Can anyone suggest a good couch for under $1,500? Are French Bulldogs too much maintenance?
If you use Twitter at all, you've probably seen plenty of people lobbing questions to their followers— when they could have easily just gone to Google and searched for the answer.
This habit actually has its own hashtag, #lazyweb, and InboxQ and Column Five Media created an infographic laying out exactly the types of questions people tweet out when they're too lazy to search. But it reveals a lot more than the depth of people's laziness — it also betrays the types of things that current search technology just doesn't find very well.
First, a bit about the #lazyweb hashtag: Its use peaked around 2008, and since then it's a pretty muted phenomenon, garnering about 50 questions a day. But that doesn't necessarily mean that the hashtag is insignificant — without it, imagine how hard it would be to find the questions that people ask on Twitter specifically when they're too lazy to do their own research.
Things get interesting once you drill down into the actual questions that people ask. Programming apparently is quite popular, as is technical support. Recommendations follow close behind that: for products, local businesses, and web services:
These are the types of questions that the human mind is still better at answering than a computer — situations where context, personal taste, and semantics play a big role. Step back, and you realize that there are dozens of huge startups vying to create work-arounds for this search problem: Websites from Gilt.com to Svpply.com are trying to reinvent the shopping experience with curated experiences, thus doing much of the work of a search engine. Yelp, of course, helps you find businesses using the filter of consumer ratings.
But none of these services is all that good at searching out something specific; you have to sift through pages upon pages of information to find what you're looking for. I'd wager that there's got to be an easier way: A type of searching format that would do to Google in 2011 what Google did to Alta Vista in 1999. You'll notice that Google is inching toward an answer with its new image search features. And that same idea of improving search is what lies behind many of the attempts to use social networks to filter information, whether it's news or music.
These all feel relatively provisional, and they still don't work as well as a question posed to your Twitter followers. If I was a VC in the Valley looking to find Google 2.0, that's the user experience I'd be piggybacking off of and trying to refine — and not all this stuff using algorithms, social networks, and "people like you." Long live #lazyweb.