content analytics

What is content analytics?

Content analytics, also known as content intelligence, is the process of measuring and analyzing how users interact and engage with digital content. Organizations can use these analytics to understand how their content is performing and, from this information, determine the best ways to optimize their content strategies.

Content analytics can apply to digital assets of all types, including blog posts, news articles, podcasts, videos, social media posts, text documents and standard webpages. A content analytics platform measures the performance of each published asset by tracking key metrics -- such as pageviews, engagement times or number of unique visitors -- and then analyzing the collected data to provide a deeper understanding into the ways people are engaging with content.

The goal of content analytics is to gain new insights into existing content. These insights can then be used to define strategies for optimizing the content to better attract and engage the website's visitors.

For example, content analytics can show how visitors find a site's articles. They might click on links to the articles from search engines, embedded ads, social media or any combination of these and other sources. The organization can also learn how long its visitors spend on each article and the rate those visitors are signing up for the newsletter. Through such information, the organization can better understand what types of content resonate with visitors and where to focus its marketing efforts.

Content analytics tools

To perform content analytics, organizations need tools that can collect the necessary performance metrics, process that data in meaningful ways, and deliver clear and comprehensive reports that provide insights into how users are interacting with the content. Many of today's content analytics software products use natural language processing, machine learning algorithms, contextual discovery, predictive analytics or other advanced technologies to uncover patterns and trends in the target content. Examples of such tools include Google Analytics, HubSpot, Semrush and Qualtrics.

As part of this process, the software relies on a wide range of metrics that measure the degree to which users are engaging with content. These measurements provide multiple perspectives of visitor interactions, helping to paint a more complete picture of the content landscape and how it might need to change. The following metrics provide a cross section of some of the more common types of information that the different tools track:

  • Backlinks. These are the number of links on external sources that point to the content on the monitored website.
  • Bounce rate. This is the percentage of viewers who view only one page and leave the website without engaging in any significant way.
  • Comments. This is the number of comments associated with a post, article or other asset.
  • Conversion rate. This is the percentage of visitors who complete a specified activity, such as downloading an ebook, signing up for a newsletter or creating an account.
  • Downloads. This is the number of times that a specific asset was downloaded.
  • Engagement times. This is the amount of time that users actively interact with the content.
  • New visitors. This metric is the number of users who hadn't visited the website before or have not visited within a specified time, such as the previous 30 days.
  • Organic search. Organic search results are the number of visitors who found an asset on the website through a search engine.
  • Pages per session. This is the average number of pages viewed during a user session.
  • Pageviews. This is the number of times that an individual asset was viewed.
  • Returning visitors. This is the number of users who had visited the website before or visited the site within a specified time, such as the previous 30 days.
  • Shares. This refers to the number of times an asset was shared.
  • Unique visitors. This is the number of unique visitors to the website.

Content analytics tools can track many more metrics than those shown here, although they don't necessarily track the same ones. For this reason, organizations should carefully vet any tools under consideration to ensure that whatever they choose can capture the required information. Just as important as the metrics, however, is the platform's ability to analyze the data and provide comprehensive reports that lead to actionable insights into the target content.

Learn how companies can engage their users with these real-world multichannel marketing examples.

This was last updated in January 2024

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