How To
9 min read

A Guide to Content Analysis With Key Metrics to Track

Soniya Khubchandani

June 10, 2022

Are you sure your content is taking your business where you want?

Thirty percent of content marketers believe that proving the ROI of the content they ship is a significant challenge.

With so much data being generated around content creation and consumption, why are marketers unable to prove the effectiveness of their content marketing programs?

The problem is with their content analysis methods.

Are you in the same boat? 

Let us help you navigate in the right direction with confidence.

This guide will provide a comprehensive overview of content marketing analytics or content analysis.

You will learn how to measure your content marketing success and take the business to the heights you envisioned with the power of content.

Let’s get started.

What is content analysis, and how does it lead to a successful content marketing program?

Content analysis is the practice of analyzing the metrics related to the reach, engagement, and conversion data of a piece of content to understand its performance and take informed actions.

Here are a few critical ways a solid content analytics practice shapes your organization's content marketing program.

Keeps key stakeholders in confidence

If you are a content marketing manager, one of your key responsibilities is to communicate your team's progress to the marketing manager/ C-Suite clearly and transparently.

An intelligent way to accomplish this is to create timely content marketing performance dashboards. Knowing the content analysis process makes such reports possible.

For example, if your CMO wants to know the ROI from a whitepaper you spent a hefty amount to create, you can showcase "number of whitepaper downloads" as a key metric in your dashboard.

Maximizes chances of meeting content marketing goals

"What gets measured gets managed." This quote from Peter Drucker, the renowned management expert, holds true for your content as well. You should have a goal for every piece of content you create. For example, getting a minimum number of social shares.

Monitor the performance of a content piece against its goals to get a clear picture of where it stands. From that knowledge, you can either make changes to that content (if possible) or apply it to similar content in the future.

The individual content goals ultimately culminate in the overall content marketing program's goals. Content analysis offers a bottom-up approach to meet your overall goals faster.

Improves resource allocation across channels

How do you allocate budget and team to different content channels? Do you have any logical way to distribute resources? If not, performing a content analysis will provide you with actionable insights into each channel's performance. You can use this valuable information to double down on top-performing channels and reduce focus on money-wasting ones.

For example, you may start with an equal budget for SEO and social. After a few months of experiments and data collection, when you perform your analysis, you realize ‌SEO outperforms social in terms of unique visitors. You act on this insight and reallocate the budget to 60-40 between SEO and social channels.

Optimizes content workflows

A content workflow is the series of tasks your team performs to create a content piece. Content analysis can also cover such operational activities in its scope.

This allows you to magnify a critical content development process, find inefficiencies, and remove them with optimal solutions.

For example, you may find that a typical "how-to" blog takes two weeks from idea to publishing. You realize that this speed will not allow you to meet your quarterly content marketing goals. You decide to analyze the process in more detail, and find out the review process is taking the most amount of time.

Finally, you ask your team to create more detailed content outlines to reduce gaps in the first draft from the writer's end. This action leads to a two-day reduction in the overall blog publishing time.

Makes content strategy changes data-based

Your content strategy is not set in stone. While documenting your content strategy is essential, timely revisions are equally vital.

But how do you make revisions to your content strategy?

This is another place a robust content analysis practice will help you. 

For example, your content strategy document may mention that you should post five times a week on Twitter. You have been measuring the total impressions for some time and seeing them decline weekly. Then you decide to experiment with four posts a week and you see the cumulative impressions spike. 

Based on this data-driven observation, you make a change in the strategy document to post four times a week.

Understanding content marketing metrics: The foundation of good content analysis

Knowing what to track and not track to measure your content performance is fundamental to conducting content analysis. While you may be tempted to track everything, it is best to stick to a few good metrics that reflect and align with your content marketing goals.

To make it as simple as possible for you to get started, we have a simple yet comprehensive framework to assist you.

At a high level, all metrics are divided into two main categories: "Performance metrics" and "Operational metrics." From there, we break them down into sub-categories.

Performance metrics

Reach metric example from Google Analytics

Performance metrics answer questions related to "how does a piece of content do" once published. We further break it down into three main areas. Let’s deep dive into each.

Reach metrics

Reach metrics answer the primary question, "How many people have viewed this content piece?"

Let’s look at various reach metric examples by different content types.

Reach metric examples for a blog post:

  • Total number of page views
  • Unique page views
  • Number of visitors from organic search
  • Number of visitors from social media
  • Number of visitors by any channel
  • Number of views/user

Reach metric examples for a video:

  • Total number of video views
  • Number of video views per user
  • Unique video views
  • Number of video thumbnail impressions

Reach metric examples for a social media post:

  • Total number of post impressions
  • Unique post impressions

Reach metric examples for an email:

  • Number of emails opened
  • Email deliverability (Number of emails successfully sent/Total number of emails in your list)

Reach metric examples for gated content:

  • Total number of visits to the asset landing page
  • Unique visits to the asset landing page
  • Total number of asset downloads
  • The total number of form submissions to access the content

Engagement metrics

Engagement metrics tab in the analytics section of YouTube Studio

Engagement metrics answer the primary question, "How many people have interacted with your content piece?"

Let’s look at various engagement metric examples for different content types.

Engagement metric examples for a blog post:

  • Average session duration
  • Number of pages visited per session
  • Percentage read/scroll depth
  • Click-through rate to other pages
  • Number of comments in the blog's comments section
  • Bounce rate

Engagement metric examples for a video:

  • Average watch time
  • Total number of likes
  • Like/dislike ratio
  • Total number of comments
  • Number of shares

Engagement metric examples for a social media post:

  • Number of likes
  • Number of comments
  • Number of shares
  • Number of clicks on "Read more" (post-expansion)
  • Click-through rate to external links

Engagement metric examples for an email:

  • Number of link clicks
  • Click-through rate
  • Number of emails forwarded

Engagement metric examples for gated content:

  • Number of pages read from the PDF
  • Number of external link clicks from a document
  • Number of shares of asset landing page
  • Average time spent on the asset
  • Average time spent on the landing page of an asset

Conversion metrics

Conversions section in Google Analytics report

Conversion metrics answer the primary question, "How many people took a desired action (converted) after consuming the content?"

Let’s look at various conversion metric examples by different content types.

Conversion metric examples for a blog post:

  • Number of email subscribers gained after reading the blog
  • Number of social shares 
  • Number of free trials initiated after reading 
  • Number of inquiry forms submitted after reading 

Conversion metric examples for a video:

  • Subscribers gained after watching the video
  • Number of products sold after watching 
  • Number of inquiry forms submitted after watching 

Conversion metric examples for a social media post:

  • Number of new followers gained
  • Number of direct messages initiated
  • Number of products sold
  • Number of inquiry forms submitted

Conversion metric examples for an email:

  • Number of products sold after clicking through the email
  • Number of inquiry forms submitted by clicking through the email
  • Number of new subscribers gained from email forwards

Conversion metric examples for gated content:

  • Number of inquiries after consuming the resource
  • Number of free trials started after consuming the resource
  • Number of new emails received from resource downloads

Please note: Some metrics can be grouped under a different category/multiple categories depending on how you define reach, engagement, and conversion for content. For example, if you consider external link clicks from a social media post as a conversion, it can also come under conversion metrics.

Operational metrics

Operational metrics answer questions about "what does it take to produce a content piece?" We further break it down into two main areas, “production metrics” and “cost metrics.” Let’s drill down into each.

Production metrics

Production metrics answer the primary question, "How the content is produced?"

Here are some examples of production metrics:

  • Time taken from content idea to live URL
  • Number of content pieces produced per week
  • Number of content pieces updated/optimized per week

Cost metrics

Cost metrics answer the primary question, "How much does it cost to produce a piece of content?"

Here are some examples of cost metrics:

  • Average cost to produce a content item
  • Average cost to promote a content item
  • Number of people involved in creating a content item

Attribution models and content marketing: The science of assigning credit to content

Attribution models describe the possible mechanisms to attribute (credit) a content piece for a conversion. 

With customer journeys spanning multiple marketing touchpoints, attribution modeling is becoming more important than ever to get an accurate picture of marketing ROI.

For example, if you use the last-click attribution model, the last content that the user interacted with before making the purchase will get all the credit. 

Suppose the user learned about your company for the first time from an educational blog post. In that case, its contribution will not be counted if the person finally converted from a social media post.

This is why it is essential to know about all the major attribution models when doing your content analysis.

Attribution model comparison tool in Google Analytics

Let’s check them out with the help of a conversion journey scenario.

Scenario:

A customer finds your website by reading a blog after a Google search. She returns three days later by landing on your sales page via a social media post. On the same day, she comes back for the third time from your marketing email, and then a few hours later, she returns by entering your website URL in the browser and completes the purchase.

First interaction model

The blog post will receive 100% credit for the purchase if you use this model.

Last interaction model

If you use this model, the direct channel will receive 100% credit.

Last non-direct click

This model ignores all non-direct traffic, and the last click before that is assigned 100% credit, i.e., the email campaign.

Linear model

In this model, the credit is distributed equally among all touchpoints, .so in this scenario, the blog, social media post, email, and direct channel will all get 25% credit for the purchase.

Time decay model

In the time decay model, the maximum credit is given to the closest touchpoint to the sale, and then the credit value decays with time. In this case, the direct channel will get maximum credit, and the blog post will get minimum credit.

Position-based model

This model will assign 40-40% credit to the first and last touchpoints, i.e., blog post (40%) and direct (40%). The remaining 20% will be distributed equally among the touchpoints in between - social posts (10%) and email (10%).

Best practices to make your content analysis initiative a success

Reaping the benefits of content analysis requires it to be thoroughly implemented and adopted by your organization. Here are a few valuable tips to streamline the process.

Encourage a data-driven marketing culture

Any key initiative can succeed in an organization if the culture aligns with the change. The same applies to content marketing analytics as well.

This initiative must be embraced by key stakeholders, like the CMO and the CEO, as this will allow you and your team to get the support needed to carry out the work.

Start with a pilot program

Getting an idea validated quickly can help scale it faster as it increases confidence among stakeholders. For an initial pilot program, you should pick an area of your content marketing program where data-based analytics can improve performance quickly.

For example, start with a simple content marketing metric like "Total number of unique visitors to a blog." Focus on three blogs that are already receiving traffic but can get more. Optimize these blogs and track results.

Gradually, take up more metrics in your content marketing reporting.

Set up actionable reporting

Most of the communication with others will happen through your content analysis reports. It’s helpful to create easy-to-understand and visually appealing reports to get everyone's attention. A free tool like Google Data Studio is excellent for creating content performance reporting dashboards.

Create the right team

Content analysis will require a specific set of skills to do it well. You need to create a team with the necessary skills and take ownership of the different tasks involved.

You can start by reassigning one of your team members to focus on this crucial area and then support them with training and guidance.

[Suggested interlink] Related: What is a content marketing agency?

Use a suitable technology stack

Content analysis requires collecting relevant data and turning them into insights. There are many free and paid marketing analytics tools available to make your job easier.

Be clear about what you want to achieve

Setting the right expectation is important for any new project. You should define your purpose for doing the content analysis clearly.

For example, you can communicate that the analysis will help figure out the top-performing content channel so your team can devote more time to it.

Closing thoughts

Knowing where content is taking your business is a powerful piece of information to have as a marketer, and that information comes from quality content analysis.

No content is created in a vacuum. Every piece of content has a goal to fulfill.

Content analysis brings this thought process to the forefront. If you want to take your content marketing program to the next level, it is time to focus on measuring its effectiveness.

We hope this guide has provided you with the knowledge you were seeking to take this data-driven path to success.

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