Outbrain is the only discovery platform with both audience targeting and lookalike capabilities. It allows Marketers to extend interactions – outside of the walled gardens of social media - by connecting brands with the audiences with the highest propensities to become customers based upon the content they are actively engaging with. Outbrain tracks billions of content consumption interactions from users across the web, tapping into real user interests and discovery mode behaviour that goes beyond a consumer's public persona. In pairing lookalike modeling with Outbrain's proprietary interest graph, it is able to drive greater efficiency and value for brands with performance goals.
Brooklinen and Everquote are among the first of more than 30 brand partners who have already successfully implemented and taken advantage of Outbrain Lookalike Audiences. Brands in the beta program have seen on average 45% more conversions and 30% lower CPA compared to standard targeting. A recent case study with homeware darlings Brooklinen showed that Outbrain drove 50% lower CPA compared to standard campaigns, as well as 15% more conversions within the same day, than social platforms with 3X lower CPCs.
"Lookalike Audiences is Outbrain's latest commitment in bringing bold and impactful tools to the industry and through it we were able to significantly increase our conversions at a CPA 50% lower than that of regular targeting campaigns. When we compare this to the results seen from comparable and complementary campaigns on social networks we see 15% more conversions within the same day," said Justin Lapidus, General Manager at Brooklinen. "Outbrain has proven itself as a strong partner capable of marrying our content with the right customer to drive quality audiences to purchase on our site at scale."
"Outbrain Lookalike Audiences allows brands to scale audiences and drive improved performance by pairing lookalike modeling with our proprietary interest graph," said Amit Elisha, Vice President of Products at Outbrain. "Through Lookalike Audiences, Outbrain will continue to advance the Discovery category and enable brands to reach beyond the walled gardens of social media and tap into the Open Web - better matching content to people and improving personalized recommendations to drive conversions. Our vision is to offer marketers targeted, measurable, data driven Discovery solutions that sit alongside their Search and Social strategies and allow them to reach the right audiences in an authentic way."
Reach more of your audiences in one place
Outbrain Lookalike Audiences can be modeled off of 1st party data (site visitor segments, DMP segments, CRM lists, etc). The more homogenous the seed audience, and the closer the seed audience is to lower funnel converters, the better performance the lookalike audience will drive.
"Lookalike Audiences are most commonly associated with social media, but a significant gap exists between what we read and what we share with friends. Outbrain Lookalike Audiences allow brands to tap into this global phenomenon and extend their reach to new audiences that are truly interested in what the brand has to offer, thus complementing their efforts outside of search and social," said Dr. Ronny Lempel, Vice President Recommendations Group at Outbrain.
Dr. Roy Sasson, Chief Data Scientist at Outbrain, added: "The data yielded from our research shows that interest categories that receive many views and few shares do not always reflect as well on those who consume them, while categories such as art, education, architecture, careers, and literature receive many shares and very few views with low engagement. Outbrain Lookalikes can help brands better reach their true audience, with high probability of converting them to potential customers."
Data Science at its Best - How Lookalike Modeling Works:
Moran Gavish, the Data Scientist leading the research and development on Outbrain's lookalike framework, explained briefly how the algorithm works. "A marketer (for example - an online retailer) delivers Outbrain a list of valuable users, for example - users who have made a purchase, not necessarily through Outbrain. We use machine learning models, such as logistic regression, decision trees and matrix factorization to characterise these valuable users' content interests. Such interests (we call those 'features'. There are thousands of those) may include the main content categories they read and not likely to read, publishers they visit and not likely to visit, personas and companies they're interested in etc. Using these models, we identify in real time a user which is not included in the marketer's list, but similar to those users, and recommend them with campaigns by that marketer."
Outbrain (www.outbrain.com) is the world's leading premium content discovery platform, bringing personalized, relevant online, mobile and video content to audiences while helping publishers understand their audiences through data. Outbrain serves more than 250 billion personalized content recommendations, reaching in the region of a billion users every month across the globe*.
Outbrain's expansion to some of the web's largest global properties is a reflection of its rapid growth and its successful innovations in supporting a new era of digital publishing. Top-tier premium publishers that currently leverage the Outbrain platform include: CNN, ESPN, Time Inc., Le Monde, Fox News, The Guardian, SPH, The Telegraph, New York Post, Sky News, TF1, Condé Nast, Bild, Orange and L'Equipe.
Founded in 2006, the company is headquartered in New York with a presence in a growing number of locations globally, including the U.S., UK, Israel, Singapore, Japan and Australia.
Follow @Outbrain on Twitter: https://twitter.com/Outbrain
* Internal Outbrain numbers