Social Media Analytics Explained

The importance of social media analytics lies in facilitating informed decision-making, understanding customer perception, and gaining insights into competitor strategies. By utilising these tools, businesses can optimise their social media strategies, identify opportunities for improvement, and enhance brand perception across various platforms.

More than half of the global population is now using social media. This is a cause for alarm among competitive businesses because there is more data to uncover. Knowing how their efforts on social media platforms are paying off or finding more meaningful ways to reach the audience needs to be more data-driven than counting likes, comments, and shares. This is where tools for social media analytics come in. 

What is Social Media Analytics?

Social media analytics involves gathering unique data points of the audience across one or more platforms such as Instagram, TikTok, YouTube, and Twitter, and measuring their impact. These data points ultimately help improve the social media strategy that aligns perfectly with the overall marketing objectives and business goals. 

Social Media Analytics vs Native Analytics

Social media analytics tools are broader in scope in relation to native analytics solutions that platforms generally offer. The native ones provide important metrics on engagement and reach, yes. But the dedicated social media analytics tools can monitor brand mentions, keywords, hashtags, sentiments, and even employee advocacy online. 

One primary difference between native analytics and social media analytics is that the latter can give you the reasons why anyone likes or engages with your posts. 

We will simplify the effectiveness of social media analytics below. 

What Can Social Media Analytics Tools Do?

Social media analytics tools include the following. 

Sentiment Analysis

It refers to the process of exploring how customers and audiences think of your brand. It is also known as opinion mining. Social media tools including Hootsuite offer sentiment analysis. 

Most tools track brand mentions when they are tagged but analytics tools such as Hootsuite can dig mentions based on positive and negative words including love, perfect, bad, terrible, and similar. Some tools can also distinguish among ambiguous or neutral sentiments of the audience. 

For sentiment analysis, tools are powered by natural language processing that eliminates human error.

Share of Voice

Share of voice is an important metric that social media analytics tools such as Sprout Social offer. This metric is analysed based on the conversations about the brand, the brand reach, and ad spending in the market against the competition. 

It can give marketers the opportunity to know better about what consumers prefer and how a business can get ahead of the competitors. 

Influencer Analytics

Native analytics platforms also are not designed to tell you which influencer you should choose based on their individual metrics. 

Approaching influencers with good metrics can be much more beneficial and more informed for a social media strategy. Social media analytics tools can track metrics such as number of posts influencers publish on their social media handle(s), total audience interactions per 1000 followers, previous brands they worked with, and similar. 

Dashboards

Data visualization tools offer myriad appealing ways to visualise and present data. Social media analytics tools, too, have built-in data visualisations and dashboards, and they are usually customisable. 

Reporting is as essential as tracking marketing efforts, and easy-to-understand visualisations and dashboards make it better to communicate and streamline work and keep stakeholders informed. 

Types of Social Media Analytics

There are five types of social media analytics. 

1. Descriptive Analytics

This is the most basic form of social media analytics. It describes what happened on your social media channels in the past, providing information like the following. 

• Reach: How many people saw your content.
• Engagement: Likes, comments, shares, etc. on your posts.
• Click-through rate: How many people clicked on your links.
• Demographics: Age, gender, location of your audience.

Some of the methods for descriptive analysis are mentioned below.  

• Data collection through platforms' native analytics dashboards, social listening tools, and website analytics.
• Basic calculations like averages, percentages, and ratios. Charts and graphs to visualise data.

Benefit: Provides a clear overview of your social media performance and identifies areas for improvement.

2. Diagnostic Analytics

This goes deeper than descriptive analytics to understand why certain things happened. 

It explores questions like:

• Which content performed better and why?
• Which platforms are driving more engagement?
• What are people saying about your brand?

Some of the analysis methods go beyond the ones used in descriptive methods. Segmentation, sentiment analysis, correlation analysis, and comparison between different time periods and content types are some. 

Benefit: Helps you identify the root causes of your performance and make informed decisions about your strategy.

3. Predictive Analytics

This uses historical data and statistical models to predict future trends and behaviours. 

It can be used to:

• Forecast future engagement and reach.
• Identify potential influencers and brand advocates.
• Predict the impact of changes to your strategy.

Here, the analysis method is quite advanced. Statistical modeling, machine learning algorithms like regression analysis, and time series forecasting are some common methods here.

Benefit: Allows you to be proactive and prepare for future challenges and opportunities.

4. Prescriptive Analytics

This takes predictive analytics a step further, suggesting specific actions you can take to achieve your desired outcomes. 

It can recommend:

• What type of content to post and when.
• Which platforms to focus your efforts on.
• How to respond to negative sentiment.

Benefit: Provides clear and actionable insights to optimise your social media strategy for maximum impact.

5. Quantitative Social Media Analytics

This focuses on measuring and analysing numerical data from your social media channels. It includes metrics like:

• Number of followers.
• Engagement rate.
• Click-through rate.
• Website traffic generated from social media.

Most of the data collection happens natively and from tools, which help calculate key metrics, track trends over time, and compare performance across different campaigns or platforms.

Benefit: Provides objective data to track progress and measure the ROI of your social media efforts.

Importance of Social Media Analytics

Decision-making process becomes easier as marketers get to know the perception of the customers towards the brand. Businesses can even know how much competitors are spending through analytics tools. Apart from that, some advanced tools can predict which posts can be better for engagement.

For example – 

A brand may be spending too much on hiring influencers and focusing on just one platform like Instagram. 

But with a social media analytics tool, the business can choose only the best influencers based on the KPIs or metrics and find out where the competitors are getting the most engagement apart from Instagram. For the next month, the business can reduce the cost of hiring and try out other platforms such as Facebook or TikTok. 

Another way to look at the importance of these tools is while creating a product. Aggregating feedback across various platforms can help brands resolve the common issues in products they face and spread across social media. Not listening or monitoring can be detrimental to brand perception.