Show me your friends and I’ll tell you who you are.
As we “like”, comment and share information with our friends on social networks, we are actually creating a sort-of self-portrait, which can tell a lot about our personality, preferences and tastes. So much, in fact, that Israeli company Correlor says it has found a way to use our likes, posts and comments to effectively increase companies’ revenues.
Correlor is a next-generation customer intelligence company, delivering socially-based big data insights and personalization to telecom operators, ecommerce sites and media companies. In other words, through the use of complex algorithms to analyze customers’ social media profiles and browsing and purchasing history, Correlor provides companies with unique insights into users’ preferences in order to hatch marketing strategies and increase revenue.
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Are you a “techie” or a “hipster”?
“We’ve developed some very advanced algorithms and technological methodologies to interpret social signals from sources such as Facebook and integrate and interpret this data together with operator data (e.g. mobile use data), and from that understand the user and provide personalized recommendations,” Laurence Rubin, CEO and founder, tells NoCamels. Through integration of both their analytical data and the company’s existing information, Correlor is able to assist their clients in achieving optimal results in terms of marketing and revenue.
The company developed a system to sift through what they call “social signals,” or our social media activity, and identify “social genes.” By analyzing social genes, Correlor is able to categorize users into groups such as “techie”, “hipster”, “alternative” and more. Using this categorization, companies can better understand their users and integrate the data into their marketing strategies.
Trust your friends
“We’ve discovered that one of the most important things that influences people to engage on a website (e.g. purchase a product), is recommendations by friends. Our solutions can automatically choose friends with similar interests and ask for recommendations and advice from them,” says Rubin.
Indeed, an analyst survey they’ve referred to reports that 70 percent of respondent users would rather hear about a new product from a Facebook friend than from a brand. In this context, Correlor has gone beyond standard advertisement and marketing strategies to a more personal approach, providing users with what they call a more “meaningful” experience.
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“For example, through our psychographic analysis of a person’s social genes we’d find out that a person is a techie and active eCommerce purchaser. Based on this our personalization engine will recommend a smartphone as opposed to a simple cell phone; the latter would simply not be of interest to that person,” explains Rubin.
Knowing everything about an anonymous person
How does Correlor create such detailed profiles without infringing on users’ privacy? Rubin explains: “When users logs in with a service, for example an app or a website of a service provider, they are requested to accept the ‘permissions’, to grant the service provider with access to their data. Hence, they provides an explicit access and our clients then provide us with datasets with signals collected via the social login.”
But Correlor insists that despite the personal nature of their analysis, Facebook identities remain anonymous. “Correlor’s engine is not requiring the Personally Identifiable Information (PII) components to work,” says Rubin. “The PII (user IDs, etc) is typically stored separately. Correlor creates a non-identifiable interpretation of [user information], in form of user attributes – aka Social Genes. We do not even need to keep the raw data details about the users, but the derivatives of this data – the ‘Social Genome’ profile for each user.”
From biology to marketing
“The inspiration for Correlor came from some academics with the idea to do what was being done in the world of medicine, where treatment is personalized based on each person’s unique DNA and do personalized services and products based on each person’s “social DNA.” The idea was to decode and decipher each person’s unique social genes,” Rubin says.
The company was founded in 2012 by a team of experts in artificial intelligence, data science, social media, psychology and anthropology. Their lead investor is VC Jerusalem Venture Partners. They currently offer their services internationally, with clients ranging from the United States to Israel and Asia.
Laurence Rubin, founder and CEO, has a PhD with a main focus on executive management from Claremont Graduate University in California and has founded three startups in the past.
Photo: Businesswoman pressing modern social buttons on a virtual background by Bigstock