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  • Marc in Madison

Digital Metrics: Twitter and the Wisconsin State Journal

Updated: Mar 31, 2021

This was written for CAS 839: Media Analytics Communication in the Michigan State University Strategic Communications MA program.


As a digital media news user, I am only active on Twitter.

I deleted my Facebook account many years ago. I have created and deleted Instagram accounts many times also. But I get all of my news from Twitter. I enjoy the ability to constantly refresh and read hot takes on news from organizations other than the standard news outlets.

I find that often there are analysts, researchers, and former politicians and government employees who have unique perspectives.

So if anyone approached me about my news habits, they would focus on Twitter metrics. I would suggest the following questions because they create a geographic, demographic, psychographics profile by which they could segment me as a user:

  • Geography

  • Age

  • Gender

  • Income

  • Average session time

  • How often do you use this app?

  • What do you read first: timeline or trends?

  • What is your pinned tweet?

  • Do you tweet in Gifs?

  • Does Twitter make you feel pessimistic or optimistic?

  • Do you get your breaking news from Twitter?

  • If so, do you follow up with a traditional news source?

  • I believe social media is a positive way to receive news. (Y/N)

  • I think social media makes people depressed. (Y/N)

In an inquiry into a user's personal big data, these metrics would prove useful:

  • Top tweet

  • Tweet performance

  • Engagement rate

  • Types of engagement

  • Frequently used hashtags

  • Follower/unfollower growth

  • Impressions

  • Hashtag performance

These metrics would help Twitter management gauge the reach of my posts and assess the value of my content. If I maintained a fast-growing Twitter account, then I might be a candidate for verification, for example. Also, Twitter metrics are used in marketing—through third-party companies like BuzzSumo—to identify influencer marketing choices.

Engagement would speak to the amount of two-way conversations on my beed. Link clicks would assess the efficacy of follow-through on links I post and endorse. In a qualitative sense, management could assess my Tweets for tone and sentiment. In the constant battle of the bots and of deep fakes, the latter and the former are more important than ever.

The picture above is a screenshot from the front page of the Wisconsin State Journal (Monday, February 1 around 7:30 a.m.). The other pictures are of the landing page (with banner ad) and a secondary view with extensive page ads.

In reviewing ways to test the success of this page, I used these categories:

Bounce rate: How many visitors hit the site, then left the site. Although they may have achieved a take-away, these visitors left the site quickly. Management would be very interested in this metric. Story topic, layout/design, advertising (display, banner, pop up) layout, sidebar content, journalist(s) appearing on the page, photo play, day of the week, and time of the day are all factors to consider with bounce rate. Are people turned off by these ad-dominated pages?

Click-through rate: This metric explains how many visitors clicked a hyperlink on the page. University of Wisconsin is an evergreen topic in Wisconsin, and health news is crucial for everyone. Are people likely to click through the jump for the center article? Are people clicking those HyVee ads? Management would be interested to see how many people follow any of these stories. Criteria to consider include headline writing, story topic, the journalist(s), does the article have a photo, is the article local or national, and what is the total word count of the article. These metrics could form a benchmark for future comparison. Theoretically, a click could include an email directed towards the journalist from a hyperlinked byline.

Concurrent visits: How many total visitors are on the site at one time. This can inform about optimum publishing, ad placement, and promotion times. Also, marketing and advertising could use statistics from peak times to compel advertisers and prospective advertiser—empirical proof of traffic.

Conversion rate: The advertisement on the top of the page (which slides as you scroll down the page) is a good example of conversion rate metric consideration. How many people click the ad? Do they follow-through on subsequent pages (enrollments, subscriptions, registrations, etc). It is almost physically impossible to not click on the HyVee ads. Are these ads converting shoppers? Conversion rate applies to the newspaper itself, as well as any aspect that invites an action. Management, especially advertising and marketing, will want to know how successful campaigns perform. They can use successful metrics in sales presentations or even for recruitment (on the newspaper's careers section).

Engaged time: The more time one spends on the page, the more compelling they find the information. Management could infer this statement, and similar to bounce rate, analyze individual snapshots of pages with low, medium, and high engagement times to see what works and what needs improvement. Do sidebars and short introductions to stories limit engagement on the front page?

Entry/Exit rates: Management might like to know where visitors enter and leave the site. This can tell management where to "make a good impression" and where to focus content, advertising, and calls-to-action (or where not to include these items).

Reach: This metrics ties to social media, as it explains the total amount of unique visitors who have been exposed to content (and frequency explains how many times that user was reached). Similar to an impression on social media (which states content was viewed, but not necessarily clicked, in a timeline), reach can tell management how far content is circulating.

Engagement: This is a direct indicator of how many people not only see content, but scroll and click and interact with a page. They scroll and view content all the way to the bottom of the page. They click sidebar links or jump links. They may leave a comment on a story. These actions surpass the cursory visit. Lee, Lindsey, and Kim (2016) state that in the fusion between social media and journalism, there are robust opportunities for audiences to interact personally with journalists.

Loyalty describes the amount of return visitors—an indicator that a visitor not only enjoys content, they trust the organization enough to visit regularly to stay informed. Ideally, these visitors will share links on social media and act as brand ambassadors—increasing reach, engagement, and revenues.


Beaty, J. (2021, January 24). Journalism - Key measures of digital analytics. Retrieved from the Michigan State University D2L site.

Lee, S.K., Lindsey, N.J., & Kim, K.S. (2016, November 22). The effects of news consumption via social media and news information overload on perceptions of journalistic norms and practices. Computers in Human Behavior, 75(2017), 254-263.

#MediaAnalytics #SocialMedia #StratCom #DigitalMetrics #DigitalNewspapers

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