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Marketing analytics has changed tremendously over just the last few years, moving from so-called soft metrics like page views and shares to more sophisticated measures of user behavior and engagement. Increasingly, content marketers need to be able to approach their work the way other data-driven functions do. That means identifying the right metrics, understanding the data you’re collecting, and using content marketing analytics to answer business-critical questions and demonstrate ROI.

First Things First: Align Content Metrics with Business Goals

One thing that quickly becomes clear when you delve into content marketing is that there’s no shortage of metrics you can turn to: email open rates, click-throughs, impressions, form submissions, and so on. What’s less clear is which of these metrics most closely map on to your business goals.

Remember: Just because you can measure something doesn’t mean it’s relevant to your business goals.

How should you decide which metrics to focus on? The answer depends on both your content strategy and your business. For example, if your content program is designed to support your sales function, then a sales metric like leads generated or touched might be a better metric for evaluating white paper performance than downloads or social shares, though all three of these particular metrics may be hard to track for various reasons.

Here’s another example: If your content program consists of targeted emails designed to get users to come back to your site or app, then retention metrics like page depth or subscriber growth are likely to be more meaningful than open rates or click-throughs.

Tip: Mapping goals to business needs can drive better alignment and also help define content direction. For example, looking at the full funnel view of the customer from starting –touchpoints, interactions, etc.–to final conversion will identify gaps where content can help guide or persuade the prospect to purchase.

Understand the Data You’re Gathering

Data scientists will tell you that data is only useful if it’s reliable. This is true for any function, but content marketing analytics brings with it a number of specific challenges, including the indirect relationship of many metrics to the actions they serve as proxies for.

Take a typical content email, for example. Let’s say it features the text of a recent blog post, along with an infographic and a call to action. Because we can’t embed analytics tracking in emails, we have to rely on proxies for various kinds of engagement.

How do we tell how many people saw our infographic? We could go by open rates, though many email clients don’t load images by default, meaning that open rates may consistently overstate how many people are actually seeing our content.

Okay, but we can get a sense of how valuable people found the email based on how many people clicked through, right? Not so fast! Click-throughs might tell you how well a given CTA is performing, but a user can still get value from an email without clicking through, meaning that click-throughs may consistently understate how many users are reading your content.

This is just one example of the sorts of challenges content marketers face when trying to tie actions to data. Some other common challenges include gated content getting indexed in search and social media metrics like impressions that measure potential but not actual views.

Answer Questions and Demonstrate ROI with Analytics

After several years of consistent growth, marketing budgets got a haircut in 2017-2018. It’s critical that content marketers be able to demonstrate that their efforts are having an impact on the bottom line. If you’ve aligned your metrics with key business goals and made sure you’re collecting the right data, you’re most of the way there.

Building a successful content marketing analytics operation can be a major undertaking. Constructing flows and funnels can mean getting engineering resources to create tracking code for your pages, assets, and apps. With these in place, you can start to understand exactly how people are interacting with your content, and what they do later. Combining this behavioral data with demographic info like location, date of birth, etc., you can begin to put together some pretty sophisticated profiles of your users, leads, and customers.

With content marketing analytics in place, you can start asking (and answering) questions that align with those business goals we started out with. For example, if our goal is to help turn more leads into sales, we should be able to use a mix of engagement and sales data to answer questions like “How soon after a lead downloads a white paper should someone from sales reach out?” or “Does gating content actually lead to more conversions?”

There are many analytics platforms out there. Some are geared toward developers, but there a lot of options that emphasize value for marketing and sales. These tools, like Mixpanel, CrazyEgg, Localytics, Marketo, Amplitude, and Custora, place a greater emphasis on features like installation tracking, cohort analysis, measuring CLM, marketing automation, and mobile ad attribution.

Tip: Once you’ve got your measurement capabilities in place, you might find conversion is still elusive or not as robust as your strategy originally painted. This is a good time to step back (breathe!) and then look at what’s working to optimize, iterate, and improve. Because with content–and a good CMS–you’re never really done!

No matter what platform you go with, you’ll want to make sure you have someone with data engineering expertise to make sure your dashboard is set up and your trackers are all in place. And of course, don’t forget about the content marketers and writers who make it all possible.