The Good NET Guide

Posts Tagged ‘then-interprets’

Startup Peerset is launching an advertising data tool that generates “psychographic” recommendations and ad placement advice, based on content analysis. Peerset’s proprietary technology organically links interests, values, lifestyles and attitudes to brands, letting advertisers see the constellations of these links.

Sound confusing? That’s because Peerset’s technology is fairly complicated. The startup basically examines interactions on social media sites and then interprets these connections and provides recommendations to brands and advertisers based on the results. For example, if the ad subject is “Fashion,” Peerset may determine that the ideal audience is also communicating about “Sex and the City,” “sushi,” and “Madonna.” Peerset says that this data can help advertisers and brands figure out what audiences are likely to engage and connect strongly with a product or service.

Peerset goes beyond just giving advertisers data on target audiences; the startup actually integrates with existing ad serving systems and will place contextual adds next to connecting “subjects.” Peerset will actually execute media buys either through social media publishers or through ad networks which let you target by keyword. For example, the “Fashion” ad would be placed next to content about Sex and the City or sushi.

And Peerset’s technology lets advertisers create campaigns that target and connect with audiences who share similar values, interests or lifestyles. It should be interesting to see if Peerset’s technology proves to be profitable for advertisers and brands.

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Gil Elbaz wants people to make lots of spreadsheet tables filled with fun and important facts and share them across the Web. Later today, he will be launching Factual, which he describes as “a platform for anyone to share and mash open data.”

Elbaz previously was the co-founder of Applied Semantics, which Google bought in 2003 for $100 million and turned its technology into AdSense. With Factual, he is trying to collect a rich repository of structured data (i.e., data neatly placed in rows and columns in his database), all contributed by developers, publishers, and “data enthusiasts.” So if you love making spreadsheets, Factual is for you.

The way that Elbaz is going to get people to contribute to his online database is that all the data placed into it is open and free to use. He is also making it easy for people to create their own tables and embed them on their own sites. “We’ve built smart tools to help a community maintain a large, trusted source of structured data,” he explains.

See the examples embedded below of U.S. prisoners on death row and American Idol finalists to get an idea of what these tables look like. Every cell can be clicked on to add comments, see the source of that particular data point, and offer corrections. The tables can be filled with any kind of data, from a list of cancer doctors with their specialties and which insurance they accept, to a list of farmer’s markets across the U.S.

Elbaz believes that good data leads to good decisions. So he designed Factual to self-correct and improve its data over time. Once he has a rich source of structured data, that will start to become very appealing to developers, who can access Factual’s data through its API .

Of course, he is not the only one trying to o this. Danny Hillis at Freebase has a two-and-a-half year head start. Everything in Wolfram Alpha is highly structured in an automated way. And Google is trying to get into the game with Google Squared.

Check out the interactive Factual tables below.

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