Recommendations engine Loomia has signed deals with the Wall Street Journal, CNET, and NBC to provide users of those companies’ news websites with recommendations based on what their Facebook friends are reading.
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Readers of these publications who are also Facebook users with Loomia’s SeenThis? application installed will see a list of recommended news articles like the one seen to the right. These recommendations are in addition to the ones typically made by the news sites, and they are derived completely from what your other SeenThis?-using friends on Facebook have been reading on the site. The so-called “social annotation line” below each headline gives users a sense of how the recommendation was generated.

Loomia co-founder and CTO David Marks says that there are several factors that go into determining whether a recommendation should be made. Of course, a user must actually visit an article before it can be considered for recommendation, but other factors such as link clicks are also taken into consideration. If a user explicitly shares an item on Facebook through Loomia, the behavior will show the strongest preference for an item. As for how the system decides which of your friends’ articles are most appropriate to show you, SeenThis? considers which Facebook groups and networks you are part of, in addition to which articles you have read personally.

Sound a lot like Facebook’s own Beacon? Well that’s because it is…but it also isn’t. With Loomia, all of the data is anonymized so there is no fear of revealing your reading habits to others. Loomia’s SeenThis? system also inverts the Beacon concept by providing social recommendations outside of Facebook and on partner sites themselves, in addition to the other way around (the SeenThis? application within Facebook will let you see what your friends have been reading across Loomia’s partner sites). Finally, SeenThis? differs by focusing on news article recommendations and not purchases from places like Amazon. Don’t expect to see a scarf recommendation from Loomia while browsing Amazon anytime soon.

When pressed on whether he’s concerned that Facebook could extend Beacon’s capabilities to include off-site recommendations, Marks responded by saying that content partners actually have an incentive to work with a third party company like Loomia when integrating social recommendation features. If they were to partner with Facebook directly, they would then have to partner will every other social network individually as well. With Loomia, they need to establish only one business relationship and the SeenThis? application will then aggregate information from across all participating social networks.

Oh yea, and about that WSJ subscription wall – Facebook users will be able to read any WSJ articles recommended to them for free.

Update: Marks wanted to add to the distinctions between SeenThis? and Beacon by emphasizing that SeenThis? is not an advertisement network like Beacon. Whereas with Beacon advertisers essentially pay Facebook for the opportunity to participate in the on-site “recommendations” by Facebook users, no one is paying Loomia to advertise on Facebook. He also emphasizes that 95% of SeenThis?’s usage takes place outside of Facebook, even though the application within Facebook serves as a destination for recommendations.

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The module, which appears next to stories, suggests other Wall Street Journal content based on what the user has read previously on the site, and compared to what other users have read, too. The module is titled “People Who Read This…” – see image below.

Loomia competes directly with Aggregate Knowledge, a high flying startup that has raised a total of $25 million in venture capital.

Like Aggregate Knowledge, Loomia offers its core recommendation engine to both content providers and ecommerce sites. Their pricing differs based on the type of partner – they charge a CPM for content sites and a percentage of sales that can be tracked to referrals for ecommerce sites. Pricing is here. They also have a free product for blogs and other smaller sites.

Ultimately, what Aggregate Knowledge and Loomia are offering are merchandising tools to Internet companies. Sites like Amazon can afford to develop their own solutions in-house, but other sites, battling razor thin margins already, need to outsource this. Companies like Loomia and Aggregate Knowedge are there to fill that need. BazaarVoice is another company in this sector, although they offer a different product – reviews and commenting features.

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Loomia is an excellent podcasting and videocasting resource. You can subscribe to podcasts, and listen to them via the site or download them to your computer or device. The key value-add is their recommendation engine – you rate media and get recommendations based on your ratings v. ratings by other community members (it works in the same way that Netflix recommends new movies to you).

In addition to substantial visual improvements, Loomia has added tagging of media, creating a great new way to find podcasts and videocasts of relevant content.

Check out Loomia – it’s free and it’s the best resource we know about for finding new podcasting and videocasting content.

Launched: June, 2005

Location: San Francisco

What is it?

Loomia provides search, recommendations, and personalization for podcasts, videocasts, and other syndicated media. In a nutshell, their goal is to help you find content that you will enjoy based on how you rate content you’ve already absorbed. The idea is awesome, and their approach is perfect (centralized website, plus distributed services to content providers) .

As with most successful web 2.0 companies, they are leveraging their users to create their core value. Users rate content. Loomia compares a user’s ratings and recommends other content that they should also enjoy.

For instance, if I like Podtech (which I do), and if other people who like Podtech also like Earningscast (an Archimedes Ventures company), Loomia will recommend that I also check out Earningscast.

Netflix takes a similar approach to recommending movies. My experience as the CEO of Zip.ca (a movie renting company in Canada) with similar recommendation features proved to me how powerful these recommendations can be. It is a hugely powerful way of connecting like minded people to like minded content.

Loomia isn’t planning on keeping all of this data to themselves. A core part of their business model will be working with other companies (think odeo as well as podtech) to allow those services to add ratings, recommendations and other features. If Loomia gets in the middle of this data stream, they could have a very bright future ahead of them.

Loomia is just getting started and the site reflects this. However, they have an awesome team (see below) and the core feature set is there. I recommend you give it a try. Mark, Loomia’s CEO, has promised to let me know when new features are added, and we will update their profile here at TechCrunch.

Additional Screen Shots:

Team:

David Marks, Co-Founder and CEO
Francis Kelly, Co-Founder and Director of Technology
Ken Fromm, Co-Founder, CFO and Director of Business Services

Links:

PodcastNYC.net, Mike Rowehl, About Loomia, Pokkari Blog

Tags: loomia, podcasts, podcasting, videocasts, techcrunch, web2.0, odeo,