Thoughts on Apple Watch Survey, Segmentation, and Adoption Cycle Theory

I wanted to add a few more points, specifically for our Tech.pinion Insiders, on the Apple Watch customer satisfaction report Wristly and I worked on together. Part of my goal is to help you understand my thinking and my methodology.

As I explained in my article, it was the interviews I was doing with consumers which led me to create the thesis that those later on the adoption cycle viewed tech products differently — perhaps with more tolerance, patience, appreciation, etc. — vs. those who are early adopters or gadget enthusiasts. This is why several weeks ago, when the panel had less than 400 people (it’s now over 1,200), I worked with the team to add screening questions to each survey. This helped us better segment the responses and be able to filter based each profile. Questions such as which iPhone was their first or which iPhone is their current model. People who join the survey are also asked screening questions such as the date they got the Apple Watch and their geographic location. When we put all these together, we are able to use market knowledge to create the segments we did. Note: this is not standard practice to deeply segment your panel when it comes to customer satisfaction results.

I was driven to do this because, if our panel was simply a bunch of early adopters, hard-core Apple fans, and app developers or investors who have a vested interest to study the product, I wanted to know that as I would read the data a certain way, knowing the profile of the panel. Once we learned we had quite a wide range represented, we thought a customer satisfaction survey could be published with a high degree of confidence.

However, the more I started digging into each profile we created and their responses to surveys, the more I saw the pattern play out of how uniquely early adopters and mainstream “average” consumers think about tech products. I’m not sure I’d equate this entirely to a new revelation, since we should assume these categories were different, however, it was the distinctive way they think I could not quantify until now.

We saw this quite clearly in the first “Net Promoter” (someone willing to recommend or promote a product to someone else) score we ran when the panel had 300 or so folks in it. It came back below 40, which is quite low. A good net promoter score is above 80. The closer the score to 100 is, the more likely the group is to recommend a product. Contrast the below 40 number with the very first net promoter score Wristly ran before I was involved, when the panel was only 130 or so, and the net promoter score was 26. When I started reading the answers from respondents, I saw the deep and thoughtful critique this early adopter audience put into this product. You could tell it was heavily evaluated and thought about from every angle.

Contrast that with the interviews I did with other Apple Watch owners. I observed quite the opposite response from those who were obviously not early adopters. It was not that they were not thoughtful. It was more that they honed in on just a few things they couldn’t stop talking about and they seemed to have more tempered expectations or tolerance for the things the early adopters were heavily critical of.

What this has got me thinking about is adoption cycle theory. Folks have mentioned it is accelerating but the Apple Watch got me thinking that, perhaps in Apple’s ecosystem, adoption cycle theory is no longer relevant. Apple may have such a mature ecosystem, and users within that ecosystem, that when they launch a new category, it has the potential to appeal to the innovators all the way to the laggards on day one.

The iPhone is one of the singular tech products that spans the diffusion of innovations curve. I have a sense this plays into something unique about Apple’s ecosystem and the dynamics of adoption cycle theory related specifically to Apple’s ecosystem.

If this is true, it has important implications for Apple. It means new categories are not reserved to only early adopters. It also means new categories have the potential to penetrate higher percentages of Apple’s base faster than earlier anticipated. I originally had a much slower trajectory for the Apple Watch but I’m starting to wonder if it grows faster based on the research we are doing with Wristly.

As I find more interesting nuggets from our data I’ll share them with our subscribers.

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Ben Bajarin

Ben Bajarin is a Principal Analyst and the head of primary research at Creative Strategies, Inc - An industry analysis, market intelligence and research firm located in Silicon Valley. His primary focus is consumer technology and market trend research and he is responsible for studying over 30 countries. Full Bio

40 thoughts on “Thoughts on Apple Watch Survey, Segmentation, and Adoption Cycle Theory”

  1. I don’t think the adoption’s cycle breakdown is due to technical maturity as much as it is due to fashion being a, perhaps the, primary motivator. If you’re buying a tool to do a job, you need experts to tell you what tool is good/best. If you’re buying a prop to join the in-crowd, you need in-crowders to rubber-stamp it. Ars Technica vs Vogue.
    Edit: the overemphasis on a single function from let’s call them Voguers might be due to interviewer’s bias: if you keep prompting for a tech reason for the purchase, interviewees will make up one, but may have difficulty making up more than one, even though they really bought it for looks/validation.

    1. Are you suggesting the primary purchase motivation was fashion/prop for the in crowd? If so our data doesn’t support that. Most the reasons for attraction had strong utility and productivity angles than fashion. Most saw its usefulness from the start.

      1. I’m actually straight out telling it in the first sentence :-p
        People don’t tell the truth in questionnaires. Or, it’s hard to make them. They mostly try to please/look good to the interviewer.
        There’s a logic issue too: you state that part of your panel focuses on few features, say alerts & fitness. Those features have been available for ages on other (cheaper) devices, hence the purchase can’t be solely/mainly features-driven.

        1. I’m not sure I agree, since we have a pretty good track record getting true market sentiment data which proves true of the arc of time.

          This is also why I interviewed on the phone or in person people just to hear what they think in a candid way. But overall, as I said, we are seeing much more clarity in the panel that the use case value it tending to be more on the utility side. The things they talk about the most favorably are more utility or productivity use cases is my point. Not fashion, looks, status, etc. Speaks to the usefulness angle.

          1. Isn’t that true of every premium/fashion/luxury segment ? Do people ever own up to buying something because it’s the in-crowd thing to do ?
            My niece waxed lyrical about getting new fair-trade, eco-conscious shoes. I lost major Uncle Points when I told her the eco-conscious thing to do was to keep last year’s shoes, or get second-hand ones. What really mattered was getting the right model/brand, yet she never said “my friends are gonna like me sooo much for having those”. That behaviour is very obvious in teens. Do you think a there’s a switch flip at some time in adult life ?

          2. June 24 obathelemy reply to Kizek – QUOTE:

            “I don’t have the same faith as you in articles, hearsay, anecdotes rumors and news. Do you have any actual data aside from those ?

            If you don’t, at least we learned what you base your opinions on !”

            When he’s not writing Android Fan Fiction, Mr. O often argues from both sides of his mouth.

            When presented with some actual ‘data,’ it is immediately ‘suspect’ because it doesn’t confirm his beliefs.

          3. You got Apple stock too ? Spacegogo at least has that motivation for being a flunkie.

          4. Again with the name calling. I think I speak for many commenters here. Please add value to the discussion and cease posting useless noise.

          5. I was recently chastised for name-calling. But, the ‘Black Knight,’ à la Monty Python, fits him perfectly.

            Most commenters here are capable of defending their opinions with cogent and consistent arguments. And they admit when they’re wrong, mistaken, or shown to be in error. Him? Not so much.

          6. Look, I think most people are fairly tired of your name calling and insults. Knock it off.

          7. I’ve told you repeatedly to stop trolling my posts. You want to be a brat, you’ll be treated like one from now on.

          8. Good. Go read up on what “methodology” and “track record” mean instead, you need it.

          9. And to top it off, more insults. If there’s such a thing as giving up twice, I’ve just done it.

          10. I always take comfort in threads like these when someone resorts to derision, name calling, and smearing. It is a pretty good indicator that the commenter has run out of any meaningful arguments.

          11. Grow up, stop acting like a jerk.

            If the owners of this site took moderation seriously, this kind of behavior from you would be grounds for banning.

          12. He asked for particulars of the study. What you mean by data are really just results, not actual data.

          13. Of course he asked for particulars. But if you’ve ever read anything he posts regarding Apple, you’ll note that he doesn’t see/hear/understand anything that doesn’t tear down Apple.

            He is not really interested in the particulars, as he is omniscient and infallible.

        2. It would nice if you could stick to evidence-based comments. Ben has provided very good evidence and data. Where’s yours?

          1. I love logic, my minor in university was in Philosophy. Now, if you could please stop resorting to personal insults and attacks and offer evidence, data, something that adds value to the discussion. Rather than simply repeating the old talking point that Apple products are fashion baubles. Ben has presented good evidence that says this is not the case. The onus is now on you to offer credible evidence. So far your only ‘evidence’ is to accuse Ben of presenting bad data.

          2. You’re a waste of time.
            I’m not accusing Ben of anything, and you’re blindly trusting results of a survey you haven’t even seen, but since it’s pro-Apple it’s all good, he ?

          3. Again with the personal insults, so disappointing. I’m not blindly trusting anything. Ben has a good track record, and the methodology is explained.

          4. Only you can see the methodology as explained. No info on sampling method. No actual questionnaire.

          5. That’s where Ben’s track record comes in (and it is quite good). Essentially you’re saying that some surveys are flawed, therefore Ben’s survey is flawed. That is a logical fallacy.

            Your example of political pollsters is a poor one. Political pollsters have a strong financial incentive to create a horse race. In 2008 one guy beat all the pollsters, simply by doing it better and with no need for more “means” (as you put it). He just had a better model.

            Another great example from 2008, in the primary race between Obama and Clinton, that race was mathematically over the evening of February 19, Obama had won the primary. And yet pollsters kept pontificating on Hillary’s chances after March 4th. There’s no money in a race that is over. So yes you are correct that many kinds of polls and surveys can be incredibly flawed for many different reasons and can give you incorrect data. But it does not follow that Ben’s survey and data is then flawed. That would be a logical fallacy.

            Ben did expand some re: the survey on Twitter, I suggest you take a look.

          6. Only you can see the methodology as explained. No info on sampling method. No actual questionnaire.
            Edit: I take surveys as Churchill did statistics.

          7. Why did you post the exact same comment again, only with an edit about Churchill? I believe the quote attributed to Churchill re: statistics is “I only believe in statistics that I doctored myself”.

            So are you suggesting Ben has doctored his results to paint a positive picture of Apple Watch? I think you better have something substantial in the way of evidence to back up an accusation like that.

          8. well, you’ve still haven’t answered the point, so let’s do it again: “Only you can see the methodology as explained. No info on sampling method. No actual questionnaire.”
            Then you move onto yeeees but track record. So I guess you’re taking back the “methodology” argument ?
            As for track record… what exactly is the poll predicting that we can evaluate it on ? It can’t be sales, because iPad satisfaction is about as high, yet sales are down. I’m curious as to what you think a track record is. When people run fast ?

          9. I’ve already told you Ben expands a bit more on sampling et al on Twitter. You can check that out if you like. You’re certainly not the first to immediately cry “bad data!” when faced with positive results for Apple.

            If that still isn’t good enough for you (which I’m sure it isn’t) I’ll leave it to Ben to provide more detail (if he thinks your comments need a response).

          10. “I only believe in statistics that I doctored myself”- Winston Churchill
            Where the hell is Falkirk when you need him!?

          11. Customer sat questions are in the chart, so you can see the questions as they were stated in each chart of the full report. No secret there.

            Sampling was opt in of Apple Watch owners using the web, and social media to grow the panel.

            Screening questions consisted of gender, location, job, first iphone owned, current iPhone owned, time range when watch was acquired.

            Even without the screening margin of error at that sample size is less than 1%. With the screening were got even more accurate. Similar to that of a behavioural observation study. I also interviewed a significant number of people. They were not paid, (which is what usually skews your results the most).

            Understanding humans is one of my gifts. Hence the empahsis on behavioural science. I’ve even already profiled you. 😉

          12. Self-selection probably skews results more than payments. It’s not so much an issue when measuring things over time when you’re looking at momentum rather than level, but volunteering to participate in a iWatch study that pays with iWatch study results is skewing things. I’d be leery of dragging in only people committed enough to their purchase to enthuse about it ? Then again, if the same methodology was used for the iPhone and iPad surveys, comparisons between those 3 are probably fair. Also, non-payment skews things to, towards people who don’t value their time, or who value participating more then doing something else.

            I’m not sure what the margin of error is at this point.If you’re assuming your sample isn’t skewed, then it’s always pretty low anyway.

          13. Given how many of these I do, and how accurately they all “mostly” turn out, I’m pretty confident. The human interviews helped out a great deal. I work with lots of third parties to do unbiased observational research of a range of things, not just tech sometimes, so there is a lot of anthropology and behavioural science I integrate into the survey work.

            Any ownership survey is going to be slightly skewed, folks own the product.., and all ownership surveys are self selected, but one stat we did not chart was the very dissatisfied group which was less than 1% but they did show up. We has some unhappy campers in there it just wasn’t a lot of them. We also had some folks who told us they were in our survey group but returned the Watch and I got to talk to them also. Again, my point in bringing clarity in this methodology is to let people know I’m trying to see this from many perspectives. It is rare we get to study a new category with this type of lens and that’s why I’m excited about the research.

  2. I think it is very likely that Apple has found the secret formula to go straight to the early majority at least, and maybe even to the laggards. However what that secret formula is, is still anyones guess. It is possible as @obarthelemy:disqus mentions that the secret is in fashion. It might be the ecosystem, or as I would put it, familiarity and trust in the brand as a result of being highly satisfied with a previous Apple product. The trust may be simple satisfaction, but it also may be related to Apple’s reputation for making technology useful and easy to use for non-techie people (I know that in some cases Apple products have awful snags, but at least for non-techies, it seems that they still strongly believe that Apple products are easier to use). It might be Apple’s marketing and advertising prowess. Although I have my personal favourite theory, I don’t think I have enough evidence yet to put my finger on the secret sauce.

    Android Wear actually provides us with a good experimental control. I expect Android Wear (and Tizen) to greatly improve in the fashion aspect as traditional watchmakers jump onto the smartwatch bandwagon, and as Samsung, Motorola, etc. work hard to sell their stuff as well. If these succeed, then a strong case can be made that fashion is the secret.

    The failure to date of Android Wear suggests that the Android ecosystem, although quite strong, was not enough. This suggests that having a strong ecosystem with a very large market share alone is not the secret. There are certain attributes of the iOS ecosystem that are different from the Android one, but it will be harder to see if these are the secret.

    Regarding marketing and advertising, we have yet to see Samsung or anybody else in the Android Wear/Tizen camp do a serious marketing campaign. I think they are waiting for Apple Watch sales estimates before committing on one. Once we see serious marketing, we will be able to see if marketing/advertising is the secret.

    So hopefully in the next couple of years, Android Wear/Tizen will try very hard to replicate Apple’s success (assuming that an initial sales ramp faster than the iPad is considered a success), and as a result, we will get more clues on what enables Apple to go straight the early/late majority.

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