Rebel Insights

Is There an Optimal Article Length? Chartbeat’s Data on the Relationship Between Word Count and Engagement

Is There an Optimal Article Length? Chartbeat’s Data on the Relationship Between Word Count and Engagement

This article was originally posted on the Chartbeat blog. Chartbeat’s real-time content analytics, historical dashboards, and optimization tools help the world’s leading media organizations understand, measure, and build business value from their content.

Publishers have always had to weigh the risks and rewards of quick news bulletins and deeply-reported longreads. Write too much and you might lose readers who are just looking for the facts. Write too little and you might cut the sections that turn those casual visitors into loyal readers.

While striking this balance is the responsibility of a good editor, one of our responsibilities is to uncover data and insights that make those decisions easier. It’s in that spirit that our Data Science team recently investigated the relationship between word count and engagement.

We sought to find out how Average Engaged Time changes as word count increases and how editorial teams can use this data to optimize their content. More on those findings below.

Average Engaged Time Increases With Word Count, up to a Point

In the undertaking of this study, Chartbeat’s data scientists analyzed millions of articles of 10,000 words or fewer that were published between January 2019 and April 2022. With a global network of publishers, languages, and grammar rules in the same dataset, this was not as simple as scraping HTML and calculating engaged time, but our team was up to the challenge and delivered a trove of data illuminating the relationship between article length and engagement.


When we plot Average Engaged Time by word count, two clear patterns emerge:

  1. Between 0 and 2,000 words, Average Engaged Time increases as word count increases.
  2. Once word count grows beyond 4,000, the variability in engaged time also grows, and the return on additional length is less certain.

In other words, we can confidently say that for articles of less than 4,000 words, the longer the article, the more engaging it will be. Beyond 4,000 words, however, the interval of expected engaged time varies much more widely, and we can no longer conclude that engaged time will increase with word count.

While this doesn’t mean that there is no more engagement to be had beyond this point, it does mean that performance will depend more heavily on how well optimized a page is for engaged time after publication. This data also allows you to benchmark your articles of various lengths against our global averages.

Decoding the Binned Scatterplot

Since we frequently use bar and line graphs in our research presentations, it’s worth pausing here to explain the graphic above. Rather than plotting millions of articles on one graph, the binned scatterplot uses one dot to represent the Average Engaged Time of all the articles published at a given word count. For dots that are intersected by a line, this denotes the expected range of engaged time for an article of that length. From 0 to 2,000 words, the variation is only hundredths of a second and the dot is essentially also the line. Around 10,000 words, the range visibly stretches to almost 9 seconds.

If we look at the 6,000 word mark as an actual example on the graph, the dot tells us that the Average Engaged Time for all articles of 6,000 words is 80 seconds. The line through the dot then shows us that the least engaging articles of 6,000 words receive about 77 seconds of engaged time, and the most engaging receive about 83 seconds.

The Majority of Articles in Our Network Are Far Less Than 2,000 Words


After discovering that articles between 2,000 and 4,000 words get more engagement than shorter articles, we wanted to see what proportion of total articles fall in this range. Not only did very few articles register more than 2,000 words, but the majority of articles came in at fewer than 500 words.

While the Average Engaged Time for 500 word articles is in line with recent global engagement benchmarks, the difference between a 500 word article and a 2,000 word article is nearly 30 seconds of engaged time.

Word Count and Engagement by Loyalty

Since engaged time is a strong indicator of loyalty, we also looked at this data by visitor type. We found that the average percentage of loyal readers, or readers who have visited a site at least 8 of the last 16 days, is highest on articles of 2,500 words or fewer.


We’ve previously found that loyal readers tend to read more pages per visit but spend less time on individual pages, so it’s not surprising that longer articles would see more new and returning visitors.

Word Count and Engagement by Device Type

When we look at word count and engagement by device type, we see that the crest of Average Engaged Time for both devices occurs around the same word count as the larger study.


Though mobile referrals generate more pageviews than desktop, they haven’t quite caught up when it comes to engagement. As the graph shows, this doesn’t mean that readers aren’t willing to read longer articles on mobile, and engagement strategies should be mindful of the different experiences by device as you execute your optimization strategy.

Using This Data to Optimize Your Content

As you incorporate these findings into the other data and experiences informing your audience engagement strategy, remember that curation and optimization – not word count – will ultimately dictate how much of your content gets consumed. These benchmarks are an additional tool for diagnosing article performance, and when used with real-time analytics, can make your content more engaging before and after publication.

Here are our key takeaways from the research:

1. Between 0 and 2,000 words, Average Engaged Time increases as word count increases.

Our analysis shows that up to almost 4,000 words, the longer article, the more engaging it will be. If your articles are falling short of the benchmarks we’ve shared, a real-time optimization tool like our Heads Up Display can show you how far readers are scrolling and give you an opportunity to make changes at the point of exit.

2. Beyond 4,000 words, variability in engaged time grows, but that doesn’t mean there’s a ceiling.

As we see with our year-end list of the most engaging stories, unique topics can require more depth than daily reporting. This doesn’t mean you should shy away from covering them. It just means you’ll need to devote more attention to optimizing these pages for engaged time.

3. The majority of articles published across our network are less than 500 words.

Not every story can fit snugly between 2,000 and 4,000 words, and we’re not suggesting they should. Articles of all lengths have their place in your content strategy, and can be used together to increase recirculation and engagement. For example, if a brief piece of breaking news goes viral via Search, use well-placed links to drive that traffic further into your site to more engaging articles on similar topics.

4. Engagement should be evaluated on all types of content.

Even after all of our reporting on the way Average Engaged Time increases as word count increases, this article totals only about 1,300 words. If we had additional data and insights that added value, we would gladly include them and expect to further engage our readers. Since we do not, in the days after publication we’ll be monitoring our Historical Dashboard to see if it’s generating around a minute of Average Engaged Time, the benchmark for articles of similar length.

Want more data to fuel your content strategy? Check out more insights from Chartbeat that shows engagement time is increasing despite dips in web traffic overall.

Ready to make the most of modern publishing? Request a proposal to take your website to the next level with RebelMouse.

What Is RebelMouse?
Request a Proposal
Meet the RebelMouse Platform: The Highest Performing CMS on the Web
Rebel Insights

Meet the RebelMouse Platform: The Highest Performing CMS on the Web

Make sure your site is set up for success in 2022.

In the spring of 2020, Google let the world know that its Core Web Vitals would become the new benchmark for measuring a site's performance in its search results, known as the page experience update. Fast forward to more than a year later in August 2021 when, after much anticipation, Google's page experience update became official.

Since its rollout, developers have felt the impact of how their publishing platforms stack up against the new standard. Important decisions around the architecture of your site can now make or break your site's performance in the eyes of Google.

HTTP Archive, a tracking platform that crawls the web to identify trends and record historical patterns, frequently reports on how top content management systems (CMS) have weathered the page experience update through the creation of its Core Web Vitals Technology Report. RebelMouse has consistently outperformed major CMS platforms on Google's most critical metrics throughout the year:

Getting superior scores on Google's performance benchmarks isn't easy, either. The Ahrefs blog analyzed Core Web Vitals data from the Chrome User Experience Report (CrUX), which is data from actual Chrome users, to see how the web stacks up against Core Web Vitals. Their study found that only 33% of sites on the web are passing Core Web Vitals.

data from Ahrefs tracked on a line chart finds that shows only 33% of sites on the web pass Google's Core Web VitalsFrom Ahrefs.

Luckily, performing well on Core Web Vitals is possible with thoughtful, strategic changes to your site’s codebase. Here's what you need to know and how we can help.

Keep reading...Show less
Multivariate Testing: An Introduction to Data-Driven Site Design
Rebel Insights

Multivariate Testing: An Introduction to Data-Driven Site Design

Understand the differences between multivariate testing and A/B tests

The modern digital landscape is founded on one critical element — data. From content creation to site design, there’s no reason to take chances on what will resonate with your audiences. Adopting a data-driven mindset means you can take the guesswork out of your business strategy and focus on the methods that are actually moving the needle.

And one of the best ways to figure out what strategies are moving the needle for your website is through multivariate testing.

What Is Multivariate Testing?

Multivariate testing is the process of testing one or more components on a website in a live environment. These components can be anything from a CTA button, headline formatting, or even an entire page design. The beauty of multivariate testing is that you can test each one of these individual features on a page to see what performs well among your users.

Think about it for a moment. Creative teams with great ideas are most successful when they have an environment where ideas can easily be tested against each other instead of trying to find total agreement on one idea. Multivariate testing allows teams to cherry-pick each idea to create an end result that works best, backed by the data to prove it.

multivariate testing allows for various layout designs and element placements to be tested live to see what attracts the most readershipSee which elements and layout designs attract the most readers with multivariate testing. Graphic from Invesp.

Multivariate Testing vs. A/B Tests

Traditional A/B testing is the process of creating two different layouts and splitting the traffic between the two to see which one performs better. It’s possible to test more than just two layouts, of course, and there’s no issue with creating A/B/C/D/etc. tests depending on how many layouts you have to try.

A/B tests can produce great results, but they are limited since they test an entire layout at once. Remember, multivariate testing allows you to test the different components of a layout individually. Think of multivariate testing as running multiple A/B tests at one time. Here’s a good illustration of the differences between A/B testing and multivariate testing from HubSpot:

A/B testing compares two layouts as a single page, while multivariate testing allows for multiple elements to be tested simultaneouslyAn illustration of the more complex testing available through multivariate testing. From HubSpot.

Multivariate testing is a great way to help creative environments stay focused. However, it’s vital that all ideas get measured, because one idea might sound awesome to the group or a team member, but it may not always perform.

How Do I Know When to Use Multivariate Testing?

If you are looking for fast results, it’s best to use A/B testing. However, multivariate testing is the preferred choice if you have the time to analyze and review multiple data points. Combined, the testing on each one of your site elements will help you curate the highest-performing page possible. It’s also recommended that you use multivariate testing on your pages with the highest traffic because there will be more data to analyze to determine which site elements are garnering the most engagement.

Keep reading...Show less
Interested in a Free Website Health Check?Check Your
Website's Health
Get Your Free Analysis Now