What are some startup ideas that persistently fail?
quora.com
quora.com
Re dating sites: Try OkCupid / POF. Or the up and comer LikaALot.
"Social recommendations", seriously are you insane? Do you have any idea how much business is driven via social recommendations? If social recommendations didn't work then amazon would have no 'people who bought, also bought...' If you had a company that could make those things 10% better you'd have a truckload of money.
Anything that makes programming "easy for non-programmers or businesspeople": You might want to ask a little company called Microsoft about that and how much money they make by making it easy to program. Perhaps you've heard of something called ruby / python, that offload massive amounts of intellectual capacity off of programmers. Seriously, how many ruby programmers know assembly? How many companies derive incredible amounts of money from things like profilers, etc. Barely, anyone programs computers anymore.
Anything involving paying people to look at ads: You might want to ask the hundreds of companies that run things called 'focus groups' about that.
Anything that promises to make email a thing of the past: You've probably got an IM client on your desktop, might want to ask 37 signals about a product called Campfire. There's also that company called Twitter.
But there are tools like LabVIEW and Simulink (MATLAB plugin), which are fairly popular among engineers.
I'm not sure where this falls on the serious-but-mental/clever-troll scale but it's pretty far at one end or the other. Ruby and Python offload massive amounts of intellectual capacity from programmers? They're not "non-programmers" then, are they?
The point is, if your business starts off as "we sell books" (and expands to "we sell books and stuff") and you get a lot of users that way, you can mix in some social recommendations on the existing user base and thereby sell more books and stuff.
If your business is "we do social recommendations" you're screwed.
It's easy to justify the failure of a product or solution by blaming the circumstances, like the "market not being ready" or "people don't need it" or "the market is too small" etc. Often, it's just that the product sucks, which might or might not be the fault of the creators.
TL;DR: Ideas only keep failing until someone does them right.
But I very strongly think that you should know that you are walking into a minefield, rather than just blundering into it. You should know that you need to learn the landscape, try to figure out what failed, and sail your project through what may be a very narrow window hard to find by chance, as opposed to other startup core ideas where success is more about perseverance and market savvy and a lot of other things other than sailing through a very small technical window.
Also, document synchronization is a word I'd save for actually trying to synchronize documents, change tracking and merging, etc. Dropbox isn't the first to solve the problem of presenting your backed up files as a folder, a much simpler problem, they're just the first to productize it for consumers successfully. Business and open-source-technical solutions were around for a while.
dating/t-shirts - Lots of people date and buy t shirts online. I don't get this.
social or mobile _____ - How long have these been pursued? Most people don't even have smartphones yet and the first and only social thing they use is facebook. Patience.
grocery delivery - I can get groceries delivered in my area (melbourne) by one of several big companies. 10% or 1% of a one of the biggest markets is not failure, is it?
Maybe it's not possible to answer this question in a useful way.
Context is another - online grocery delivery is VERY successful in the UK too - for many reasons including lower car ownership than the US.
For the record, their stock has almost doubled in value since they IPO'd last year (http://www.google.com/finance?q=OCDO)
The business model I'm following most closely resembles the now-defunct Contenture; Readability is similar but not identical. Obviously I have some additional technology secret sauce or there wouldn't be a project in it to satisfy university requirements.
To me the main failing of conventional tipjars is the requirement to manually tip the recipient. To my eyes Tipjoy was the first real twist on this -- that you could commit to tip before paying -- but otherwise it was the same as Flattr and the dozens of others that have come and gone in this space. Flattr's twist is OK, but I think imposes even more potential cognitive overhead in terms of "I really like this site, I need to find more articles to flattr".
I think that the Contenture / Readability / my-company-name-here model works better because it requires no thought on the part of the customer. Payments are divvied up automatically. No transaction cost ("Do I tip or not?") is imposed on the user.
Mind you, my most imposing business obstacle is getting a merchant account. Businesses which take money from party A and pay some portion to party B are basically viewed as kryptonite crossed with rat poison by the banking sector.
Fair enough, too -- such businesses have statistically high rates of complaints, failures and money laundering shenanigans.
I don't think Kerchingle's model is right either. They still require you to click their medallion to begin payment to a publishing site, introducing that same cognitive disruption as conventional tipjars. Also I think the "social cents" thing is basically nuts. Far too easy to be embarrassed. It smacks of that idiotic site that published credit card transactions. Blippy? Blit? Something like that.
If a merchant processes a fraudulent transaction their processor/merchant bank gets charged for the entire transaction, which they in turn charge the merchant.
More precisely the transaction doesn't have to be fraudulent. The buyer just has to be unhappy enough that they call their bank and issue a charge-back.
So to reduce the chances of that the processors have a risk assessment department that determines the probability of these kinds of transactions occurring. If the probability is high, they just won't work with that merchant.
Now let's say the merchant wants to take money from Party A and give it to Party B. In this case Party B is probably the merchant as they're getting paid for something. But Party B didn't go through the processor's risk assessment process and they may have a much higher probability of causing charge-backs. This basically moves control from the processor/merchant bank to the merchant opening up a possibility for money to siphon out of the processor/bank and potentially never be recovered.
That's why it's very difficult to get approved for something like this. For more info read up on Third Party Payment Aggregation.
But there are many examples of things and markets which at first didn't seem all that promising. But then someone made something slightly different (or radically different) and it actually made users happy.
So just keep trying.
Semantic Search
1) It might be that it is hard for mortals to formulate a semantic query
2) AI is hard
That struck me as a problem that might be worth working on. Presumably we're being paid to solve hard problems that might have value. If someone can improve search by tackling the AI problem and make it relatively easy for people to use, they could push search to the next level.
I'm not saying some of the automated semantic extraction technologies are useless. Some of them are very cool, and it is absolutely the way we should be heading (waiting for humans to tag everything is a waste of time). However, we need to recognize while this path is taking us somewhere good it will ultimately fall short of the vision--much in the same way that the AI field has given us some great improvements without approaching a true artificial general intelligence.
These ideas are probably simply the most popular startup ideas. Which means they also fail the most. Or simply, no one got them right yet.
For example, Dropbox became a big hit where a helluva lot of online drives and sync services failed before.
I also don't think math is to be blamed -- human psychology plays an important role -- i.e. I may be interested in software-dev stuff or in startups stuff, but not every hour of every day. Basically I'm inclined to read such stuff only in the morning, while drinking my coffee (the perfect time of day for big plans).
But in the afternoon I prefer reading articles about my OTHER (lighter) interests / hobbies, like photography. And I also prefer getting stuff solved, like finding an electrician to fix the poor wiring in my house or searching for gifts for my wife/child.
For any person on this earth, immediate interest in something is relative, based on time of day, time of year, mood, current needs, current problems, current hobbies, etc...
A good recommendation engine is practically unfeasible -- because if it cannot anticipate your future desires, both short-term and long-term, then it's useless; because people "search" for stuff as soon as they realize they have a new need/desire, and then it is too late to make a recommendation (at this time, the user's history is only useful to "understand" / parse the search query).
Recommendations need to happen before the user searches for stuff.
For example -- I searched for books on drawing / colors on Amazon, and bought 2. Amazon should have anticipated that I may like getting into photography, as they do know a lot about me, but it didn't, even though Amazon's recommendations are some of the best. Now that I already bought stuff, I don't care about special offers on the same kind of stuff that I already bought.
Also, people with "hackish" attitudes have done pretty amazing stuff btw, contributions to AI included -- software isn't just math, it's also biology / chemistry / physics / psychology / philosophy, amongst others.
I love the idea of an algorithm anticipating my next move and I'd argue that for the vast majority of people you can find repeating patterns that are almost always relevant. These patterns will not be simple or obvious and as you currently pointed out, the lack of data is what is holding most innovation behind. I feel that companies that own the data like Amazon will have a lot to gain if they do a Netflix-style competition to improve their recommendations engine.
If you relax the scope of what you want a recommendation engine to do, they can do an awful lot. Directed Edge is absolutely killing it here -- http://directededge.com/ . By providing a white-label API so that developers can specify the data on which to base recommendations and by using some superior algorithms, they're able to come up with impressive results for recommendations like "People who might like to buy this might also like to buy this", or "These users might be your friends", or "You should read this other article."
Something else you may have neglected in this response: the software doesn't have to just make a recommendation. It can present you an array of options which you filter. A dynamical interface.
(DirectedEdge's product is, effectively, developer tools, so people who want the feature don't have to build their own. Hunch is heading that way too, looks like.)
The main assumption with social recommendations is that I give a damn about everything my friends like. With every one of my friends, we have an overlapping interest in at least one category, but but there are about two people in my social network that have an overlapping interest with more than half of my interests.
With current engines, they say "Oh, Alice liked the new Katy Perry album, you should check it out", without any understanding that I'm friends with Alice because of she can hold an interesting conversation, rather than a shared music taste.
The proper way to do recommendations is to build up a profile of the user, and then match recommendations from people similar to the user. This is exactly what Hunch is doing. I hope they're successful, they're the only ones close to a solution.
(Disclaimer, I'm not affiliated with Hunch, but I'm founding a startup using very similar math in a different field).
I aslo agree that social recommendations have to be able to pinpoint which friends have simialr taste, otherwise the result is just noise and junk.
Nikki www.jinni.com
The better question would perhaps be about a list of common reasons for failed startups. I don't think "having a bad startup idea" would be anywhere on the top of that list. Or for that matter, even "repeating a failed idea" wouldn't occur on the list.
My advise would be to ignore such type of answer and focus on making something people want and generates traction. The author of the answer is too narrow minded and lacks imagination and creativity.
Early search engines were pretty bad (Lycos, Altavista etc) - why? because the idea was bad, or the implementation was bad?
I would say that if all dating sites fail in the same way then maybe there is a brilliant opportunity to build one that works...which is what google did with search engines.
Company no longer exists? Completely bankrupt? Burn rate continues to increase? Point is, even if a company goes bankrupt you can still can technically still sell it. Does a failure constitue that all assets of a business are completely no worth anything?
Side question - how do you actually close a company?
#2 "I am smart enough to manipulate the system to beat the tax-man"
Hypercard.
Speaking of which, why did Hypercard die in 2004? With the explosion in computer use by so many 'normals', I would think adoption would be huge. I'm not aware of any web-based technology that would enable Hypercard level of minimalist, user-friendly programming.
I don't buy in to this answer. People obviously connect with the idea of creating content on their computer whether it's word processing, creating music, or editing photos. I think people like the idea of creating their own programs too.
The problem with general programming is that the output is too ambiguous, so it's impossible to build simple tools to express them. Lego for instance has a drag and drop tool for programming mindstorm legos but the input and output are a known quantity. With PCs it is impossible to anticipate everything that can and will be built.
The problem is that the type of apps you can build are usually pretty narrow- and if your needs fall outside of that then you are screwed.
To riff on the car mechanic comparison - dental work is expensive and not everyone has insurance that covers it - doesn't mean I should perform my own fillings with a home-kit.
I wonder if there's an opportunity for a product that introduces a more powerful programming language and steps away from doing all the calculations on a grid, but that keeps the intuitiveness of Excel.
In the programmability space there's also SIAG (Scheme in a Grid).
For analysis you might also look at Quantrix and SuperTable for inspiration.
So the reason excel won as the common mans programming language is that it doesn't force you to learn everything all at once. It starts you off as just a table of sorts (useful on its own), then you can graph stuff (useful), then you learn about sum(a1:a30) (useful), and you just keep going down the rabbit hole until you've mastered everything.
The only thing that I really hate about Excel is that Procs cannot be run in parallel, otherwise so many other cool things would be possible.
last time I checked, at least.
I think Excel 2007 and further, Excel 2010 improved on that. Pivot tables, formula calculations and many other addins (not sure about Solver) use multi-threading.
There's still a good business in making web authoring environments that are as easy to use as Hypercard. That used to mean Dreamweaver, FrontPage, and friends. Now it's more like Weebly, and I think the blogging platforms fill the same need for a lot of people.
However, I do believe that the Drupals and Joomlas of the world wont be around for long - I dont ask an electrician to wire-up my house and do it in a way that I can maintain/alter the system in the future without expertise.