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Tracking Potential Google Killers

Read/WriteWeb continues to monitor the second tier of search engines. Last month, they published the top 100 alternative search engines. This month, they’ve updated the list for February, with 32 new additions.

The criteria to make the list:

1) The Search Engine should exhibit superiority to Google—not as a whole, but in just one particular area. . . . We are not arguing that any one of the 100 list members is a “Google killer”. Rather, that they should be matched against the appropriate corresponding part of Google. For example, TheFind is a shopping search engine and therefore should be compared to Google’s shopping search engine, Froogle. . . .

Oodle Launches Index to Track Pricing Data for Online Classifieds

Oodle will today announce the launch of the Oodle Index, a real-time pricing guide for online classified listings. When Oodle launched back in April of 2005, their goal was to consolidate the widely scattered classifieds space and provide users with a central location for searching and shopping for online classifieds. Almost two years later, Oodle has collected data from hundreds of millions of online listings and has launched the Oodle Index as a means to help shoppers better understand pricing trends and find those hidden classifieds bargains.

I had a chance to speak to Oodle CEO and founder, Craig Donato, earlier this week and he walked me through the various features the Oodle Index will offer at launch. Hoping to become the “Kelly Blue Book of Classifieds”, the Oodle Index will be integrated with Oodle’s search results and utilized by clicking the “Pricing” link. Users will have access to some neat interactive charts which will show pricing and inventory trends, tailored to their geographic location.

By clicking on the pricing charts, users will be able to instantly view listings available in a specific price range and get real time data on availability. For example, searching for a 2004 Honda Accord, with less than 30,000 miles on the clock, shows 281 listings in the New York area, with an average price of $18,205. Using the Oodle Index charts, users making this search will see that for an average of just $300 more, they can peruse more than 180 Accords built in 2005. It’s this type of transparency in the online classifieds space that Oodle is hoping to bring with the Oodle Index.

“Pricing in classifieds is very inefficient,” says Craig Donato. “Our vision is to be the shopping tool for classifieds.” Indeed, Oodle has access to a multitude of data points, including demographics of buyers – even able to understand car buying preferences of Republicans in California compared to Democrats in New England.

The Oodle Index is available in all geographic areas served by Oodle and will initially provide pricing data for cars, real estate and apartment rentals.

Friday’s Internet Marketing News Roundup

This will likely be the last news post until after Christmas. Here’s what’s caught my attention today.

  1. Avinash Kaushik discusses the merits of javascript analytics over web log files.
  2. Robert Scoble has re-discovered banner ads. He explains how Texas Instruments’ banner ads managed to catch his attention.
  3. Mashable is reporting LinkedIn has secured new funding which suggests the company has a $250 million value.
  4. Social media expert, Neil Patel, explains why some SEO web sites are being banned by Digg. Digg just doesn’t like SEO. Maybe the social bookmark site is receiving cash incentives from Did-It.
  5. Is MSN inflating the conversion data at adCenter? Search Engine Roundtable takes a look.
  6. Wengo is offering an embedded flash player for bloggers wishing to share their good looks via their web cam.

You Might this New Shopping Search Engine

Photo search technology company, Riya, has launched a new visual shopping search engine named Like. Now, I’m not sure if that’s meant to be “like, these boots are really cool” or “I really like those boots”, but either way, your online shopping experience is about to get a lot better.

According to Business Week, here’s how it works…

Find a photo of a red strappy shoe that you like (or type an initial search on “red strappy shoes”), for instance, and you’ll get an array of, well, red strappy shoes from a variety of retailers, such as and Zappos…Once you take a look at those products, you can highlight the part of the shoe you like, and the search engine will find other shoes with similar patterns, shapes, and colors…you can further refine the search with sliders that let you rank the relative importance of pattern, shape, and color.