Social media contains a massive amount of data that can help brands understand consumers, competitors, campaigns and more. To get the most value from this data, you need to understand the elements of social media analytics. But with so many different components, how can you make sense of social media analysis and use it to uncover business insights?
We’re breaking down the basic Elements of Social Media Analytics with a blog series to serve as an introduction (or refresher) on how each component of social media analysis works and how they all fit together.
What is Social Media Analytics?
In his Seven Layers of Social Media book, Gohfar F. Khan’s defines social media analytics as “the art and science of extracting valuable hidden insights from vast amounts of semistructured and unstructured social media data to enable informed and insightful decision making.”
Check out our What is Social Media Analytics? post for more on the definition:
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Social media provides a great way for brands to understand what consumers are saying about their products, ads, competitors and more. But what is being said is only one part of a larger story. Understanding who is doing the talking is just as important. Audience analysis allows brands to gain a deeper understanding of their current and potential customers to improve marketing strategy, customer experience, and brand perception.
How do consumers really feel about your brand? What about your competitors? Or the latest trend? In the past, when brands wanted to understand how consumers felt about something, they had to pay big money for market research firms to run focus groups and administer surveys. Today, sentiment analysis tools allows brands to answer these questions much more quickly and easily than in the past.
Images are taking over social media. What does the growth of image sharing mean for social media analytics? How can brands track and leverage the growing number of images posted to social media? Emerging image analysis and computer vision technology allows brands to add images to their social listening strategy and get the full picture of what’s happening.
From voice assistants to self-driving cars, machine learning is everywhere. Every day, a new product, app, or service announces that it uses “machine learning” to get better and smarter. But because the term can mean so many different things, it’s hard to understand exactly what machine learning means when it’s applied to a new technology. Machine learning gives an analysis tool the ability to learn exactly what you’re looking for in social media posts, and categorize posts based on that training.
Social media analytics provides instant access to competitive intelligence on your business landscape from specific competitor’s products to larger consumer trends. Based on all of this intelligence, you can make smarter decisions about your campaigns, creative, ads, and more. Having access to these insights in real-time means that you don’t need to wait months for a competitive intelligence report to spot an opportunity and take action.
It isn’t easy to track the true impact of a global marketing campaign. Sure, modern digital marketing makes it easy to track clicks, views, and likes, but what about the big picture? Are you reaching your target audience? What is their reaction to the campaign? Is the campaign changing the conversation about your brand? Luckily social media analytics can help you answer these tough questions.
Want a deeper look at the fundamentals of social media analytics? Download our free guide: