Content Analytics for Dummies: The Metrics That Matter

Content Analytics for Dummies: The Metrics That Matter image content analytics buildings like a graph

Many content marketing strategists who generally know how to create great content and tell stories, but don’t really self-describe as “numbers people.” Only 27% of B2B marketers say they are effectively tracking content utilization metrics.

We know you’re not a statistician, but don’t let analytics become the monster under your bed.

This post will cover the necessary analytics to track. You can get a more in-depth version by downloading the Content Marketing Analytics presentation, a deck walking you through everything you need to know to measure the right numbers.

The 4 Key Areas of Content Analytics

If you follow these four analytics categories in your reporting, you’ll not only demystify the impact of content marketing, but you’ll have your boss swooning over the data.

Related Resource from B2CWebcast: PR Hacking: How Ideas Spread And What Marketers Need to Know

1. Production

Content Analytics for Dummies: The Metrics That Matter image screen shot 2014 03 11 at 11.21.59 am

What? Production refers to the total amount of “stuff” being created. Only 32% of marketers say they effectively execute enough content. But by setting production goals and literally counting your content production stats, you can change that. Depending on what makes sense for your business, the areas to include could be:

  • Content by Type (number of eBooks, webinars, or blog posts created)
  • Author Output (number of content pieces each author produces)
  • Content by Category (number of content pieces related to certain categories in your business)
  • Content by Persona (number of content pieces targeting each of your buyer personas)

Why? Production metrics are important because they track the yield of your content team. Content strategists use these metrics to define goals like how many blog posts should be created in one month to meet goals (like lead generation), or which author is producing the most material. Marketers can also benchmark the data to compare the volume of content creation month-over-month, year-over-year, etc. When well-executed, production analytics ensure an optimal level of output throughout the year.

Engagement

Content Analytics for Dummies: The Metrics That Matter image screen shot 2014 03 11 at 11.22.19 am

What? Engagement measures the amount of social or digital activity a piece of content evokes. It answers the questions, how involved were users with this content? Did this content spur a reaction? Typically social sharing suggests users like your content and brand, and also spark purchase intent. 67% of Twitter users are more likely to buy from brands they follow. Types of engagement metrics include:

  • Total Social Shares (Facebook, Twitter, Pinterest, LinkedIn shares combined)
  • Page Views (how many times was this content viewed?)
  • Comments (how many comments did people leave on your post?)
  • Links (how many link backs did you get?)

Why? Engagement metrics are a good barometer for how valuable your audience feels your content is. Users will share and spread your original content if they feel like it’s worth it. A high number of engagement shows a content piece was successfully elicited a response either by being entertaining, relevant, or emotional to users. However, engagement metrics should be tracked with a grain of salt. A piece of content that renders high engagement, does not guarantee it’s rendering new business.

Performance

Content Analytics for Dummies: The Metrics That Matter image screen shot 2014 03 11 at 11.22.29 am

What? Performance refers to the effectiveness of a piece in a broad sense. Performance metrics often combine engagement and production metrics to take a higher-level look into your content. Think about tracking:

  • Top 10 Post (in a given time)
  • Top Categories (which categories have the most content associated with them)
  • Top Authors (which author’s work is getting the most engagement)

Why? Performance metrics are a great top-level view of all your content analytics. A quick, top-10 or top-5 list provides an at-a-glance metric for your higher-up to check out.

Content Scoring

Content Analytics for Dummies: The Metrics That Matter image screen shot 2014 03 11 at 11.22.39 am

What? Content Scoring is an aggregate number that uses attribution modeling to see how effective a singular piece of content is at converting leads to sales and ROI. In short, it shows how much money each piece of content bring in for your company. It’s a fairly complicated analytic modeling effort that you can learn about here, but is the most important analytic to prove the value of content. You can sort content scores by:

  • Author
  • Category
  • Content Type vs. Campaign Type
  • Coversions
  • Revenue Generated

Why? The ultimate result of content marketing is revenue. Content Scoring is the first tool that automatically calculates ROI rendered by content published. It effectively shows which individual pieces of content are ushering buyers down the sales funnel.

Putting It All Together

Choose the metrics that matter to you. Identify which analytics are most important to your company or firm and put those into your monthly reporting. Develop a system of tracking that works best for your business. The point is to hold your content marketing team accountable to driving business objectives and tracking the numbers over a long period of time.

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