Content analytics

Calculate which content drives most revenue and engagement

With the Content Analytics market expected to reach USD 12.76 billion by 2026 (Mordor Intelligence), companies are building an ever-more-detailed understanding of how users interact with their content.

A warehouse-first approach to content marketing can unlock new worlds of information. With detailed event-level data (aka. behavioral data) in a well-understood central storage location you can start to rationalise every decision you make about where to invest your time and resources, as well as massively increasing engagement and revenue.

More detailed tracking enables fully data-led decisions

Snowplow offers more granular fields and metrics than other providers. You get 130 fields populated right out of the box, which can be used immediately to get deeper insights into content engagement. You can also create unlimited custom fields.

This opens up the possibility of a fully data-informed content strategy, as you invest your time and resources into the site sections, content types, and styles which are working.

Which content analytics use cases are possible?

Here are some of the more advanced content analytics use cases.

  • Match content to individual users or user groups: this can be based on working out which types of content lead to the most conversions for a given segment or which content drives more engagement.
  • Real-time content recommendations: serve the right users with the right content at the right time with second-by-second accuracy.
  • Create a clear picture of content interactions: use data to show which parts of a page are working for a certain user or group of users, this can be as granular as the seconds of a video watched or the horizontal scroll depth of a carousel. 
  • Create advanced automations: adapt the content of a page in real-time based on user behavior. This can help find the ideal placement for an image or which quote to choose, for example.
  • Discover what is driving the most value: identify your highest-value readers, staff writers, and which content is generating the most revenue.

A content analytics use case

The Globe and Mail is Canada’s leading news media provider, with a weekly readership of 6.1 million.

The Globe and Mail’s AI platform uses behavioral data captured by Snowplow in some incredibly advanced ways. The most important of these is in the creation of a composite weighted content score, known as the ‘Sophi Score’. 

This score takes into account the ‘value’ of a piece of content across different platforms, depending on what the platform deems its purpose to be – from advertising revenue, and subscriptions, to retention and email registrations. 

Some of the benefits of their approach are:

  • It gives journalists a better understanding of how their work supports the commercial objectives of the organization
  • It enables newsroom chiefs to allocate resources based on established trends 
  • It helps editors decide whether to paywall an article (rather than rely on guesswork)
  • It calculates and compares the expected ad and subscription revenue of an article, and makes a predictive decision based on what would bring the most value to the business.

“Sophi has helped The Globe and Mail move from a 70% advertising revenue and 30% reader revenue split, to a 30% advertising and 70% subscription revenue split, and it’s not losing market share on the advertising side. ”


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