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Editorial Audience Data Analysis – New Metrics for Content

A new study by the Reuters Institute preaches for the development of a tailor-made data analysis approach for editorial decision-making: reaching people sustainably, mastering the stakes of content in the light of the economy of attention, integrating a non-tyrannical data analysis grid, and resonating with the content strategy.

Data analysis and editorial, a matter of priorities

In editorial planning meetings, traffic data and other analytical results are now ubiquitous. These metrics have become crucial in editorial decision-making, whether at the level of large companies, news media, advertisers or startups. From now on, the behaviour of the hearings is placed at the center of the preoccupations and the strategies of content .

This is a good thing, but is a traditional use of these tools and techniques really relevant to content marketing? Are the figures analyzed and interpreted correctly by the drafting committees? According to a new study published by the Reuters Institute of 30 startups, newspapers and broadcasters, data analysis is unfortunately often restricted to the short-term optimization of page views and the number of unique users. A little short, as the other would say.

However, some organizations surveyed stand out. They have developed a data analysis approach for the editorial. That is to say, a personalized approach aligned with editorial priorities, in support more than cantilever of the content strategy.

Analyzing Data for the Editorial: The 3 Fundamentals

In an editorial, the analysis of data cannot be entirely shaped by advertising, commercial or technological priorities. Instead, it must inform sustainable, evolving and contextualized decisions.

In general, any analysis of data must be adapted to the sector, trends and organizations. This is even truer for the editorial. The conclusions of the Reuters report thus show three main specificities:

  1. The editorial has its editorial priorities. The content has specific roles and objectives, linked to DNA and brand discourse, to dissemination media, to acquisition and conversion methods.
  2. The editorial works in the short, medium and long term. The content reaches audiences immediately, but also builds a storytelling, a relationship … and a virtuous cycle of loyalty.
  3. The editorial is continually evolving. The content follows the rhythm of a changing media environment, as well as the rhythm of cross-media and transmedia reading habits.

In an editorial, the analysis of data cannot be entirely shaped by advertising, commercial or technological priorities. Instead, it must inform sustainable, evolving and contextualized decisions.

How to implement an editorial data analysis?

The recommendations of the Reuters report to put in place a data analysis approach adapted to the editorial are in the direction of better integration of the stakeholders and a need to create tailor-made.

Here are some ideas:

  • Democratize data using user-friendly interfaces
  • Create criteria and KPIs specifically for organization and culture
  • Integrate parameters that underpin long-term editorial priorities
  • Implement agile and scalable analysis models
  • Develop a data culture with a positive focus on curiosity and interest
  • Involve editors and teams at all levels

Of course, the data never tell the whole story. And even the best approaches are sooner or later confronted with a range of issues related to data quality and access. This is why an editorial analysis of relevant and functional data must reinforce the editorial decision rather than direct it.

It must concentrate on analyzing the best quantitative and qualitative data available without introducing a tyranny of numbers. A condition sine qua non to stay in the race to attention.



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