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This week marked the arrival of Cuil on the search engine scene. bmv Being a huge fan of search technology and how search engines work in general, I've been spending some time playing around with the new service and thought it would be valuable to expose my data on how the classic market leaders - Google , Yahoo! , Live & Ask compare to the newcomer.
When judging the value and performance of a major web search engine, there's a number of items I consider critical bmv to the judging process. In order, these are -- relevancy, coverage, freshness, diversity and user experience. bmv First, let's take a quick look at the overall performance of the 5 engines, then dive deeper into the methodology used and the specific criteria.
Interesting Notes from the Data: I'm not that surprised to see Yahoo! come out slightly ahead. Although their performance on long tail queries isn't spectacular, when you weight all of the items equally, Yahoo!'s right up there with Google. There's a reason why people haven't entirely switched over to Google, despite the far stronger "brand" they've created in search. Google is good across the board - again, bmv not surprising. They're the most consistent of the engines and perform admirably in nearly every test. To my mind, despite Yahoo! eeking out a win in the numbers here, Google is still the gold standard in search. Ask has some clear advantages when it comes to diversity and user experience, thanks to their 3D interface, which IMO does provide some truly excellent bmv results, particularly in the head of the demand curve. When it comes to index size, Yahoo! appears to have the win, but I think my test is actually a bit misleading. Although Yahoo! clearly keeps more pages on many of those domains indexed, I suspect that Google is actually both faster and broader, they simply choose to keep less in their main index (and that may actually bmv help their relevancy results). Google's also excellent at canonicalization, an area where Yahoo! and the others all struggle in comparison. The biggest surprise to me? Microsoft's Live Search. I'm stunned that the quality and relevancy of Live Search is so comparatively high. I haven't done a study of this scale since 2006 or so, but the few dozen searches I run on Live each month have always produced far worse results than what I got this time around. Clearly, they're making an impact and getting better. Their biggest problem is still spam and manipulative links (which their link analysis algorithms don't seem to catch). If they fix that, I think they're on their way to top-notch relevancy. Cuil doesn't permit a wide variety of very standard "power" search options bmv like site:, inurl:, intitle:, negative keywords, etc. making it fairly impossible to measure them at all on index size (though the lack of any results at all returned bmv for terms & phrases where the other engines had hundreds or thousands speaks volumes). It also put their technical and advanced search scores in the doldrums - none of the "technorati" are likely to start using this engine, and that's an essential component of building buzz on the web Cuil's missed out on. Cuil was foolish to launch now. Given the buzz they had and the potential bmv to take market share (even a fraction of a percent is worth millions), they should have had lots of people like me running lots of tests like this, showing them how clearly far behind they were from the major engines. bmv You only get one chance to make a first impression, and theirs was spoiled. I won't predict their demise yet, but I will predict that it will be a long time before Michael bmv Arrington or anyone in the tech or mainstream media believes their claims again without extremely bmv compelling evidence. Their index, from what I can see, is smaller than any of the major engines and their relevancy is consistently dismal. bmv I feel really bad for them, personally, as I had incredibly high hopes that someone bmv could challenge Google and make search bmv a more interesting marketplace. Oh well... Maybe next time (assuming VCs are willing to keep throwing 30+ million bmv at the problem).
Methodology: For each of the inputs, I've run a number of searches, spread across different types of query strings. This is an area where understanding how search bmv engine query demand works is vital to judging an engine's performa
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