KPIs & User Journey Metrics for Marketers: Part 3

In the first post of this series on content analytics, I talked about the old way of measuring your marketing content with key performance indicators (KPIs) and why you can’t rely on old measurement models for new media channels. In the second post, I offered an analytics framework for measuring content KPIs along a user-journey continuum.

This leads me to the third post in this three-part series on measurement. In this post, I’m focusing on how you can measure the actions on the page to determine how users are interacting with your content. Or not.

Of course, there’s a rather basic problem here. You want to measure the performance of your content and tools, but most reports are just measuring the page itself. We want to measure the components.

Next, let’s look at the ways that we can tag and measure these components and how we can better serve our customers by understanding the content that matters to them. This requires a bit of history.

Origins of Website Measurement

In the early days of analytics, we sifted through log files. Every page logged some sort of text data into a file that was designed to help us understand what was happening on our websites. We’d open these massive files (by 1990s standards) in software applications like WebTrends.

Even then, there was too much data. We would slice it in a variety of ways to get insights like “how many hits did we get to our website today?” It seems rather quaint and basic by today’s standards, but you’d be surprised at how many people with blogs and websites don’t even check their analytics these days.

At some point — I think it was the rise of free analytics through Google Analytics — we moved away from log files to analytics triggered by JavaScript.

As long as you put that little bit of JavaScript code into every page, you had access to vast amounts of useful data, including the keywords that were driving people to your website. (Wow, that was useful. I hope they bring it back soon.)

You could get key insights that told you how people were interacting with your website. This free tool just kept getting more robust and useful. If you had a good analytics team working with your editorial team (we didn’t call it content strategy yet), you could understand which pages were being visited by your users. You could also understand how users navigated your website, which was huge.

These days, Google Tag Manager gives useful details about what people are doing on a particular page, not just the fact that they reached your page. At one time, there were workarounds, but now it’s a standardized solution that will help us in our quest to measure our content.

Component Content Analytics

When you measure the content and resources of your individual pages, you’re really looking at the components as separate, but related assets. I don’t see anyone else really using this phrase, so let’s just call this Component Content Analytics.

With Component Content Analytics, we’re analyzing the individual components of the content on a website to understand user behavior.

Think of it this way: you have two videos of the exact same length on your webpage. Which one is being viewed more often? Where do they drop off? You can measure how many people reached the page, but you’ll get some greater insights if you actually know which of those videos is being watched and for how long.

Let’s go back to the basic user journey.

User journey map with pre-seekers and evangelists

In the example above, I’m showing that there is a progression of learning and discovery by your user. This is their journey, not exposure to your brand, but you can align your content to their learning journey.

People early in their user journey will be most interested in Seeker content, move into Considerer content, and eventually into Active Solution content. That’s their journey, but from the example above, you can see how the brand can provide content all along this user journey.

The content you provide at the early part of their learning journey is not the same content you provide after they become your customer. The content that they access gives you an indication of where they are in their personal journey.

You can measure the fact that they hit a particular page and call it a day. Or you can go one step further and see what they are doing with the components on that page.

Three Levels of Measurement

Typically, I recommend that we measure three levels of activity on a standard webpage. This framework may not scale for all mediums, so let’s just focus on where it does work.

Three levels of activity:

  • Exposure
  • Engagement
  • Action

Let’s look first at Exposure.

Exposure metric in Analytics

Exposure is like a hit to your webpage. While you can’t tell if they did anything, you can know that someone reached a specific page. That’s a classic KPI that spans old and new media. It’s the lowest-common denominator of website analytics measurement.

Exposure means that someone had it up on their screen. We’re not talking about time on page, if they bounced, or how they navigated there, we’re just measuring the basic fact that they got there. Exposure has a basic value, which you can determine on your own, but it’s worth measuring it on a scale.

Looking at the slide above, you can imagine a dollar sign in front of those numbers. That would indicate how value increases with the user journey. The Seeker content (value = 1.1) is basic information that suggests that a person is currently some distance from the ultimate destination of being your customer.

If you go back to Part 2 of this series, you can review how to measure your content along a user journey.

The next level is Engagement.

Engagement measurment in a user journey

If Exposure is seeing your content, then Engagement is interacting with it. Engagement measures the action someone takes with your content.

The term Engagement is sometimes utilized to reference time on a webpage. This is incorrect.

I hear people proclaim “they spent 2 seconds longer on this page as compared to last month, which means they are really engaged.” Extra time on the page can be attributed to people who are slower readers or that they left their browser window open. You can’t look at time on site and leap to the conclusion that this indicates engagement.

Engagement is something that shows that they did something beyond arrive at the page. An engagement is clicking on a video, using a tool, downloading a PDF, or doing something that goes beyond the basic exposure on your page. We are measuring the micro components on the page, not just the fact that the page exists.

This is an important distinction and one that you can and should measure. Of course, not every page has components that a person can click on beyond a basic hyperlink. If you want to measure an Engagement metric, put a component on the page for people to click.

(It’s worth noting that not every page will have components for you to measure. Google Tag Manager offers a lot of ways for you to tag elements on your page, so work with an expert to guide your content strategy measurement plan.)

You’ll notice in this framework that the analytics stepped up one level. That’s because the click/action indicates that someone was interested enough to move the mouse and do something. The value metric KPI steps up and is relative and consistent with the user journey. Easy and logical.

Here’s where it gets a little controversial.

The next level is Action.

Action stage in content marketing analytics

Analytics framework for Content Marketing: Action Stage

Action is when someone willingly exchanges their anonymity for information of some value. In my example, users only give up your information if they see value in the exchange.

Perhaps you are researching a solution, you’re planning to become a customer, or you are actually an active customer. These are times when you voluntarily drop the veil of anonymity that we enjoy on the Internet and connect with a brand or solution.

This measurement is designed for or websites for content marketing purposes. It does not apply to sites where the value proposition of the brand is actually the content, like Twitter or Facebook.

If a brand creates and makes content freely available, that’s content freely available for marketing purposes with no information exchange required.

Sometimes a brand will want to keep certain content behind a firewall. Content like this may include pricing or some other detailed information that exceeds the information a brand is willing to publish.

There are other resources, including newsletters and coupons that may require an email address or phone number. This indicates a level of Action by the user that is beyond basic Exposure or Engagement.

Take another look at my analytics map. Some people have challenged the idea that this only happens at the end of a user journey. They argue that people in a Considerer mode may have comparison questions, which indicates that they are still at the Considerer stage.

I agree that this can be true, but argue that this same user will exhaust other options that maintain anonymity before creating a relationship with a brand. Why? Well, simple, people may not want to get marketing materials and messages from a brand that they don’t actually use.

Think about it. If you are comparing two different products for purchase, you’re going to be reluctant to give up your personal information just to get some info that’s easily available. Nobody wants to be bombarded with marketing materials for a product they don’t end up purchasing. (Even marketers!)

This is a pain point for many marketers. They want to measure this Engagement as an Action. They think that because a user is engaged that this is a clear indicator that they are taking “action.” Not true.

If you become a customer of Brand A, you may opt-in for additional information from that brand. But you probably won’t want ongoing newsletters and promotions from Brand B and C, especially if this is an expensive purchase that you don’t make regularly (cars, furniture, appliances).

Think of Action as an indicator of intent to convert or actually converting. That will differentiate between using your content and starting to become your customer.

Adding Flexibility

Over the years, I’ve presented this component content analytics model many times. I’ve noted carefully that this is a content marketing model for brands, not for every possible scenario of measurement. Analytics must be tailored to whatever it is you’re trying to accomplish.

Expanded Action Stage for Content Marketing Analytics

Expanded Content Marketing Analytics Framework

The graphic above expands this component content analytics model to include Action taken by Considerers. This broadens the measurement model to include users taking an Action in the Considerer stage.

For example, a user researching your brand may contact you on a website form that requires a unique ID, like email. They are looking for more information, but they may still go with a competitor brand. This is why I’ve added measurement points 3.3 & 3.4. You don’t have to use them, but they are there for a more flexible measurement model.

There are still no KPIs for Seekers. Nobody gives up their personal information in the Seeker stage.

As noted earlier, this analytics model and additional flexibility are intended for websites that feature content created for marketing purposes. It may not scale to work for every conceivable interactive digital scenario.

Final Thoughts and an Action Plan

If you made it this far, thank you. I hope you enjoyed this three-part series and find it useful in your content marketing. Again, this is Part 1 and this is Part 2.

The idea here was to capture the content marketing analytics model that I have been discussing for the past few years at conferences. If you’ve seen me make a presentation, you could come back to this series and review the details at your own pace. As many of you know, I tend to talk pretty fast.

If you use this model or even some variation of it, please let me know at I’m always looking to improve my own analytics model. I welcome your feedback.

Remember, this isn’t just an abstract concept to me. This is what I do at my day job, so I am in the trenches with you trying to figuring this out. Like you, I’m adjusting my techniques as new technologies change the landscape. 

The expansion of the Action metrics into the Considerer section came from direct feedback and discussion at conferences and in follow-up conversations with people just like you. It made more sense to expand the model than to be rigid with the measurements. Thank you to all of you who challenged my ideas and offered constructive feedback.

It’s important to note that this measurement feedback is part of a larger idea around content optimization, planning, and governance. In 2015, I did a series of presentations with Michelle Killebrew regarding the length of content.

At some point in the future, I’ll create another post to detail the connection between user journey and length of content.

Again, thanks for the feedback. I hope you have enjoyed this series on component content analytics.

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2 thoughts on “KPIs & User Journey Metrics for Marketers: Part 3

  1. Awesome wrap up. Nice job with the visuals as a clean, uncluttered way of positioning the escalating value of user engagement alongside your model. Always helps to have an ‘image’ of your measurment strategy. I really like the idea of placing a $ value on each step. That’s not always easy but definitely takes the model to an even more valuable level – ramping up the ROI factor.

    One other note – I really appreciate your suggestion that this is a pliable, evolving model. I’m sure this looked very different 10 years ago and 10 years from now will morph into something even smarter, as tools, and hopefully the people using them, advance. Thanks for helping to move things forward.

  2. Tony,
    Thanks for taking the time to read all of these. I think we have to be flexible with our interpretation of these guidelines. We’re seeing new channels and better tools all the time.

    The kind of information that we can collect in Google Analytics using the Google Tag Manager is just amazing. It’s only going to get better.

    More to come.

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