Over the last month or so, there has been a lot of buzz about Real Time Search. Twitter is already doing it, Google wants to jump in, Bing introduced bingtweets.com and many startups like OneRiot, Wowd, Twingly and Collecta are mushrooming, some with VC money. So is Real Time Search for REAL?
Let’s start with a definition of Real Time Search? To quote Danny Sullivan, editor-in-chief of Search Engine Land
“Real time search” means looking through material that literally is published in real time. In other words, material where there’s practically no delay between composition and publishing. You take a picture and seconds later, it’s posted to the world to see. You think of something, immediately tap it out on Twitter, and your tweet is shared almost as soon as you thought of it.
Twitter, the leader in real time conversations, has 1.9 million conversations everyday. Number of unique trending topics per day on Twitter is approx 8900 with an average “shelf life” of 11 minutes. There are more than 100 million videos on Youtube (with more than 65k added everyday). There are over 200 million blogs on the World Wide Web (with over 900k blog posts added in a 24 hour period).
With the tsunami of information streamed at me every second, do I really need to turn the firehose on? Do I really need to “listen” to each and every tweet about MJs death or the Iran elections?
Google’s Marissa Mayer, VP of Search Products and User Experience, offers some thoughts on the usefulness of Real Time Search
We think the real-time search is incredibly important, and the real-time data that’s coming online can be super-useful in terms of finding out whether – something like, is this conference today any good? Is it warmer in San Francisco than it is in Silicon Valley?
I have a lot of respect for Marissa and what she has achieved at Google. I agree with her that Real Time Search is potentially useful to find out if a conference was good or not. But why do I need real time search to find out whether it is warmer in San Francisco than in Silicon Valley? I have weather.com for that.
Listening to Tobias Peggs of OneRiot at the OMMA Global Real Time Search Panel Discussion hosted by David Berkowitz,
60% of searches on the web are “Navigation” searches (20%), and specific “Informative” searches (40%). An example of a navigation search is when a user is trying to get to Sony.com, or Yahoo.com. They will enter a search query in an attempt to find a recognized home page. An example of an informative search is when a user is trying to find a specific recipe for Cabbage Soup that is definitely “out there somewhere.” They enter a query in attempt to find that specific information.
The remaining 40% of users are performing search queries which display an intent that is best satisfied by realtime search results. Irrespective of industry numbers, Iran – the country, the situation, and the search query – has proved beyond doubt that there is huge demand for search results from the realtime web.
Whether or not the market for Real Time Search is 40% or a lesser number, I don’t think people ONLY care about what is happening “right now”. They care way more about “relevant” and “intelligent” information than “real-time” information.
Gerry Campbell, CEO of Collecta: a real time search engine, says
Is real-time search overhyped? He says it absolutely is. Not because there’s not a ton of opportunity, but because no one’s certain of what the opportunity is yet.
I think most users will be okay with results that are a couple of minutes dated to allow for indexing & analysis of data and make it meaningful. OneRiot and Wowd seem to be on the right path.
OneRiot offers users to sort search results by Pulse (a weighted rank of freshness, domain authority, people authority and acceleration). Similarly, Wowd offers the user two options in doing true search and real ranking (analysis done on the basis of link analysis, popularity, a multitude of search signals like keywords in the title, as well as other signals like the number of retweets on any given tweet, and freshness).
As real time search evolves, we will need to add another “R” in there: RELEVANCY.
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