NEW YORK/LOS ANGELES (October 10, 2012) — LocalResponse, the first advertising platform that helps marketers respond to real-time consumer intent, today announced the launch of historical intent targeting (HIT), a breakthrough new service that now gives brands the ability to go back in time to deliver advertisements based on past social media behavior across public networks such as Twitter, Instagram or Foursquare.
Unlike other forms of targeting, which rely on recent or real-time impressions, HIT allows advertisers to reach back to consumers that have previously expressed interest in a brand or product months or even years in the past.
“Our mission is to make ads truly contextual. By leveraging the history of a social media conversation, we now have enhanced ability to do this,” said Nihal Mehta, CEO of LocalResponse. “Imagine a movie studio serving banner ads for a movie rental to those who talked positively about the same movie months prior. Or a retailer who wants to send a promotion to a consumer who checked into their location during the past year to get them back in. The opportunities are endless.”
Using HIT technology, advertisers can now mine historical data based on tweets, shares, and posts, such as anyone who checked into Foursquare during last year’s holiday shopping season. It’s especially ideal for content publishers who want to target users’ interest in brands, franchise titles, or even key events in a celebrity’s life. As an example, if someone tweeted about seeing a film in theaters last summer, studios can use that information to target that consumer with contextual banner ads appearing on both their smartphone and PC web browsers for next summer’s sequel.
Sony Pictures recently partnered with LocalResponse during a summer pilot program, and has already seen impressive results from its campaigns. HIT combines LocalResponse’s analytics data platform with DataSift’s powerful social data platform, which filters and extracts insights from the billions of current and historical public social conversations on Twitter, leading social networks and millions of other sources.
“With the combination of LocalResponse and DataSift, brands can now communicate more effectively with their customers by providing more relevant and compelling messaging,” said Rob Bailey, CEO, DataSift.
Through its ad targeting and display platform, LocalResponse is able to mine public social media channels to reach consumers who have expressed interest or “intent” in a particular brand or lifestyle associated with their brand partners. This allows companies to target consumers who had expressed explicit intent (i.e. a Foursquare check-in) and implicit intent (i.e. a tweet mentioning that one is in or intends to visit a store) around a specific brand. Advertisers can then respond with either hyper-targeted online ads or directly with an @mention.
LocalResponse is the first platform to help marketers respond to “real-time consumer intent,” defined as a social media moment: a Tweet, a status update on Facebook, a photo on Instagram, a check-in to Foursquare and many more. Based in Chelsea NYC, LocalResponse is co-founded by digital advertising pioneers Nihal Mehta (founder ipsh!, sold to Omnicom in 2005 and early investor in Admob), Kathy Leake (co-founder Media6Degrees), and Michael Muse; and works with over 125 advertisers including Audi, Cadbury-Adams, Coca-Cola, Dell, Estee Lauder, FedEx, General Electric, General Mills, General Motors, Hershey’s, Kmart, Loews, McDonald’s, Microsoft, NBC-Universal, Pepsi, Verizon, Walgreens and WalMart.
DataSift Inc. is the leading social data platform, enabling companies to aggregate, filter and extract insights from the billions of public social conversations on Twitter, leading social networks and millions of other sources. DataSift provides access to both real-time and historical social data to uncover insights and trends that relate to brands, businesses, financial markets, news and public opinion. DataSift has offices in San Francisco, New York, Chicago, and Reading, U.K. For more information, visit www.datasift.com and follow us on Twitter @datasift.