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Content Analytics: A Primer For Content Marketers & Publishers

If you’ve ever published content online, you’ve likely used Google Analytics to monitor how it performs. But, despite the ubiquity of Google Analytics, the platform wasn’t built for content marketers or publishers. The tool doesn’t sufficiently measure content performance because Google Analytics:

  • Only measures what happens on your website
  • Doesn’t measure true content engagement
  • Leaves valuable data out of aggregate metrics and averages

Being able to track and closely monitor how audiences interact and engage with your content is vital—and it requires a more specialized approach than traditional web analytics solutions (like Google Analytics) provide.

Content analytics is a more comprehensive option that’s tailored to the needs of content marketers and publishers. With content analytics, you gain access to specialized tracking, including metrics that are more accurate, reliable, and actionable for content creators and publishers.

Here’s everything you need to know about content analytics.

Table of Contents

What is content analytics?

Content analytics is a category of analytics tools specifically built to track the metrics that matter to content marketers and content-based businesses. Those metrics often include things like true engagement, top posts, and social referrals and interactions.

Content analytics tools help digital marketers learn which content truly resonates with their audience. They do this by providing a more accurate and reliable way to measure web sessions and to bring together engagement across various channels. Armed with that information, content creators are better equipped to produce more of the content their audiences want and respond to.

The benefits of content analytics

If you’re like many content pros, you’ve probably been using Google Analytics to measure your content’s performance—and it’s likely been working… okay. So why should you consider switching to a content-specific analytics tool to measure performance?

Because content analytics tools are designed for content marketers and content-based businesses. That means they offer several important benefits over traditional web analytics tools like GA.

More accurate and reliable engagement metrics

Content analytics tools measure engagement more accurately and reliably than traditional web analytics tools. Namely, content analytics tools can measure when visitors are actively engaged with your content—regardless of whether or not that engagement results in an action.

Google Analytics measures engagement only when the user clicks onto the next page. Content analytics can measure engagement regardless of whether or not there is a next page and can tell the difference between having a page open and truly engaging with it (more on this later).

This granular way of measuring engagement ensures that every session is accounted for in both aggregate and average engagement metrics. The resulting metrics are more reliable and more useful.

Additional, more actionable metrics and KPIs

Content analytics also gives content marketers access to additional, more actionable metrics than traditional web analytics tools can offer—for example, how long readers spend actively consuming content or how content performs across multiple platforms.

These metrics, measured, more readily capture the information content marketers and publishers need to inform content and editorial strategy.

Enables decision-Making in real-time

When you have a true measure of how engaged your audience is—along with the authors, topics, and platforms spurring that engagement—you can use that information to inform future content efforts (including topics, formats, channels, and authors). To that end, content analytics enables you to make more effective strategic decisions about which content to create, promote, and update.

Content analytics vs. web analytics: How are they different?

The primary difference between content and web analytics comes down to this: Web analytics tools focus only on what happens on your website, whereas content analytics aims to give marketers and publishers a holistic view of how content performs across all platforms and channels by comparing previously hidden metrics and correlations (for example, how a piece of content’s location on a site impacts performance).

That difference manifests primarily in the type of metrics and KPIs each type of analytics typically includes and how each approaches data collection and measurement.

Web analytics metrics and KPIs

If you’ve used Google Analytics to measure content performance before, you’re probably familiar with some of the commonly tracked metrics available:

  • Traffic and pageviews
  • Bounce rate
  • Session duration and pages per session

First, let’s talk about how Google measures web sessions.

When someone visits your website, Google drops a cookie into their browser that enables them to track that user’s behavior on your site. But here’s the thing: Those cookies measure engagement for a certain amount of time. When they expire, visitors have to take an action (reloading the page, for example, or clicking onto another page) to enable the tool to drop a new cookie and keep measuring.

The problem arises when you need to measure the complete visit. Google Analytics can’t measure the last page because there’s no next page. The “time-on-page” for the pageview of that last page is technically zero, and Google doesn’t include that visit in your average data. That means single-page sessions are left out of your data entirely if they don’t spur another kind of action. Our internal analysis shows that can lead to up to 40% of visits being left out of your aggregate data. Google also doesn’t differentiate between active time spent on your website and the time a page is open but inactive.

Content analytics measures true engagement

Content analytics tools measure website visits, sessions, and pageviews differently. Our analytics tool, Parse.ly, uses a “heartbeat” pixel to check in on the session every few seconds. This enables us to track whether or not the browser tab is currently open and if the user is actively engaged with the page.

Our proprietary algorithm isn’t reliant on “exit events” the same way Google is. So we’re able to accurately track the journey from initial pageview to the end of the user’s visit—without relying on the next pageview as an exit event. That means every visit gets tracked, even when it’s the last page of a session or a single-page visit.

Content analytics also measures the time during which a visitor is actively reading your content (versus when they just have it open amid a dozen other tabs in their browser). That means you can actually rely on the time-based metrics content analytics provides—because you know the visitor was actually engaged with your content.

Here are some of the KPIs and metrics that algorithm enables content analytics tools to track—metrics that web analytics tools simply can’t measure:

  • Total engaged minutes
  • Average engaged time (including for new vs. returning visitors)
  • Engaged time by topic
  • Top posts by author, section, or tag
  • Pageviews by author
  • Social referrals
  • Social interactions

How do you know if you’d benefit from these metrics? Let’s look at some companies already using them.

Content analytics use cases: Who uses them and how?

Google Analytics and other traditional web analytics tools are popular. Many people and brands use them because they’re capable tools for some use cases. Content just isn’t one of them.

So who benefits from content analytics tools? In our experience, two broad groups:

  • Publishers in the media space (Condé Nast, for example, or Slate, Bloomberg, WIRED, etc.)
  • In-house content, marketing, and comms teams (typically content marketers, social media managers, SEO specialists, and similar roles)

Each of these groups needs to understand how their audience interacts with published content, along with how individual content performs across authors, topics, digital channels, and more. They need this information in order to gauge performance and make game-time decisions about which content to prioritize for creation and promotion.

Specific Use cases and customer stories

To better understand how both publishers and content marketers use content analytics, let’s take a look at some of our own customers, along with how they’ve used and benefited from Parse.ly’s content analytics tool.

1. WeddingWire

WeddingWire is a global marketplace that connects couples with wedding vendors for their big day. They’ve used Parse.ly’s content analytics solution since 2017 to help grow their organic search performance.

Parse.ly metrics help them decide when to update content based on the growth and decline of its search traffic, monitor the top posts for each search referrer, and choose which articles to optimize for which keywords.

Morgan Gibson, WeddingWire’s senior manager of digital content, said, “My philosophy is that in order to create good content, you have to equip your editors with tools and the understanding of what good content is, so you can make more of it. Giving the team Parse.ly empowered them to become more analytics-driven.”

You can read the full case study here.

2. HelloFresh

HelloFresh is a meal kit delivery service that allows customers to choose from a variety of recipes and receive a weekly box filled with all the ingredients and instructions they need to make those recipes for themselves.

According to HelloFresh copywriter Jacqueline Parisi, their content team had been flying pretty much blind—because “it was cumbersome to dive into the depths of the Google Analytics world to find insights worth sharing or acting upon, so data got deprioritized.”

With content analytics, they were able to develop a simple and streamlined analytics dashboard to report on total engaged time, social and search pageviews, app pageviews, and social interactions and referrals. Thanks to that data, they were able to enact a more data-backed content strategy and better prove their value to the broader HelloFresh team.

Read the full HelloFresh case study here.

3. Bloomberg

Bloomberg is a business news website that covers global business, along with stories on more regional and localized events and news. Before implementing content analytics, the team at Bloomberg assumed the priorities and interests of their readers across the world varied, but they didn’t have any data or mechanism available to prove it—or to figure out what content readers outside the U.S. were interested in.

According to the company’s Managing Editor of Digital Katie Boyce, “Anywhere where we had a regional edition of our content… we were able to look at the geo-segmentation and decide what stories are resonating.”

Segmenting their content analytics by geolocation allowed Bloomberg to promote the most relevant content by region, balance local and global news, tap into regional social media trends, optimize for varied social media habits, and gauge regional reactions on social media.

You can read the full case study on Bloomberg here.

How do content analytics tools work with CMS tools?

Many teams use a content management system (CMS) to publish and host their content. While these systems are great for publishing, they only provide very basic analytics capabilities. They aren’t designed to offer true content analytics.

A CMS, for example, won’t be able to tell you where your traffic is coming from, how people are interacting with it across social media, or how it drives conversions. But that information is critical for modern content pros—and that’s where integrating a content analytics solution into your CMS comes into play.

It’s for this reason that many content analytics tools offer turn-key integrations with popular CMS tools, like WordPress, Drupal, and Sitecore.

Once integrated with your CMS, content analytics tools automatically pick up on all the key attributes of your content, including the metadata you provide (typically for SEO purposes) and derived metadata like word count and topic. You can then parse performance by different metadata groupings; for example, you can see the impact word count, content type, and even location on the website have on engagement.

This granular performance tracking allows you to unlock real business value from content and make decisions based on data, not hunches.

Parse.ly: The top content analytics solution

If you’re sold on the value and potential of adding a content analytics tool to your stack, we suggest Parse.ly.

We’re confident that our content analytics solution is the best way for marketers and publishers alike to gain a deeper understanding of their content, their audience, and the intersection between them. That’s why some of the world’s top websites already use Parse.ly to:

  • Improve and duplicate content that works.
  • Update and fix what doesn’t.
  • Test new ideas.
  • Show readers the content they’re looking for.
  • Deliver more business value.

Our tool gives content creators access to subscriber tracking, robust options for audience segmentation, and 30 unique attention metrics that help uncover where readers come from, how you can increase readership, and how to more effectively engage your audience.

With Parse.ly’s plug-and-play integrations, you can start using our tool to analyze both real-time and historical content performance right away. And, unlike traditional web analytics, Parse.ly enables you to view content performance holistically across social media channels and various web and mobile platforms, regardless of content format or type.

Content analytics doesn’t end with a treasure trove of data—and neither does Parse.ly. Not only do we show you the data and give you insights, but we also let you automatically leverage your data through our API.

The API makes it possible to turn data into better content performance and real business value. For example, you can use the API as a recommendation engine that automatically uses your content data to recommend the most relevant content for each reader, driving more shares, clicks, and engagement. Through a combination of historical content consumption, profiles, and behavioral patterns, the API customizes what content returning readers see and interact with. This leads to higher engagement over the long-term.

Wrapping up

Content analytics is the best option for modern content creators and publishers looking to better understand their audience and create more relevant, engaging, and effective content. If that sounds like you, chat with one of Parse.ly’s product specialists today about how we can help you along the way.