Source: Midjourney

The flow of energies when choosing to write on Medium

In the past five years, I have published on Medium, and this year I am writing on Medium for the sixth time. Despite the fact that Medium is a powerful platform for writing, in terms of the analytical data it exposes, the platform is sorely inadequate. This leaves creators wondering if they are doing well when it comes to productivity gains or losses. Getting nowhere with my writing on Medium, I decided to pull all of my Medium data into a spreadsheet last year. With the spreadsheet, I was able to map out different metrics that showed me how much I was writing every month. These metrics showed me which months were my most productive, and which topics piqued the interest of my audience the most.

It is in today’s post that I will sum up all that I have learned and also demonstrate which Chrome plugins can be used.

The first layer of data

The stats that Medium offers

One of the first things you will notice when you visit Medium is the site’s monthly View, Read, and Fan stats. Although these stats are quite useful, they cannot be broken down into yearly, weekly, hourly, and daily views. This can be achieved using an add-on plugin called Better Medium Stats that is available on Chrome Webstore.

Snapshot of Views data in Better Medium Stats plugin

Going Deeper

One of the blog posts on my list

A list of all my blog posts can be found below these stats, along with additional statistics in the form of Views, Reads, Read Ratio, and Fans. I find these statistics extremely helpful, as they provide me with a better understanding of each post I write. I have been able to see which articles have worked in the past and which have not. The listing also includes the publication date, and the article’s length based on the total number of words denoted in minutes as a unit. As well as the length of the article.

When I click on the “Details” link within each blog post, I am able to see a whole new set of statistics as well. Beyond Views, I am able to see Earnings in US$, Average Reading Time, and the correlation between Views, Earnings, and Medium Member Reading Time. The majority of views I get from Medium are from external sources and Medium doesn’t pay for them, so I don’t get much from Medium for my blog posts. It’s only about 27% that comes from within Medium.

A side-by-side comparison of Views, Earnings, and Member’s reading time data

There are several external sources that link to my blogs, so it’s good to see that. The list of external sources and the reader’s interests are listed at the bottom of the page. Views by Traffic Sources aren’t all that useful, but seeing the reader’s interests is. It usually occurs that the most frequent sources of readers for my articles are from the following tags:

• Visual Design
• Design
• Technology
• Creativity

Views by Traffic Source & Reader’s Interests

Productivity

Tracking my productivity metrics was the first thing I did when mapping my Medium analytics. Put simply, it meant mapping Month names, Years, No. of blogs in each month, and the total number of blogs written each year.

• By mapping a bar chart between Months and the Number of Blogs, I was able to see how I was performing month-over-month and which months were my most productive in terms of blogging.
• In order for me to understand the frequency of my blog writing cadence, I made a pie chart illustrating the number of articles I have written each month, and this helped me to understand how to manage my writing time. It is interesting how in spite of a few months where I have written 15+ blogs, around 31% of the time, I have simply written one post per month.
• Finally, a bar graph of the number of blogs I have written over the course of the past year helped me to understand which of my previous years was most productive, as well as the way my writing frequency has increased over the past few years.

Publisher, Topics, & Read Time

• It is also important to note that the number of publishers is another important metric that Medium underestimates, but mapping this simple pie chart helped me understand the lack of diversity that I have on the publisher’s side of the equation. As a result, I was able to see which publishers have published most of my work and which ones were a minority.
• In the process of writing blogs online, we can categorize them into different topics. Despite the fact that the tags remain the same for each of my blogs, the topic of each blog changes vastly. By manually adding this value to each of my past blogs, I was able to figure out what topics I have written the most about in the past. There’s a possibility that I am more comfortable writing about specific topics like Design systems or Branding or perhaps it just means that I have a deeper understanding of the topic.
• Before moving on to the last part of the analysis, I thought it would be helpful to map out a relationship between Read/View and Read Time so I could understand the ideal length of a blog that would most likely be read by my readers. According to the data you see above, readers tend to pay more attention to blogs that are 5 minutes or less in length based on the Images + Word count.

Earnings

The last part that I plotted was the correlation between my earnings from Medium and other variables like Topics, Publishers, and Read Time.

• I began by looking at all the earnings data for all my blog topics and I was amazed to find that despite the fact that I have written the most blog posts on case studies topics, I find that my most lucrative earnings come from Design Systems and Branding topics.
• There are 2 publishers who have contributed to the most of my earnings so far — UX Planet and Prototypr, as well as a small percentage from UX Collective and Bootcamp, which is not unexpected since I published most of my content on Prototypr last year.
• As a final point, I found that Earnings plotted against Read Time helped me to see the obvious, that the blogs around the 5-minute mark work best for me in terms of earnings.

That’s the end of this short yet hopefully insightful read. Thanks for making it to the end. I hope you gained something from it.

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