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Editorial Analytics: The Missing Link in Monetization

This is a guest post by Uyen Tieu, the co-founder and CRO of Rumble. She is a seasoned executive in figuring out how media companies make money and how they morph onto new platforms.

analytics

If you’re a traditional content publishing company, the digital age has already been a disruptive force in your industry for a good number of years.

The leaked New York Times Innovation Report serves as yet another wake-up call for the industry. The report highlights how this iconic news organization is seeking innovation, and where news organizations can improve or adopt new strategies. One way to get there is to arm the editorial team with the analytic tools to help drive unique content, readership, engagement and ultimately monetization.

To date, many organizations have invested heavily in advertising analytics to translate user data into hard cash. These analytics teams — consisting of ad technology partnerships, data scientists and statisticians– work closely with IT and the business management team to deliver a robust technology and help guarantee ROI for advertisers. However, this operational structure to date has excluded the most crucial group of a media company’s brand and product: editorial.

What the New York Times Innovation Report signals to editors is that they need to become more involved with the analytics of not just their users, but also the analytics of their content. In a world where you cannot sit on your laurels, where a strong brand does not guarantee high traffic and where there are infinite options of where to get your news, discoverability and relevancy are critical players for an editorial team. By playing a greater role in data analytics, editors can continue to make great content, but also be empowered to make business decisions that enable the monetization of their content.

Page views alone won’t cut it as editors also need to understand which articles are resonating. Data tagging is a great tool to help navigate their content through the social media waters to convert into traffic. As there is a louder drum beat for native ads editorial analytics will help editors know what is most valuable and how to best design the native ads.

The availability of data analytics enables editors to see the lifetime value of their content, and help surface archives that can also drive traffic. For instance, as the situation unfolded in Ukraine, a lot of people started to search about the Ukraine and its relationship with Russia. If editors have access to their publication’s archives about these two countries, they can repackage this with their current coverage in a more dynamic way that can potentially retain loyal readers and attract new ones, as they link to relevant historical articles. With great data tagging, this can be automated.

And finally, analytics enable editors to defend their content decisions based on readership trends. This trend data also help editors operate a more efficient newsroom by allocating reporting resources where they are most needed. For example, tech editors can determine how many reporters they will assign to cover the soon-to-be-launched Apple iPhone 6 based on the traffic and engagement generated by coverage of previous iPhone launches, as well as buzz leading up to the main event.

Editors can also determine the type of content format that will drive the most engagement. Should the coverage have a video component, or allow reporters to be more active in socializing the content? Would a live blog of the launch be well-received by readers? Content data analytics can provide the answers to these and other pertinent questions.

Without content-focused editorial analytics, business decisions are often based on a whim or gut reaction, both of which puts publishers at a crippling disadvantage as they compete with data-savvy digital content publishers, such as The Huffington Post and BuzzFeed, and for ad dollars against Facebook and Twitter.

With the right analytic tools, editors can fuel content to cater to the tastes and preferences of their readers, while the business function can use this data in their monetization efforts. Ultimately, the strength and flexibility of technology decisions that include both the editorial and business management teams will drive the success of a digital news strategy.

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