Content recommendation provider Taboola, which I've been tracking since its early days, is now on a $100 million annual revenue run rate, according to co-founder and CEO Adam Singolda, whom I spoke to yesterday. It's the first time Taboola has revealed its revenue profile, and Adam also said the company has also been cash flow positive for several months.
Taboola got its start helping content providers generate more video views on their sites by analyzing their own videos and the sites' users' behaviors and then adding a strip of recommended videos to help recirculate traffic. It then expanded by providing those recommendations to an ever-growing publisher network. In December, 2011, it applied the same underlying predictive technology to article recommendations and also began distributing these through its network. Adam said there are now over 1 million articles and videos, which are recommended 3 billion times/day.
Taboola, which now serves 3 billion video and article recommendations per day across a wide network of publisher sites, is unveiling "Taboola Choice" this morning. Taboola Choice allows users to proactively filter out unwanted video and article recommendations, so that these will not be seen on any publisher sites which are subsequently visited. By adding this feedback loop, Taboola's recommendations become more precise over time, resulting in a better user experience and more efficiency for both content providers and publishers.
Taboola and Kaltura have released the results of a poll taken during a recent webinar they conducted, in which attendees (content publishers and advertisers) were asked about their interest in using paid recommendations/native advertising to build their video viewership. The poll found that while 27% currently use paid recommendations/native advertising, 95% said they would "consider switching from marketing their videos using traditional advertising to paid recommendations/native advertising in the next few years."
(Note a couple of caveats here: the sample size was just 34 respondents, so the results are more directional than statistically significant. Also the webinar itself was focused on content recommendations, so presumably those attending were already interested in the topic.)
Taboola has raised another $15 million, led by Pitango VC, bringing its total to date to $40 million. The Series D financing comes just 9 months after raising its last round of $10 million. Taboola will use the new funds for continued international expansion and product development. CEO and founder Adam Singolda told me the company has 70 employees currently and plans to double in size by the end of 2013.
Taboola's roots are in providing recommendations for content providers to better promote their own video within their sites and also for third-party video to gain wider, targeted distribution. Over the past year Taboola has also leveraged its underlying EngageRank recommendations technology to quietly begin distributing article recommendations as well (I noticed these last month on WSJ.com).
Video recommendations provider Taboola has announced a $10 million Series C financing this morning led by Marker LLC. With the new round, total capital raised to date is $24 million. Proceeds will be used for international expansion and product development.
Taboola's EngageRank now delivers 500 million recommendations per day to 130 million monthly users for publishers such as WSJ, NY Times, CNN, The Hollywood Reporter, USA Today and others. Monthly users have doubled since last November, when Taboola had 64 million users in the U.S. User growth likely reflects increased penetration with U.S. publishers, and also international growth in countries such as Germany (where Taboola recently announced a deal with OMS, a consortium of 30 newspapers), England, Israel, Brazil, France and Poland.
For Internet-based content, recommendations have to be one of the toughest nuts to crack. There are just so many variables in play - analyzing and characterizing the initial piece of content consumed, building a large enough database of content to match it against, understanding individual user's peculiarities, presenting results in a meaningful way, etc. Still, effective recommendations are powerful because they enhance the user's experience, increase consumption and drive more ad inventory.
One company trying to crack the recommendations nut for video content is Israel-based Taboola. I recently caught up with their CEO/founder Adam Singolda to learn more about their approach and progress. The company's ViDiscovery system analyzes both the content provider's video and its users' behaviors. The combination of the two then drives Taboola's recommendations, which can be presented in a number of different formats depending on the content provider's preferences.
You can see several examples of the recommendations in action. At CNN.com, a little tab in the bottom left of the video window prompts for "Videos Like This" which in turn opens a horizontal scroll bar with recommended videos. In some cases the recommendation work very well, matching specific news stories with one another. But in other cases the experience was mixed. For example, when watching a video about the "Zooz Beat" music app the first recommended video was an update about Hurricane Gustav from August '08 and the second was about a refinery workers' strike in the U.K. Hmm, if there's a correlation between the three videos, I'm not sure I see it.
Still, Taboola's team has an impressive pedigree and has raised $6M to date, plenty for a small team to continue refining its algorithms and results. The company's primary model is ad-based, with it receiving a revenue share for incremental video viewing that it drives. That kind of success-based approach will endear it to resource-constrained content providers eager to generate additional usage and revenues without extra expense. It's easy to implement Taboola by just adding a line of code to the player or web site.
High-quality recommendations are not easy to pull off, but if Taboola can get its system really humming with demonstrable case studies of success it could gain very quick traction.
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