This was not what I expected. I thought it would be about toxic customers. It's actually about a set of very good customers who happen to like products that are doomed to failure. The idea is that some people have a distinct out of the mainstream taste. Kind of like when I tell my daughter I like her outfit so of course she won't wear it again.
Two things strike me.<p>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.<p>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.<p>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?
This is pretty interesting but may not be so relevant in the context of digital products or doing a startup. Yes, we want our products to be mass market from day 1 but if your low-capital 2-person company can get traction in a 1% niche market then you'll have money to focus, retarget, and grow to 2%, 4%, 8%. Pepsi, on the other hand, needs to pay for inventory, shelf space, marketing, and distribution so their profit margins probably depend on mass market adoption. They're also in a position where it's more profitable for them to just axe less popular products and try again rather than steal shelf-space and mindshare from their big sellers.
I wonder if this works for TV shows.<p>I know plenty of people who like all/most of Firefly, The Sarah Connor Chronicles, Dollhouse, Defying Gravity, Almost Human, etc.<p>All shows that got cancelled after a season or two because they failed to attract a wide enough audience.
"Harbinger of failure" seems to be a misnomer, given that the article does show any way to pragmatically identify these users - the only way seems to be with the benefit of hindsight. A 'harbinger' requires predictive value, not post-mortem value.<p>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.
It's worth skimming the (still incomplete) paper rather than just reading the article. The article misses a key point made in the paper: repeat purchases by 'harbingers' was found to be an informative feature, in predicting whether or not a new product would succeed.<p><a href="http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2420600" rel="nofollow">http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2420600</a>
A grain of salt: these insights don't strike me as relevant if your market is over-saturated (i.e. end-user mobile apps, web frameworks, etc).<p>Appealing to a niche is -- as far as I understood it -- a good way to stand out in a "me too" marketplace.<p>Assuming the niche is large enough and isn't already satisfied by your competition, the real challenge is retaining those niche customers.
These are the customers that you do not want for a product with fixed costs (like Pepsi).<p>For an web-based product, the customer you do not want is the free user who uses up huge amounts of tech support time.
It seems to me yes they are niche customers, but also having ever changing tastes in things. Not like early adopters, but will buy a unique product for short time until they find the next unique product they like or get bored and move on.<p>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.
Sounds to me like they just analyzed a bunch of data and found that there were some people, in that historical data set, who consistently bought products that fail.<p>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.<p>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 the basic thesis is: given support by a potential prospect for a new product, check what other products they have lent support to. If those products are still around, great. If not, you might have a problem. Or more succinctly: "You don't want people that buy failed products to buy your product--and if they want to, you should change your product"?<p>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).<p>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?)<p>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...
The general idea is reasonable ("in product study, make sure your sample is representative") but the recommendations are problematic.<p>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)<p>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.<p>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.
I think there's a lesson here that might be applicable to, say, JavaScript frameworks, devops tools, or maybe even programming languages. If you're building a new JavaScript library, and you're getting lots of positive feedback from people who have tried everything except jQuery, you're probably not creating something with mass appeal...
My guess is that the "harbingers of failure" are just anti-popular-item folk. They like an item because other people (read: the huge market a company actually wants) don't like it, or because it's "different." Not because it has actual inherent new value, or actually tastes good. Perfect setup for failure -- tons of people dislike your product, and the only ones who like it are the ones who like it because others don't. Cases in point my guess are Crystal Pepsi (as the article uses), another is Zima[1], a third is Orbitz[2].<p>[1] <a href="http://en.wikipedia.org/wiki/Zima" rel="nofollow">http://en.wikipedia.org/wiki/Zima</a><p>[2] <a href="http://en.wikipedia.org/wiki/Orbitz_(soft_drink)" rel="nofollow">http://en.wikipedia.org/wiki/Orbitz_(soft_drink)</a>
<i>"These customers do not seem to be shopping at odd hours, and they are not any more likely to pay full price for the products, both of which might indicate that they are less alert or savvy than other customers."</i><p>Did anyone else read that as "too drunk or stoned to know the difference"?
Fairly trivial article which fails to state its primary assumption: it is talking about mass-market FMCG (fast moving consumer goods) which want immediate success. This is why we have tens of varieties of instant coffee but no 'cold concentrate' type liquid coffees.<p>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).
On the other hand such products could sustain a lifestyle business with a sort of 1000 True Fans model.<p>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.
Let's be clear: this is about bringing mass-market products to market, not niche products like most people on HN are building. This article considers a niche product to be a failure.
> Just as positive feedback from lead users signals that a new product will likely succeed, positive feedback from harbingers signals that a new product is likely to fail.<p>Straight from the "creepy similarities" department:<p><a href="https://news.ycombinator.com/item?id=7706539" rel="nofollow">https://news.ycombinator.com/item?id=7706539</a><p>Vocal geek minority supporting your product for righteous reasons means your product will fail.