When I read a recent article on Facebook (Nasdaq: FB)’s plan to offer a question-and-answer feature (as do several other players in the search space), two thoughts immediately ran through my mind.
The first was to wonder about the possibility that the proposed model will actually work, and the second was how it might make money. (The skeptic in me looks for the problems before embracing the possibilities.) Here is my take on the short-term outcome of Facebook's plan.
The initial difficulty of semantic search, which would be used to help users get answers to their questions, is for the technology to correctly understand the question. Here is a case in point. I typed the following question into a standard Google search box: “Who said showing up is half the battle?”
The first of 1,180,000 hits was a link to WikiAnswers showing that this was an uncategorized question, meaning one that no one had answered. Refining the search with quotes around “showing up is half the battle,” the WikiAnswers entry still rated high, number 2 out of 4,990. Scrolling down that list, I discovered that Woody Allen said that “half of success is showing up…” This is plausible; I have no idea whether it is correct, but it was the closest that I came to attaching a name to my quote and question.
I did not ask the original question for rhetorical reasons. I wanted to use the quote and give credit to the author. The query to Google illustrates the difficulty that traditional search engines have interpreting questions. They are excellent at finding strings of characters, and when you put quotation marks around phrases, the results are generally excellent.
In the example, I was not looking for all the places where my quote was found on the Internet; I was looking for the original source so that I could give it proper attribution. Semantic technologies are getting better at interpreting questions, and it looks as if WikiAnswers understood what I was asking and knew that it did not have the answer in its content base.
The reason for using the quotation was prompted by these questions: How can social “answering engines” work if no one shows up with the answers? Will we be able to trust the authoritativeness of answers found through a Web of social sites from which the contributors will presumably come? What will motivate people to contribute answers to trivial questions or even important ones? At what point does the complexity of a question, or the way it is phrased, eclipse the ability of the semantic engine to interpret it? How will the engines correctly target the appropriate social sites where answerers would be found?
As with all semantic software technologies, there is a tremendous amount of trial and error, testing and tuning, required for users to ask questions the right way. There will be even more challenges for the software to get to people with the right answers. How many adopters of the technology will still be around when, and if, successes and reliability begin to accrue?
It did not matter to me if the correct quote is “half the battle is showing up” or “half of success is showing up,” because the sentiment is still the same. Mine was a trivial question, but for millions of important questions, will a critical mass of people show up in social spaces with the right answers?
If not, interest will soon wane, and widespread use will be limited to special applications. Some of these already exist to address very serious challenges. You might want to take a look at one good example, Innocentive, which uses social tools and search creatively to bring specialists to problem-solving.
The answer to my second question, “How will they make money?” is easy: Charge for answers. But if questions are not correctly understood and the right people aren’t found to answer, we are back to a tough spot, and this is not a short-term winning business model.
What about long-term possibilities? Niche applications might be the successful opportunity to pursue. That’s where I would place my bets on most semantic technologies.
Greg Sterling, founder of Sterling Market Intelligence, who was quoted in the July 26 LA Times article cited above, probably has it right: “This whole notion of Q&A and human-powered search is really valuable and powerful, but not so far done in a way that is effective across the board. It's really about how they can provide targeted responses to questions people have. You have to provide a great experience every time.”
— Lynda W. Moulton consults at LWM Technology Services on knowledge management strategies for enterprises.
taimur_tz, I agree with you that Facebook don't need to charge directly for answers to make money. They will find a way to monetize this search engine better than we think. But the main problem that people will face is the accurancy of those answers.
Study hard. Work harder. If a Master's Degree or a Doctorate were easy, They wouldn't be worth a thing. Make it so that all the other students are challenged to work hard every time they see you in class with them. Students are the only segment of American society, who want less for their money. Don't be one of them. If a professor says "We're going to end early today." Shoot your hand into the air and ask "Will there be a rebate on the tuition I paid? I ask because I'm paying for this class with money earned as an American War vet. And the tax payers deserve my best efforts getting the education."
I find Tamiur-Tz's comment offers the most likey way to monetize such services. As he said, "Whatever you search for, tells them more about you.. . .The more they know about you, the richer their records are and the yummier this information is for the advertisers." It's very true. I am always flooded with offers for "free" samples online that only offer the item as a reward for filling out forms that provide the suppliers with exactly the information they want about their potential customers. Learning about their customers is worth money to them, and something that tracks a person's searches can be a very valuable resource for those who know how to exploit -- I mean utilizie -- it.
Great article Lynda. I updated the WikiAnswers answer that you link to above with more info about the quote. In a New York Times blog Fred Shapiro recently dug in and found the closest attributable quote to be Woody Allen's "showing up is 80% of life." So as IQ Crew writes in a comment below, it appears to be a quote that evolved from multiple places.
On the larger issue, people are showing up, to different degrees on different sites and in different categories, to answer these questions. Sites like Answers.com / WikiAnswers (where I work) are based on getting all the best answers from users and trusted publishers into a database to show them to future Askers. Facebook Questions is currently looking to get your friends to answer your questions on the fly. Niche sites like Stack Overflow are very successful in specific markets (in their case, computer programming).
I don't think this is a model that's going away. Different companies will achieve different levels of success in different areas.
Regarding money, paying for answers isn't the only model. That model will probably only work for the relatively small subset of answers that you'll pay for. Successful sites will have many community members giving good answers for free, for different reasons, just as your post has many people leaving great comments, for free. The ad supported model should work for some of the other sites.
Those are interesting statistics, Ariella. I agree that the accuracy level is probably about the same. I do agree with the questions and the premise in the blog. I am not sure that social networks, and that structure, will be a reliable source of information. It will be more of an opinion, whereas Wikipedia is more about information.
I also don't believe people will be willing to pay for that information, do you?
"A notable early study in the journal Nature suggested that in 2005, Wikipedia scientific articles came close to the level of accuracy in Encyclopædia Britannica and had a similar rate of "serious errors".[3] This study was disputed by Encyclopædia Britannica.[4]
In other words, even Wikipedia could not presume to simply tout its accuracy as irreproachable on the bsis of the article in Nature. Users are warned: "but users should take care – as with all general reference works – to check their facts and be aware that mistakes and omissions do occur."
Also check out http://www.livescience.com/technology/091106-ttr-wikipedia.html, which says, "A 2005 study by the journal Nature found Wikipedia roughly as accurate as the Encyclopedia Britannica, and a 2008 study in the journal Reference Services Review pegged Wikipedia's accuracy rate at 80 percent compared to 95-96 percent among other sources — not bad for a free, crowd-sourced encyclopedia." 80% is significantly lower than 95-96% when measuring accuracy.
I didn't say "faulty," IT_Duchess, you really have to be careful not to misrepresent people's words. I said that it is "not to simply be taken at face value." Clearly, Britannica believed they were right to refute the article and even called for a retraction. Nature felt justified in standing its ground for the claim it made. I stand my ground in questioning your original statement. Your is much more sweeping than the claim of Nature's article. Nature did not claim, "Wikipedia has been determined to be at least as accurate as most major encyclopedias." The word they used were "comes close to," and that only for science topics. In other words, while you indicated that Wikipedia matches or surpasses major encylopedias in terms of accuracy for all area, Nature only argued it "comes close to Britannica in terms of the accuracy of its science entries." That is a much more limited claim.
I was also scratching my head as to wherein semantic search comes into this topic. I thought my reasoning was flaw until I saw your comment. This Facebook question and answer forum is basically using the "wisdom of the crowd" as we've known it to be.
I will only like to know from Lynda why she thought this was a money making initiative.
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