Cuil vs. Me.dium vs. Google
Posted: July 29, 2008 Filed under: Search, User Experience 4 Comments »I love being able to pit startups against the 800 lb gorilla – people always love an underdog and you never know when the little guys might just hit the right pressure point and topple the King.
There have been a few notable new efforts lately in the evolving search wars.
Today Cuil launched its new search engine, following closely on the heels of Me.dium, who announced their search alpha two weeks ago, as well as a few month after Powerset and Searchme.
Let’s look at the two recent competitors and do a quick compare of Cuil vs Me.dium. I think these two companies approach the problem of finding information in very different ways, not only as compared to each other, but also compared to existing players. Do either of their search results hint at a potential to beat Google?
A little background on the companies
Cuil.com, which has an impressive staff of search experts and ex-Googlers, has come bounding out of the gate taking several direct pot shots at Google. The biggest one is the size of the cuil index and how quickly they were able to create it. The founders include Tom Costello, Anna Patterson and Russell Power. The company, which has raised $33 million so far, claims to have indexed 120 billion pages prior to launch, and has decided to change the search results page (how dare they?!) from the well known, tried and true single column layout to a multiple column format.
Me.dium.com, a startup founded by Robert Reich (me), Peter Newcomb and David Mandell, and led by Kimbal Musk, opened its own search alpha to the public two weeks ago. The company, which bases its secret sauce on the browsing activity of real people has publicly stated it has a half a million unique users surfing the web with the Me.dium sidebar and vetting a half billion web pages per month. The company has raised $20 million so far.
The Difference: People vs. Robots
The big difference between the two companies is how they crawl the web. Cuil uses Twicler, a robotic crawler, to build its index. Me.dium uses the actual browsing activity of people using a proprietary sensor along with a partnership with Yahoo. These two approaches produce very different results. I ran several tests and selected the following examples to illustrate the difference. The first is current and focused on Cuil and the second blends long tail and big head “Iran nuclear talks”.
Search 1
Cuil.com – query “cuil new search engine”
me.dium.com – query “cuil new search engine”
Search 2
Cuil.com – query “
iran nuclear talks“
me.dium.com – query “iran nuclear talks“
Conclusion
Me.dium’s social search did a significantly better job at returning both tall head and long tail type queries. I am sure given enough time the Cuil engine will get better, but measuring Cuil’s official release vs. Me.dium’s alpha does not seem to be a contest. Yes, I am biased, but round one goes to Me.dium. Power to the people.
Gfiggy from Me.dium here… thanks for the awesome post!
The feedback has been great since launch – crowd powered search is definitely something the people need and we’re busting our butts to bring you organic “hot” results. Let people tell you what’s interesting, not corporations and ad $$!
What’s really unique is that as the interest of the crowds change, so do your Me.dium search results so we’re creating a new lens based on what’s going on now. e.g. do a search for John Edwards on Google or Cuil, and you get johnedwards.com and wiki/johnedwards. Do the same search on Me.dium and you learn that today people care about his love child, pictures of his mistress, etc.
The difference is real-time (what people are browsing now) vs. historical (what they browsed in the past). Social vs. Old School. Check it out and let us know your thoughts. http://me.dium.com/search.
[...] Cuil vs. Me.dium vs. Google [...]
What about Google Trends? How do Cuil and Medium’s social search compare?
I do not understand enough about Cuil to comment on their ability to predict trends, but I would guess they do not have enough query volume yet, to predict anything in a meaningful way.
Me.dium has no where near Google’s query volume either, but its users vet half billion web pages a month. This technique lends itself very well to trend type data.
I would argue Me.dium could do as good, if not a better job than Google at predicting trends.