a result.


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