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The foundations of audience data: 3 practical ways to start using data in your newsroom

As news readership shifted from print to digital, data became a central part of many newsrooms. For the Financial Times, data is incorporated into many processes including determining which stories drive high quality readership, motivating new subscribers and decreasing churn, and creating and improving products. It was essential to the FT’s journey to reach over one million paying digital subscribers.

Many other newsrooms are still at the start of their data journey, unsure of which data points are useful and how to put them into action. In this blog we explore three practical ways for newsrooms to start using data in decision-making.

A quick reminder: what do we mean by data?

Data is a collection of facts which can be measured, analysed and used to inform decisions. It comes in two main forms: quantitative and qualitative. Quantitative data is numerical, such as total monthly readers or the percentage of readers who visit from mobile. Qualitative data is descriptive, such as text or audio quotes directly from readers. Both forms help newsrooms to learn more about their readers.

Data is the starting point, not the final product and should be checked for relevance and accuracy before being combined and analysed. At this point, you can extract insights and amplify them to inform your newsroom and wider business decisions. Below are three ideas for how to do this.

Example 1: Measure and share content metrics

Some publishers have been resistant to measuring content metrics and seeing how many people are reading their journalism. They have valid concerns that relying solely on these metrics could lead to newsrooms prioritising widely-read but less significant stories, such as prioritising entertainment over climate coverage. However, content metrics should be used alongside editorial judgement. If you understand what engages readers and consider what influences them, such as the headline, topic, or placement on the site, you can use this to inform commissioning and distribution.

Some key content metrics are:

  • Page views: a count of every time the article has been loaded
  • Users: how many people have visited the article
  • Time on page: how long a person spends on the page

Page views and users unearth the total volume of traffic. Time on page develops beyond this and can be used as a proxy for engagement: if a reader is spending longer on an article, they are more likely to be reading it in full.

It’s important to share this data with your newsroom, such as highlighting the previous day’s top stories in morning news meetings or sharing a weekly roundup of the highest performing stories via email to the team. This can help to raise awareness of what readers are consuming and prompt team members to think of solutions to boost low-performing content.

Example 2: Learn who your audience are

Another key data set is demographics, which describes audience characteristics. Demographic data usually includes factors such as age, gender and geographical location. This data can be harnessed through audience analysis tools like Google Analytics, investing in first-party data collection, or by asking demographic questions in audience surveys.

From here, a basic understanding of your core reader base combines with article performance to drive further insights, such as whether men are more likely to read certain topics compared to women.

At the FT, demographic data helped highlight a gap in our current audience. As the FT’s Head of Strategic Insights, Lindsay Nicol, told FT Strategies on our podcast, demographic data helped her team discover that the FT was reaching less women than men. They raised awareness of this issue throughout the organisation – which led to a cross-functional team working on various initiatives to grow women’s readership, such as identifying which content women were engaging with and their reading habits.

Example 3: Understand your users’ habits and needs

Exploring how readers are using your products can reveal which features are most valuable to users and where improvements can be made. One way to collect this data is hearing from readers directly through surveys of both qualitative and quantitative data. Surveys can be short and simple with a few data points, or deeper with more questions and a wider scope.

A key part of the FT’s output is newsletters, which allow readers to sign up for updates on interesting topics directly to their email. Newsletters are useful because they are a free product with high engagement; important for converting and retaining subscribers. Learning more about the needs and interests of newsletter subscribers has been an area of high interest, so the Newsletters Team collaborated with the Audience Feedback Research Team to measure the success of newsletter products.

The team designed a short survey, including an open text question where newsletter subscribers could suggest improvements. Responses were analysed for key themes and shared with the newsletter team. For instance, if many readers commented that a newsletter is too short, the editorial team considered lengthening it. If readers enjoy the writer’s personality, the writer can afford to be more expressive. This highlights how surveys are useful for direct feedback from readers – rather than just assuming what they like and dislike – and then putting their feedback into practice.

Understanding newsroom data helps you move beyond assumptions about your audience to understand what they’re really thinking, reading and who they are. Extracting insights from data and amplifying them to your newsroom can open up new ventures – from understanding audience engagement and opportunities to diversify readership to improving products based on reader feedback.

At FT Strategies, we’ve supported publishers at all stages of their data journey with building a data-informed newsroom, and we can help elevate your audience analysis using insights from our own organisation. If you want to find out more, please do not hesitate to reach out to us.

About the author

Sarah Dear, Data Analyst
Sarah Dear
Sarah Dear, Data Analyst
Sarah Dear
Sarah Dear, Data Analyst
Sarah Dear
Sarah Dear, Data Analyst
Sarah Dear
Sarah Dear, Data Analyst
Sarah Dear

Sarah Dear is a Data Analyst at FT Strategies. She is experienced in delivering audience insights and strategic growth and has previously worked at HuffPost and The Guardian. Sarah has a Master’s in New Media and Digital Culture from the University of Amsterdam, where she specialised in the digital transformation of the news industry.

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