Search Startup Surf Canyon Raises a Seed Round


It’s hard to compete in the search engine market, but one approach taken by several startups is to sit on top of the big search engines and try to improve their results or interface. Why reinvent the wheel when you can simply add new spokes? Surf Canyon, a bootstrapped startup I wrote about last February, re-orders results on Google, Yahoo, and Windows Live Search through a browser add-on. Previously self-funded, the startup has raised a seed round of $600,000 from angel investors. It is showing that even a search startup can be built on the cheap.

Surf Canyon is probably not going to be the next Google, but it does improve the traditional search interface by pulling up related results that otherwise would be buried on page 12 or page 52 of the regular results. Here’s how I described the service in my initial review:

Whenever you do a search, a little bullseye icon appears at the right of each result. If you click on the bullseye, Surf Canyon inserts three recommended search results that are similar to the one you clicked on. They appear indented under the result you are trying to drill down into.

The results are hit or miss. Surf Canyon basically gets three chances per click to come up with a relevant recommendation. In general, it comes closer than if you hit the “Similar pages” link that Google provides with every search result, but it still feels pretty random. Showing more than three recommended results would help. But what I like best about Surf Canyon is the interface. It doesn’t take you to another Web page. The recommended results just appear underneath the appropriate link. It feels more like an application than a cumbersome Website where you have to click through multiple pages to find what you want. Google could take a lesson in interface design from Surf Canyon here with all of its Ajax goodness.

I find that I still use the Surf Canyon feature on a regular basis. The results, though, are still hit or miss. Maybe the new funds will help them fine-tune their algorithm.