How To Analyze Your Blog Data In 5 Steps

Blogging is one of the most popular tactics of content marketing, used by 79% of B2B companies. In fact, best-in-class marketers rate blogging as the most effective tactic —even above in-person events.

How to Analyze Your Blog Data in 5 Steps by @chrisboulas

But simply throwing up a blog on your company’s website isn’t enough. To maximize your investment in this channel, you need to analyze the impact of certain blogging tactics and use that information to inform your strategy.

Earlier this week, I shared key findings discovered from an internal analysis of our blog, the Content Marketeer:

• Publishing 2 posts per day drives 63% more traffic to our blog than publishing 1 post per day


• However, when 2 posts are published on the same day, individual posts receive on average 24% less traffic


• Posts published at 6am drive 30% more traffic than 8am posts, and 70% more traffic than 10am posts


• On Tuesdays and Wednesdays, we receive the most traffic

Read the full post to find out how we used this information to better optimize our efforts.

Today, I’m going to share how you can analyze your blog in the same way. For our internal reporting, we use a combination of Kapost Analytics and WordPress to gather data.

But, in case you haven’t yet made the investment in content marketing software (if you’re thinking about it, here are 5 signs you might be ready), I’ll explain the analysis process in 5 easy steps that any WordPress user can follow.

5 Steps to Analyzing Your WordPress Blog

For WordPress users, if you’re interested in seeing how your blog compares to our results, I’ve included a 5-step how-to guide below.

Step 1

First, you’re going to need the assistance of your web developer. You’ll need to work with him or her to obtain a time-stamped list of blog posts by publish date in a .CSV file. The files can be opened by any spreadsheet software. Make sure your file has the following columns:

• Post Date


• Post Time


• Post Title


• Post Name (This is also referred to as the URL slug)

Step 2

The next step is to find out how many unique visitors were acquired for each post on the date it was published. Within your web analytics platform, use the “Post Name” column in your report to search for each page, remembering to adjust your date range to include only the date the post was published. If you aren’t comfortable with this step, work with a colleague who manages your web analytics instance. Common examples include Google Analytics, Omniture, Webtrends, etc.

Step 3

Add one more column to your spreadsheet called “# Posts on Post Date” In this new column, write the number of posts that have been published on the corresponding date. To make this quick and easy, create a pivot table with the date as your row labels, and add a count of “Post Title” as your metric.

Step 4

Save a new version of your file, instead choosing .XLSX as your file extension instead of .CSV if you use Excel. This step is imperative because we’ll be building some pivot tables next, which will not save if the file remains as a .CSV.

Step 5

Finally, build charts to help visualize your findings using pivot tables. I won’t go into detail on pivot tables here, but if you get this far and have questions, refer to this easy-to-understand tutorial on pivot tables.

Final Thoughts

I hope this helps you generate more traffic from your blog content. The results I’ve shared are a great starting point, but before applying our results to your site, use the guide above to analyze your own historical data to further help you make the right decision for your business.

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