Tuesday, January 26, 2010

Blogging SIIA: Previews of New Products Tuesday a.m.

Last year, I saw some fabulous stuff at the SIIA Previews event--which was separate last year. Nice to see the Previews event into the "big show" this year. I'll be giving short descriptions of these interesting new companies/services:

Boardroom Insiders: provides access to C-level execs, helps to provide info on these execs to facilitate connection to these people. Boardroom Insider searches many public sources to mine information about C-levels to help clients to connect on a personal level. And yes, they are mining executive Tweets and other social networking sites too--so, IMO, CEOs and other C-levels, if they're going to tweet, should tweet about more than just trite stuff like links and aphorisms. That is, unless they don't want to be found....(BTW, they are hiring unemployed business journalists!)

DeepDyve: Netflix for Research! Mostly for non-institutional researchers who need to get information that they can't afford. It's difficult for writers to get research info from publisher sites, and article prices can be very high (how true!) So, DeepDyve helps non-institutional users (yes, that's lots of us!) to get stuff we couldn't afford. Articles are for "rent" for about $.99 each. Monthly subscriptions are for those who need more. They also have revenue share with partner sites (the ones providing content.) DD have a great reciprocal relationship with publishers, who are happy to get something rather than nothing for their content. Most institutional uses see DD as complimentary to their own sites and gives access to many who wouldn't be able to afford articles otherwise. Currently, most of their content is scientific content, but will be moving into social sciences and other content in the very near future (in talks with providers)

Something to think about: could something like DeepDyve work for newspapers that want to put investigative pieces behind a "pay wall"? Perhaps.)

Parse.ly: Gives publishers easy way to recommend info to users based on what they've viewed in the past. (note: I can see this working well for newspapers with big databases.) Pars.ly does with content what Netflix, Amazon and Pandora already do. They launched private beta recently. The user enters in some information on interests, and Pars.ly recommends news for them based on these criteria. They are licensing this info to publishers--and I'm looking at a personalized recommendation widget as it might look at the Los Angeles times. Today, they are releasing their Publisher platform (with whitelabel widget--and I signed up to test Parse.ly)

More to come

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