The four types of social media analytics explained
In an era of social media permeating our lives, there’s nothing more important for marketers than tracking the performance of their posts. It’s a free-for-all world – which means there’s a lot of competition for our customers’ attention spans. Knowing what works and what doesn’t is the key to successful social media marketing.
As such, there is nothing more important than analytics. There are four main types of social media analytics you should be concerned with if you want to achieve social media success. These four types are:
- Descriptive analytics
- Diagnostic analytics
- Predictive analytics
- Prescriptive analytics
All four seek to answer different questions and provide different insights. How do you tell which one is which? What situations are they useful in? Worry not, dear reader – we’re here to demystify the four types of social media analytics.
Descriptive analytics answer the question “what is happening”? “What happened”? These types of analytics cluster similar types of data together in order to produce a cohesive view. Comments and posts can be grouped together, for instance, for the purpose of sentiment analysis (as offered, for instance, by our very own SentiOne platform). Any time you gather a lot of similar data points in order to analyse them looking for patterns, sentiments, and/or trends, you’re dealing with descriptive analytics.
Diagnostic analysis focuses on the numbers: like counts, follower numbers, pageviews, reviews, shares, what have you. This type of analytics focuses on the performance of posts and campaigns and attempts to discern what made them successful. By comparing the performance of different campaigns, trends and consumer preferences can be discerned. Both diagnostic and descriptive analytics are reactive – that is, they are concerned with events that have already happened.
In contrast, both predictive and prescriptive analytics are proactive – as in, they attempt to predict trends, events, and shifts based on existing data. It can range from simple things, like predicting possible visits to a location based upon posts expressing that intention, to forecasting entire trends and phenomena based upon mentions. Social listening tools can help identify upcoming trends and shifts in consumer behaviour by analysing large volumes of social media data and indicating the shifting popularity of keywords.
Finally, prescriptive analysis is the analysis of data with the intention of providing the best way to proceed at any given moment. This can be applied to situations ranging from handling social media crises and incidents (“how well does this type of apology track with our target audience?”) to purchase preferences (“we’ve identified this group of customers – how do we optimise our sales process to their habits?”). Although it’s an incredibly useful form of analysis, it requires a lot of data in order to truly show its potential.
All manner of social media activity requires good analytics. Knowing how to understand and use your data can take you very far – provided, of course, you know what you’re looking for.
If you’re interested in doing a little bit of analysis yourself, social media reporting tools with excellent reporting capabilities – such as our own SentiOne (#humblebrag) – can get you off the ground in no time. Get in touch with us to schedule a free demo.