1. Are these people just general 'early adopters'? Anyone who's willing to try new stuff is going to use products that ultimately fail in the marketplace. This is the whole 'Crossing the Chasm' story.
2. Are these people merely flitting from product to product? In other words, they drink the new Cola A now but will immediately switch to even newer Cola B tomorrow. Thus, they're not really reliable long-term customers. The article gives the impression that this is not case but it's not that clear to me.
In any case, this comes down to a question of market size. If that niche is big enough, there may still be a profitable business in it. For example, how many people do you think need a service that makes Bingo Cards?
So no, it doesn't seem like it's as simple as early adopters or novelty-seekers.
Moreover, How do you distinguish an early adopter from a harbinger? I'd argue that there's very little in this article (as presented) that helps with that.
New products typically fail. If you are a consistent early adopter, you will buy a lot more failures than someone who sticks to tried-and-tested products.
If anything, "twice as many" is lower than I would have thought. In my opinion, this suggests that early adopters are rare - that there isn't a novelty-seeker type of person who goes around trying new products for the sake of it.
What they should be measuring is slightly different than this. If these people buy a new product, does that make the product more likely to fail than it would otherwise? (Given that the product is likely to fail anyway)
As I've understood, this stricter statistic is not seen in the article. Even if we could identify people like that, I would put those people into the category of "temporarily unlucky early adopters" and would not expect them to have predictive power.
With that in mind, the conclusion of the article seems nonsensical.
If people who ordinarily don't try new stuff are buying your product, then it will be a mainstream success.
If they don't, then noone cares if the consistent early adopters think that your product is great.
For a physical retail store, items that are well liked by a 0.1% of population are a failure - since they carry much of the same fixed costs as a similar item liked by 40% of population, and extra variety costs them; and the best target audience of a physical retail store is "everyone who lives close enough" or "everyone of socal demographic X who lives close enough".
An online store can serve only that 0.1% audience based on their flavour preference. If there are a million people worldwide who really like Diet Crystal Pepsi? Great, there's a lot of money to be made on that product - even if it's unprofitable to stock it in Walmart and expect that a Diet Crystal Pepsi fan will wander in today.
A SaaS app doesn't have the same sort of physical opportunity cost -- every dollar earned is a good dollar. The only real opportunity cost involved is the creator/employees' time.
(Of course, responding to the a standalone phrase, you're absolutely correct)
Recently I signed up to test a new SaaS app that I thought would be useful. The marketing language on the site was a bit different from what I found inside the app once I got going. I asked the support team for help and instead of leading me on with promises of adding things in the future, they just told me the app was a bad fit and refunded my money. I appreciated that. I was not going to be a productive user for them. Focus is key.
I think this is one of the reasons apps like Stripe take so long to go international. The user needs are very different and there's a real cost to taking on the responsibility of grappling with them.
Going away from the supermarket example and onto software - it's easy to become engaged with these types of customers, particularly if they are well funded - and lose a connection with the general market.
That is where the real danger lies. Going back to the supermarket - if these customers could affect the Cola recipe, they'd be saying 'maybe add some salt' to tailor to the unique taste they have been looking for. As they increase their purchases when you add the salt, it's easy to think you're finding the market- when in fact you're moving further away from where everyone else is.
Identifying who these buyers are is the key ... and ultimately very difficult to ascertain. Any tips on that would be incredibly valuable.
Some people prefer to buy novel products. Most novel products fail to get popular. Therefore, there is a correlation. There was no finding that such customer prefer unpopular new products over popular ones.
There actually was a finding that the analyzed customers historically preferred novel-flavor products over mainstream ones. This means, that if those customers really like your product, then that's some evidence that it may fall into the same group as the other niche products
Edit: To be a bit clearer, they do mention a sort of weeding out of users, but this requires deciding beforehand what 'mainstream' is and then (effectively) looking for confirmation bias.
Product tests are a lot like private software betas - people who actively participate and provide more than the minimum feedback tend to be called on again and again. The advice here is to stop calling on people who tell you to do stupid things.
I know plenty of people who like all/most of Firefly, The Sarah Connor Chronicles, Dollhouse, Defying Gravity, Almost Human, etc.
All shows that got cancelled after a season or two because they failed to attract a wide enough audience.
Of course, when you think about it, what's the percentage of normal shows that actually get 3+ seasons?
The difference may not be the percentage but the rabidity of the fanbase.
I haven't watched Agents of SHIELD at all yet, because the early episodes have had an even worse reception on whedonesque.com, though that seems to be improving lately.
Obviously if you just put a product in a store for a certain period of time, only pay attention to the sales numbers, and then try to make claims about the number of potential buyers in a larger population, you're going to have a bad time. (hello selection bias)
But watching out specifically for people with niche preferences in some area is not at all the answer. Barring some very strong data showing otherwise, there's absolutely no reason to suppose that a person with niche movie tastes also has unorthodox tastes in dish cleaning liquids. Now, of course, if you're about to market a Swiffer-lookalike product, whether a certain study participant likes Swiffer is an interesting variable to record. But then, you probably don't need that study all that much in the first place compared to someone who's about to bring to market a bold new product.
And of course this is just basic statistics -- do a good job randomizing your sample, and pick sample size that's large enough for your desired confidence interval.
The idea that the Internet will bring the long tail of products and services is bullshit and shows scant recognition of how economics works.
If anything, the Internet will serve to cut our existing tail shorter.
Appealing to a niche is -- as far as I understood it -- a good way to stand out in a "me too" marketplace.
Assuming the niche is large enough and isn't already satisfied by your competition, the real challenge is retaining those niche customers.
For an web-based product, the customer you do not want is the free user who uses up huge amounts of tech support time.
More like short attention spans more than anything. I mean, how long can someone who's never had diet crystal Pepsi drink until they get bored with it? Or until their friends stop asking them what it is their drinking and hop on the next "cool" product coming to town.
For this to be science, instead of just finding random correlations, they'd have to take those people and see if they _continue_ to buy products that fail.
Otherwise, sure, I have no doubt in any big enough data set, there will be some people that happen to have done whatever you want to find. Doesn't mean there's any predictive power in it.
I suppose I could believe this. But there's probably a lot of ways to interpret that data. And it seems to be about CPGs (not that that makes it worth more or less, just that CPGs have different dynamics than a lot of other industries).
Parallels to software industry: fickle users that don't want to give you negative feedback for fear of discouraging you (when in reality, they may be saving you from blowing your life savings on an ill fated concept)? Be careful with interpreting the results of customer development (or the CPG parallel--focus groups) Certain types of early adopters should be avoided (how does this square with Crossing the Chasm concepts?)
Maybe similar to how some people find themselves consistently in bad relationships, some people find themselves buying products that are doomed to fail time and time again? Perhaps they wonder why they can't just find a good product that's willing to stick around for awhile...
Did anyone else read that as "too drunk or stoned to know the difference"?
Claiming that niche consumers are the kiss of death is obviously news to many makers of luxury goods (and companies like Apple who do not cultivate mass markets but end up creating them because the niche users ended up being right).
Obviously for a mega corp stocking shelves at a B&M store such niches are not going to be viable, but for e-tailer that should be less of an obstacle.
Straight from the "creepy similarities" department:
https://news.ycombinator.com/item?id=7706539
Vocal geek minority supporting your product for righteous reasons means your product will fail.
