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Wednesday, March 4, 2009

Likaholix Wants to Know What You Like

Likaholix is a new website by two ex-Google employees, Bindu Reddy and Arvind Sundararajan. After signing up (if the site runs out of invites, Likaholix offered those who read along here some extra sign ups) you’ll be asked to enter what you like. This could be e.g. a book, or a link/ website, a person and more (I wasn’t able to enter a completely free-form item of my choice, though). After you provided a couple of such entries, Likaholix then offers recommendations in return. (Note you can also “like” other people on Likaholix, which might turn this into yet another social network of sorts.)

I’m curious how much fun this idea is in the long run... it looks amusing, but after a first look it’s hard to predict how addictive or boring this could be. What do you think? One thing that can be easier judged already is usability, which seems good, and the design, which in a lot of places feels awfully in need of some structuring... sometimes the screen elements look thrown together without clear guidance of where you’re supposed to pay attention to (lack of separating colors, anchoring lines, item groupings etc.). Some of the site’s color choices, like the site’s gray for comments or their gray separation lines, also don’t fare well on my (admittedly sub-optimal) laptop screen. (Nothing a good designer couldn’t fix, I guess.)

The About page of the site includes more information on the the back-end in use:

We use Python for our crawl, data analysis and some backend servers. Our recommendation system is built using Solr, and our website is developed using PHP and JQuery backed by a MySQL database. We run our crawl and data processing on Amazon EC2 and S3 and use Cloudfront for media serving. The website is hosted on dedicated Linux servers at M5 Hosting.

How does Likaholix plan to make money? I asked Bindu if sponsored or affiliate product recommendations based on one’s likes might be ahead (as it seems kind of a straightforward option for this type of site), and she tells me, “We are planning on experimenting with some ideas once we have enough traction ... Targeted recommendations would definitely be one of them.”

[Thank Bindu!]


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