The DataHero Blog

Measuring The Effectiveness of Your Content Marketing

December 3rd, 2013

KelliPost_MEasuringEffectContent

Update (2014/12/16) – Although you can still use the following method to automate your Google Analytics reporting, you can now do this directly by using the direct connection to Google Analytics in DataHero!

Content marketing’s effectiveness can be measured in many different ways. Google Analytics is perfect for looking at how many conversions a promotion channel or specific blog post drives. What is lacking is information on how users engage with the content. Did they find certain types of posts more useful than others? Are they more likely to share a certain kind of post? Content marketing questions center around different objectives. Does your company focus on the revenue connected to your content marketing, free sign ups, or perhaps just site visits? We can all agree though that at its core, content marketing fosters relationships between companies and customers.

Avinash Kaushik’s suggestions for measuring social media’s effectiveness can also be applied to content marketing, and we can roll some of his metrics together with a few more promotion channels to get a better picture of our content marketing’s effectiveness. In this post I’ll show you how to pull your content engagement data together, then analyze it in DataHero to answer some questions about audience engagement with your content.

Step 1: Aggregate the data

Twitter

Where to go: Analytics page > Analytics dropdown > Timeline Activity

Interactions: clicks, favorites, retweets, replies and picture views

Facebook

Where to go: View Insights > Posts

Interactions: likes, shares, comments

LinkedIn

Where to go: Company page > Analytics

Interactions: likes, shares, comments, clicks

MailChimp

Where to go: Reports > Links

Interactions: Click throughs to blog

Step 2: Pull together a spreadsheet

Manually collecting data like this from sites that promote your content is an easy and cheap way to analyze your content engagement. Also, unlike a paid aggregation tool, you can gather the data from any tool you use in your content marketing strategy. This method can also be applied to Quora, Reddit or Inbound.org using upvotes or comments as interactions. Add as many outlets as you use in your content marketing strategy. Add the data you want to analyze to an Excel sheet or even a cloud service like Dropbox to share with your team.

In this post I looked at strictly Twitter, Facebook, LinkedIn, comments on the blog itself, and clicks in our MailChimp campaigns for the sake of simplicity. Once I got all this data into a spreadsheet (the old-fashioned way, simply plugging in the numbers) I threw that spreadsheet into DataHero.

Step 3: Analyze in DataHero

The goal is to optimize your promotion channels. I have five different subject categories that my posts fall into at DataHero. All the subject categories in the blog have different goals and perform better in different outlets, so I wanted to know which categories performed best in which channels. What I found interesting in the graph below is that the Category 2 posts performed the best out of all the other categories in terms of engagement. You can also clearly see that Category 4 performs well on Facebook and Category 6 performs well in MailChimp email campaigns.

DataHero Engagement by Promotion Channel and Subject Category (4)

MailChimp  has quite high engagement as well, which makes sense because I am sending content to users who have already indicated their interest in DataHero by signing up for the email list.

DataHero Engagement by Date and Promotion Channel (1)

Break your content down by individual channel to see what your customers value there. For example, Twitter users share and comment predominantly on Category 2 posts:

 DataHero Twitter Interactions by Category (3)

Facebook users engage with Category 4 more:

DataHero Facebook Interactions by Category (1)

Don’t be surprised if one type of content soars in one channel and crashes and burns in another. The graph below shows a rather weak correlation between Facebook and Twitter interactions. Feeling fuzzy on what makes a strong or weak correlation? Check out this post. The scatter plot suggests that testing each channel individually is important, not assuming that using the same method for each will be effective.

 DataHero Facebook and Twitter Interactions

These three graphs answer some basic questions about content marketing’s effectiveness, especially in terms of channel optimization. You can also test posting times, conversions, and authors if you want to dive into your content marketing strategy even more. There are no shortage of questions about content marketing’s reach but this is what I did to get started. As I said before, also consider your goals in content marketing. If the main goal is to simply drive traffic, producing viral content that has little connection to your business model is acceptable. If you’re looking for revenue though, you’ll have to augment the engagement data with Google Analytics data on conversions. Of course, some types of posts require less time or effort as well. Factor this into content marketing planning and analysis.

Step 4: Rinse and repeat

After you analyze what types of content marketing resonate with your audience, adjust your content strategy accordingly and do it all over again. You may also want to consider new metrics or data you’d like to collect. Analyzing the shareability and engagement in your content is an ever-changing area in marketing, so your analysis should be as well.

Your turn: how do you evaluate the effectiveness of your content marketing? What data do you analyze? Leave a comment below to join in the discussion.

By Kelli Simpson

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