Looks to Help News Organizations Leverage Social Insights

Recently launched startup, which tracks social engagement with the news as it happens, is looking to change the way publishers and news organizations look at and produce content on the web, and it’s leveraging data-driven insights to make that happen. Helmed by former Al Jazeera Engish Head of Online Mohamed Nanabhay and experienced data scientist Haroon Meer, the company has strong roots in both the data research and journalistic aspects of its approach, and a bold vision of what the future of online content could look like, with a little help from contextually-relevant analytics.

Unlike other analytics tools, is aimed squarely at content and the news cycle in general, alerting publishers to stories that are doing well on their own sites, and to potential hot topics they might want to cover. It’s a little like a weather vane for online news, with a focus on helping editors and others involved in editorial policy make informed decisions about what gets posted, and when.

“There are two key differentiators that provides,” Nanabhay explained in an interview. “First, most analytics tools provide insight into a publisher’s website – is designed from the ground-up to take a look at the entire news landscape as defined by the publisher. Simply put, we can track and provide insight into audience activity on the websites of peers and competitors.”

This approach allows for reflexive analysis of what’s doing well, and which journalists are hitting the right notes in terms of connecting with readers, but also provides opportunities for competitive analysis, and gives actionable suggestions about what to tackle next. In an online news environment where driving quality traffic and repeat engagement is key, the value of that kind of insight can’t be underestimated. Nanabhay says that his experience allows him to highlight exactly the kind of info news organizations are interested in, too, which helps set the site apart from more broadly-focused analytics offerings.

“Having spent years building up Al Jazeera’s highly successful Online and New Media divisions, I know exactly what sort of data is immediately useful to a newsroom,” he said. “Most analytics tool provide so much information that it becomes meaningless to the most journalists, editors or executives. This means they have to rely on folks with specialised analytics skills.” Rather than providing something only data scientists can digest, is designed to be used by anyone at a news organization.

While presents editorial staff with a way to empirically see what is and isn’t doing well on a news site by the numbers, Nanabhay is quick to note that he isn’t advocating an approach to producing content wherein pageviews outweigh all other concerns. Because of its focus on audience monitoring, the startup is destined to find a place in the heated debate about whether quality content should trump a virtual popularity contest approach. But Nanabhay thinks can occupy a sensible middle ground, rather than adding fuel to either side of the argument.

“Let me start by saying I don’t want to see a race to the bottom. Chasing cheap pageviews by doing Kardishan stories is not what any journalist really wants to be doing,” he said. “But hiding from data isn’t the solution. Editorial policy shouldn’t be made solely on numbers nor devoid of them. Rather, good data allows editors to understand what content is resonating with their audiences, and fine tune their work.” just introduced its closed beta, and also announced that it won the Knight News Challenge, which provides it with initial investment from the Knight News Foundation, a funding organization aimed at arts, journalism and community-focused media startups initiatives. The startup will be offering a tiered subscription model for its services once it launches publicly, allowing publishers to view insights on their own site, check out information about competitors and view the entire firehouse of information from all platforms (Twitter, blogs, etc.) included in’s monitoring system.


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