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.