Search-Powered Web Apps

Venture Beat published an interview with Google’s Marissa Mayer that ran today written by Doug Sherrets. Andy@Lijit was nice enough to forward it on to me. I’m always interested in hearing what others think about socially influenced search (careful choice of words). Having lived in this world I know some of the more esoteric opportunities and problems of the space.

First, I have to clear the decks with something right out of the gate. The term “Social” has to be the most abused tech buzz word of the last couple years.

Todd’s list of what social isn’t…

1. A person, doing something.
2. A group of people, who don’t know each other, doing something.
3. A group of people, who don’t know each other but behave the same, doing something.
4. A group of people, who do know each other, but don’t interact, doing something.
5. A group of people, paid by someone, doing something. (test: What search startup is that?)

Quotes from the article with Marissa about Social initiatives at Google:

“One thing we tried…is labeling – have users annotate the search results they see and have those annotations be shared with people on their social network or with people of like mind and interest“

“Another classic thing to try is “other users like you”, where you build implicit social connections between users who are like each other“

“Other users that did that search, also searched for”

“You could take annotations that people have entered in something like Google Coop and broadcast the annotations.”

You see what is happening here don’t you? What derails ideas about social search are very simple. The Internet world grew up with a one box, take a pill, mentality. If we can’t search the entire world’s data in one box and have that box know what we mean, it’s a non-starter because of what we have come to expect.

Yet, social behavior is just the opposite. Social behavior is about the people we “know”. It’s important to “know” people in order to validate the result set they help deliver to you. We don’t “know” everyone and that contradicts the “one box” expectation of social based search. It also contradicts the “best answer” expectation. No matter how grand the plan is for social search you need to “cross the chasm” of who you and your network know, and who you and your network does not know.

For social search to work in a global, one box world, it cannot be completely a social model. What does work is using a social network of people you “know and interact with” to find a “local expert” within a known network. That “local expert” will likely have pointers to high quality data produced by “global experts”.

The system is not perfect. But it does work quite nicely in practice within the world of general knowledge and day-to-day problem solving, around YOU. Where the system is does not work as well are in situations where the local network, as whole, has little basic knowledge of the item or concept being searched. Interestingly, these are the situations where more traditional information stores like Wikipedia work exceedingly well. This is why I feel quite satisfied when I look up Nuclear Reactor in Wikipedia, but a person in the Nuclear Power space would look to his network to find more detailed information.

The graphic above is really what we want to achieve at Lijit. Though our Search Wijit we facilitate and explore the connections, discussions, and searches of connected “real” social networks. These people interact, get to know each other, have a proxy (the blog) for the metadata that exists in real world physical relationships. In other words they do more than simply throw food at each other. When the network – of networks – hits a critical mass we should have global pointers needed to cross the social chasm – in one box.

Micah shot me an interesting article the other day. It is titled “The Fight for the Second Click“. It’s pretty interesting and predicts Google’s move into (more) media services in order to monetize the click that occurs after “the search”. Google clearly owns the first click and has managed to monetize it rather effectively. In order to continue the revenue ramp, they will be increasingly forced to own the second click.

I found this concept fascinating. At Lijit we know from watching reader behavior on our publishers’ sites that a huge percentage (33%-50%) of readers come from horizontal search (The Second Click).

We also know that the normal behavior of one of these readers is to read the article that Google referenced and then hit the back button. Reader gone, moment lost, second click wasted.

This is precisely why the Lijit Re-Search feature was added to the Lijit Search Wijit. When you have this feature turned on, Lijit hooks the reader into staying for a third click and beyond. Bottom line, you only get one click to keep to your readers around – do the most you can to mine that opportunity.

Re-Search activates when a reader enters your site from a horizontal search. When a reader types “Comcast tivo cablecard” into the Google box, many results are returned, perhaps thousands. If one of those results is a link to your publication (in this example, my personal blog) and that reader clicks it, they end up on your site and The Second Click has been executed.

On a normal site without the Lijit Wijit installed it’s now a crap shoot as to what happens to that reader next. Statistically speaking the back button is most often the next click. By contrast, as the reader reads the reference article/post, Re-Search goes out and finds other articles/posts written by you on that same subject and offers them up in the Search Wijit. When the reader is done reading the reference article, there now exists the opportunity for you, the publisher, to own the third click – one of the other articles/posts on that subject.

Publishers! Maximize your second click, the one you own!

Since starting Lijit I have been living in the shoes of our blog publishers, trying to find new and cool ways to bring them value. Lijit provides awesome stats back to the publishers we serve, but primarily focused around visits and search. While those are important interactions, we were still missing something… Comments! When readers do comment, that’s an incredible wealth of information. And that’s when it clicked for me about how totally underutilized comments are and what they could really mean to publishers.

About six months ago I met Raj Bala. Raj’s company, BigSwerve, was building some really cool technology to crawl and index comments in the Blog-o-sphere. I was immediately excited to begin working with Raj and BigSwerve in order to bring even more value to Lijit’s publisher experience. Recently, Raj and I decided that it just made too much sense to pass up putting our two ideas together, which brings us to today and Lijit’s announcement about acquiring BigSwerve.

Among the interesting information locked in the Comment-o-sphere is influence relationships. When a comment is left on a blog or a site, it indicates a positive assertion of interest and focused attention. Lijit is all about the explicit and implicit networks that exist between publishers and readers. Lijit has always found innovative ways to uncover these relationships, for example following publishers’ blogrolls or using MyBlogLog community information, but now we can take this to the next level and get them from the comment layer of the Blog-o-sphere.

I’m pretty excited about the BigSwerve acquisition. Comments are a really important source of information. Look for more comment related news in the coming weeks.