Every second of every day, a new post is posted to social media platforms. With millions of people vying for people’s attention, it can be a crowded space for companies, businesses, governments, and anyone with anything to say. Analytics can help improve the efficacy of social media posts.
I recently have been curious about the decision for local newspapers to promote stories and articles on social media. While many newspapers are shuttering and merging into other newspapers, the demand for content on social channels has skyrocketed. However, many papers are underserving their audiences by inefficiently posting content.
The Standard Times
In New Bedford, Massachusetts, the Standard-Times, known today as Southcoast Today, is the city’s paper of record. The newspaper originated in 1850, and today the paper is enduring an extreme decline. Readership is now at an all-time low, and the paper was the victim of mass media merging, as mega-conglomerate Gannett Media purchased the paper. A skeleton crew now keeps the paper afloat, and local coverage has dwindled.
Yet, despite the odds, the paper is trying to remain relevant, posting articles and information on social media. One look at the public metrics included with posts, and you can assume the social media strategy is not effective at engaging viewers.
Each morning the paper releases the stories produced the prior day. At 5:30 am every morning, The Standard-Times posts social media stories to Twitter and Facebook platforms. Posts are shared exactly at 5:30 am on Twitter, and new stories are shared every 15 minutes. As a force multiplier, the other local papers owned by Gannett media share the same story on their social media platforms, usually posted at around the same time.
My question is, is this strategy effective?
A Case Study: Social Media Analysis
On Tuesday, August 31, 2021, the Standard-Times posted an article on Twitter at exactly 5:45 am. The post contains zero hashtags, does not include an engaging title, and has low user engagement. Only one person retweeted the article, the paper’s executive editor, and contains one Twitter-like.
On Facebook, the paper posted the same article at 4:34 am. 43 people interacted with the post by leaving a like emoji, two left heartfelt comments, three bickered against each other, and five shared the article. While this seems like an improvement from the Twitter post, 35,000 people follow the Standard Times on Facebook, and only a tiny fraction, less than .14% of the paper’s audience, engaged with the post.
I can only make these assumptions based on the public or, as some call them, vanity metrics included in the posts. I am not privy to the hidden engagement data Facebook collects and offers to users. I can only assume there has to be a better way.
For example, who reads news articles at 4:30 am? Who is on Twitter at 5:30 am? Let’s say someone wakes up at 9:00 am. Will they go back 5 hours to see everything they missed? It’s possible, but I doubt the strategy is effective. It might be more effective for the Standard-Times to dive deep into their social media analytics, and use the data to make better informed decisions.
Social Media Analytics
If it sounds like I’m speaking a different language, let me explain what Social Media Analytics is. In a nutshell, social media companies track an abundance of data on how users engage and interact with posts. People can then look at these data sets and make better decisions on reaching their audience better.
Facebook, Instagram, and Twitter all have free tools available for people to use. While some platforms require a business account to access these resources, the data can be invaluable for brands and companies. Analytics can provide a user with information such as: how many people saw the post, how many interacted with the post, and even how many people clicked the post. Social Media data also shows how long people interacted with posts, how large a reach the post received, and even the geographic location of people’s interactions.
The Need for Big Data
Social Media Analytics offers users a big competitive edge. The data offers companies direct insight into their audience’s behavior and demonstrates areas and patterns to engage a brand’s audience best. Using these tools can change the way brands communicate and allow brands and companies to make stronger decisions that leverage business decisions with social media posts.
For example, an ice cream shop posts a photo on Instagram promoting a new flavor of ice cream. The shop owners post the photos at 7:00 am and only garners about 4 likes in 3 hours. To improve this post’s engagement, the shop could turn to Instagram’s built-in analytic system. Using this data, they can see when their audience is the most engaged and post content when most people are accessing Instagram. This small decision can improve a post’s engagement.
Types of Analytics
Gohar Khan, the author of Creating Value with Social Media Analytics, proposes four purposes for analytics that can lead businesses and brands to be more successful with social media posts.
Descriptive Analytics
Social media platforms offer descriptive insight that presents users with information on how many people the content impressed, liked, shared, retweeted, and more. This type of data presents the findings of a specific post’s performance.
Diagnostic Analytics
Businesses and brands can use analytic data to focus on the progress of campaigns and targetted media. Users can then study analytic data to see what went wrong in the communication strategy and develop new ways to improve a post’s engagement. This data can also be helpful to identify what people were searching for in the first place and why they left or didn’t engage with the post.
Predictive Analytics
Compa can use social media data to predict upcoming events and offer key insights into users’ behaviors. For example, Google used predictive analytics to pinpoint outbreaks of the Flu in real-time.
Prescriptive Analytics
Companies can use analytic data to prescribe or optimize and personalize a user’s preferences. Companies like Netflix and Spotify have mastered this practice, analyzing large amounts of data to offer and suggest content similar to a user’s likes and dislikes. The social media platform Tik Tok heavily analyzes users’ experience, infinitely offering more content to users based on their decisions in the application.
Analytics are Here to Stay
While you might be alarmed to learn that social media companies and websites are tracking every decision you make on their platforms, analytic data is here to stay. The social media analytic industry is a 3.5 billion dollar industry, and experts have developed thousands of strategies to engage people better.
The next time you see a social media post, ask yourself this: “Why do I see this?” More often, the answer lies in someone analyzing you and a million other’s social media behavior and using the collected data to reach you better.
