If failure is defined by not getting articles written about you in Quora / TC then certainly.
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.
Perhaps you've heard of something called ruby / python, that offload massive amounts of intellectual capacity off of programmers.
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?
OK, so you've got an example that is all but a straight line from Visicalc. If that's still the dominant example after all these decades, it does not sound like a market that has been successfully disrupted, right? And indeed many have tried and all have failed. It is exactly what the article says, a perennial startup loser (and open source project loser too).
If social recommendations didn't work then amazon would have no 'people who bought, also bought...'
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.
I would be hesitant to draw far-fetched conclusions from this. Often an idea persistently fails until someone finally does them right and then it doesn't fail anymore. One example is document synchronization; people justified the consistent failure of synchronization solutions with all sorts of explanations (including the "people just don't need it" joker card) until Dropbox came along, did it right, and now synchronization suddenly doesn't seem to be a "dead on arrival" idea. There are plenty of other examples.
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.
"Often an idea persistently fails until someone finally does them right and then it doesn't fail anymore."
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.
Dropbox was as much about the market being right as good execution. If 90% of people only use one device, there's little need for synchronization. Dropbox did sync right, but also coincidentally at the same time that netbooks and smartphones were making sync a valuable mass-market product.
It's interesting how little value the answers to this question seem to have.
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.
Some of this has to do with how you define success. For dating, in the Quora said someone said "well Grindr is doing well". They have traction, in a niche community (m4m) but I'm not aware of any revenues.
Context is another - online grocery delivery is VERY successful in the UK too - for many reasons including lower car ownership than the US.
You might need to define 'successful' for online grocery in the UK. Ocado is losing money and I doubt that the major supermarket operations are profitable.
I wasn't aware Ocado was loosing money - they were definitely my delivery service of choice when I lived back home in London. I think something similar an independent company based on Whole Foods (rather than Waitrose) -- would be successful here in California.
Micropayments is a subject of interest to me, because my current hybrid honours-project-slash-startup work is in approximately that field.
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.
Can someone expand on this a bit as to why this is true? "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."
It's because of how the industry's risk assessment and fraud protection systems are structured.
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.
In my case I will probably wind up needing to hold a 50% reserve at all times. And that's with Paypal. Banks won't even talk to me until I have established turnover in the tens of millions.
I remember when I first learnt about Kerchingle -- I was gutted. I thought that my idea was unique super-magic that would made me rich and I guarded it jealously. At the time I felt that the first mover would take all. Since then watching Facebook taught me that even an enormous network effect advantage can be defeated and absorbed if you have the right mix and a smart growth strategy.
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.
The problem with money is everyone wants it and no one wants to part with it, or as little as possible!! I'd be interested in having software analyze my browser history (and my bookmarks), work out where I spend the most time or what is important to me, and allow me to spend some money that will go directly to those sites. A 2 minute carefully interfaced exercise every 6 months to a year. No background plugins, and little or no complexity for the website to implement. Badaboom.
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.
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.
Semantic understanding (including the Semantic Web) will always be alluring, but it's just not going to happen. We can't agree on semantics in real life except in small groups or in very shallow ways. Computers just aren't going to be any better at it until we create something smarter than ourselves.
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.
Wow! I would never say something would fail because it has failed in the past. Things fail because they're not done right. Demand can be created (and destroyed). This list is a list of opportunities IMHO.
My first reaction was that unlike most Quora questions, the answer summary is quite good on this. When I looked at it more, though, I realized that it didn't distinguish at all between more-popular and less-popular answers: the wisdom of the crowd (such as it is) has been lost. Also, credit for the answers isn't included; and neither are links ... so it's still far from ideal.
Actually, quite a few of these ideas persistently succeed. Dating sites, t-shirts, rss readers -- how many times have those worked since the dawn of the Internet?
dating sites and tshirts will never die, but rss readers are a blast from the past - even firefox removed the icon because people didn't use it. rss is essential to provide content for web services when you don't have an api, but on the user end it's not used anymore due to social newsstreams, dashboards, etc.
I'm not entirely sure actually - I think that the majority (if not all) of RSS readers are out dated and lack "social" features that are necessary for them to succeed. I'd list some of my ideas here but I'm currently building a very simple "RSS reader" that might solve the problem - it'll be at http://www.northpad.com when it's finished.
The best algorithms in the world won't make up for a lack of data. Few companies are in a position to make good recommendation engines.
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.
There is no reason why time of the day, temperature outside, whether Obama made a joke or not, etc can't all be features for a classifier to learn.
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.
I agree completely if we're talking about a recommendation engine that's supposed to always be able to find something of immediate interest for you. However, that problem is at least as hard as building a general AI, since not even my friends can always think of something I would find immediately interesting.
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."
bad_user, how is what you mentioned beyond mathematical modeling?
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.
Most of them fail because they don't have enough data, or they're using the wrong kind of data.
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 agree that data is the main issue here. Most companies using recommendation algorithms are over-relying on math to do the magic and make up for the fact that they are blind to what they are recommending. In order to recommend you photography related items based on your past interest in painting, the service would have to understand an awful lot about the two realms and what they have in common (art, visual, etc). Algorithms alone can't figure this out. No, I'm not blaming math, math can do amazing things to help us deal with situations where we have no data. But meaningful, accurate recommendations require meaningful, accurate information about the items being recommended. IA techniques can help automate the cataloguing of this information, but 'blind' algorithms alone will never make high quality recommendations - the kind that make you say 'Yes! Exactly!'
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, I would argue that it's not a case of "maths in general can't do this" but just that you may be using the wrong maths. You can't "just apply SVD" and expect that to work super well.
Feature, not product. No-one cares about recommendations by themselves, they just want to buy or look at stuff.
(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.)
All the answers that said "its already been done" are not quite right. Its often possible to do it better and eat their lunch. Look at DropBox. Lots of mountable-cloud-storage solutions existed but they were (are) fragile and expensive.
Something tells me the very question is wrong. If you think avoiding failure = avoiding bad ideas, then that tell me something about you: you place too much an importance on the idea. If you're already thinking this way, eh, I can't help but feel you're already starting on the wrong path.
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.
There are so many examples prooving that the type of shallow analysis given in the first answer is pointless. I thought it was finally understood that it is not the idea that matters but the execution. According to this type of analysis, google was doomed from the start, dropbox as well, Android dito, etc. etc.
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.
There is a difference between a bad 'idea' and a bad implementation of an idea.
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?
Anything that makes programming "easy for non-programmers or businesspeople"
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.
Anything that makes programming "easy for non-programmers or businesspeople"
Why?
Make Car repair "easy for non-mechanics" ... presumes people want to work on their own cars. They don't.
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.
I also don't really buy that answer, but I think it's partly because many businesspeople already do do their own programming, in Excel, a good-enough solution that also has the critical edge of being installed on most corporate machines. There are thousands of people who don't consider themselves programmers who do all kinds of what amounts to dataflow programming in Excel, ranging from quick scripts that automate repetitive tasks (what Unix folk might use a shell or Perl script for), to full-on modeling and simulation.
It always strikes me that Excel is essentially a functional programming language. A limited one perhaps (no looping/recursion) with an awkward syntax (all those commas), but still one that tons of non-programmers manage to learn and create powerful stuff with. This language then has an IDE that is quite advanced in some things (conditional formatting, charts) while strangely archaic in others (why are all variables are laid out on a grid?)
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.
You are right that Excel is the most widely used programing language, but it does have recursion and looping. They might be hidden under various tools (Macros for the trivial case, but Goal Seek for optimization, Data Tables for exploration, and Solver for multilinear optimization). Excel also does have the ability to have a "variable" hold multiple values. Pressing control-shift-enter will allow you to start using arrays in the cells, and there are a ton of functions that can handle them.
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.
>> 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.
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.
Indeed there is just such a niche of products, such as Resolver One. I think for a lot of people the attraction to spreadsheets is the same as for GUIs: very little short-term memory is required -- you can delegate remembering options and state to the user interface itself.
The sales-pitch of these "Programming tools for non-programmer's" is usually that all of the developers at your company are busy and you need to get something done so you can do it yourself.
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.
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.
I would have said that Microsoft Excel does a pretty good job at making programming easy for non-programmers - spreadsheets are also one of the first ever computer desktop applications.
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.
I've never been lucky in the jobs department on Craigslist, but everything else I've used it for, including my current new apartment, has worked out fine. Granted, there's nothing sexy about it and it can be a slog to work through in order to get what you want, but it works and people use it. Any claims of its demise are ridiculous.
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.