A Data-Informed Future

Introduction

In our very first blog post (if you can remember such a distant thing), we mentioned the different kinds of data analytics. The four types of data analytics were: descriptive, diagnostic, predictive, and prescriptive analytics. Each of these different categories has plenty of theory and information surrounding them.

However, here at DodoData, we believe that one of the strongest uses of data analytics, especially in the journalistic/social media industry, is the prediction of future trends. We covered the broad strokes in that blog post, but today we want to dive deeper into predictive analytics and how we can use it in journalistic social media. 

Predictive Analytics 101

At its most fundamental level, predictive analytics is the strategy we create after observing past data. What has happened before should influence what we do next. In predictive analytics, we see the data from the past and draw up an imaginary future for ourselves: allowing us to make decisions for future events. There are multiple different ways to do this, most of them using different algorithmic tools (1).

We aren't mathematicians but we do have a strategy to help.

Predictive Journalism

As it turns out, someone has already combined predictive analytics and journalism together into an intellectually chimeric juggernaut of astounding proportion. I am talking about predictive journalism, of course, something that many veteran journalists are familiar with. A predictive journalist makes sense of the data that they already have and forms a theory around it. If x and y have already happened, then we can assume that z will happen as well.

This is pretty commonplace in the world of journalism: from predicting the windfalls of the stock market to the winner of the presidential election, predictive journalism is commonplace (2). 

A Scary (and Online) World Out There

Many journalists approach their social media data the same way they approach their journalistic data. This we would first like to applaud. Many journalists online don’t consider their social media stats worth investing or investigating so we want to approve those journalists who care enough to step into social media more. However, it is no secret that social media is a total maelstrom of differing trends which can make predictive analytics difficult to tackle in the online sphere.

In our research, we have found you three best social media practices that can help you predict which direction you are headed in the digital seas.

1. Find Your Metric

Predictive analytics needs to have data to analyze. However, in the social media world, you are given hundreds of different data sets across platforms and accounts: too many! As a brand, you should create a small list of data sets that you will turn to to detect high performance. These data sets are traditionally called your KPIs or Key Performance Indicators.

Although that term can sound terminologically dense, it just means you picking out which statistics you value and which you look to for progress. Some common KPIs for social media accounts are things such as view count, clicks in 48 hours, likes, comments, or share percentage (3).

Once you have chosen a KPI or two, then watch them to gauge what is succeeding and what is not. 

2. Find Your Reason

After you have been on social media for a long second, you will notice that some of your posts are more popular than others. Even if you are not making new records with your posts, often there is a trend toward one kind of post over another. The temptation that many uninformed social media users make is to create more posts like the previous ones to keep that trend moving.

This will have mixed results: instead, find the reason why people are clicking on those posts rather than your other ones. If your popular posts cover a particular topic more than your other ones, you may have found a niche community that enjoys your coverage of that topic (4). 

This idea transcends just post topics, but post formats and social media platforms as well. If your YouTube shorts are getting more interactions than your Instagram or LinkedIn then perhaps you should lean more into the YouTube shorts side of things. What people currently enjoy is a good predictor of what they will enjoy. 

3. Find Your Next Step

Now that you have identified your KPIs and your social media’s reason, you can now take the next step. With this new information you have obtained you can now take a newly informed action to progress your social media. We suggest instead of repeating this process over and over again for each post or action that you make on social media, try establishing goals instead.

Follow the SMART system of creating an obtainable goal (5). Your goal should be specific, measurable, achievable, relevant, and time-bound.

For example, you may have noticed a trend of your more comedic social media posts getting more traction than your other posts. Instead of creating the goal, ‘make more funny social media posts’ consider how you can specifically make these posts, how you can measure a positive response, if comedy is appropriate to your subject matter, and the time frame in which you will be running this small experiment. 

Conclusion

Now the future doesn’t seem as scary, does it? The one thing we have been trying to reinforce and that we will continue to shout about is that data analytics can be daunting on paper, but is easy when you divide it up.

The same applies to predictive analytics. Often we can get lost in all the numbers or statistics wondering about what means what and if we should act on the latest ‘thing.’ By following these three simple steps you can catch a break and take a deep breath as you ease yourself into the journalistic social media world. 

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Sources

(1) - Harvard Business School, https://online.hbs.edu/blog/post/predictive-analytics, accessed 4/8/2024. 

(2) - Columbia Journalism Review, https://www.cjr.org/tow_center_reports/predictive-journalism-on-the-role-of-computational-prospection-in-news-media.php, accessed 4/8/2024.

(3) - Kubbco, https://www.kubbco.com/blog/social-media-analytics-how-to-make-data-driven-decisions-for-your-brand, accessed 4/8/2024.

(4) - Kubbco, https://www.kubbco.com/blog/harness-the-power-of-ai-a-comprehensive-guide-to-predictive-analytics-in-social-media, accessed 4/8/2024.

(5) - SproutSocial, https://sproutsocial.com/insights/social-media-goals/, accessed 4/8/2024.