In 2019, I first explored the importance of social media insights, but focussed on how to incorporate it into market research strategies; social media insights are the result of social media analytics, and in order to generate the best insights possible, its important to understand social media analytics in its entirety, and the important role it plays for insight professionals.
Social media is a fountain of consumer knowledge, with masses of data being generated every second. As such social media analytics has become a large section of market research; it is a term that’s often misunderstood, social media analytics is the process of both data collection and data analysis. Through the extensive use of smartphones and the creation of various online communities on platforms such as Facebook, Twitter, Instagram, and more recently, Tik Tok, social media analytics allows insight professionals to collate a lot of data, generating valuable insights on their audience.
The Benefit of Social Media Insights
If we were to try and summarise all of the insights that social media analysis can generate, then they could be sorted into a few categories. Social media analysis can help insight professionals to:
- Reach new audiences
- Promote their brand
- Communicate with their audience
- Spot new consumer trends
- Monitor if their strategy and campaigns are working
- Observe competitor activity
- Increase return on investment (investment of both effort and monetary expense)
Through all of this, social media analytics allows us to harness the power of our data and generating actionable insights that help us understand our audience, create content, services, and products directly tailored to their interests, and enhance our communication skills.
Measuring against the business’ and individual departments’ SMART objectives, the data collected and analysed from social media can go a long way to ensuring insight professionals stay aware of the wider market and pointing in the right direction. It provides a road map of sorts, for us to follow and alter course when needed.
But one thing to understand is that, although we may use it to propel our strategies forward, social media isn’t about brands, it’s about the consumers on the platforms communicating with each other about shared interests, whether that’s family, friends, or complete strangers. The data on social media comes in the form of ‘likes’, retweets, shares, and comments on both consumer and brand posts, and keywords that pop up in those posts. There is a lot of noise to cut through with millions of users posting pictures, videos, and posts every day, but there are tools that we can use to help distinguish the most valuable data.
Generating Social Media Data and Insights
Actionable insights are hard to generate, but even harder when the data is a mess of noise from millions of people. But there are lots of tools to help us with this process.
Social platforms like Facebook, Twitter, and YouTube have analytics tools built in to help brands identify where their audience is coming from, what type of content they engage with most, and the amount of engagement consumers have with each individual post. Some of the more in-depth data you can generate from these tools are follower responsiveness (Facebook), competitor benchmarking (Facebook), Ad tracking (all), and story metrics (Facebook/Instagram/Snapchat). These are great starting points for social media analytics, since they automatically collate the relevant data of all consumers who engage with the posts.
But there are also external tools that monitor consumer-brand interactions, trends, and even automate responses to direct messages when necessary. Google Analytics is one such free tool that, while it isn’t a social media analytics tool per se, links to your website and social media channels; it collects as much data on your website visitors as possible let you to explore the traffic that flows through from your social media pages to your website, where they’re from, and their basic demographic data for some extra key context. This tool also shows you which content works best on which social media channel, how many leads you’re generating vs. your conversions, and estimates the return on investment of your social media campaigns if you’ve set up that particular function.
All of this data is extremely helpful but sometimes it’s hard to interpret it. Google analytics, for all of its usefulness, only projects the data in the forms of graphs and data tables that can be hard to analyse for research beginners. This is where data visualisation tools come in handy, but that’s a topic for another blog.
Social media analytics encompasses a range of different analysis techniques that focus on different areas of insight generation: predictive analysis, for example, takes the data generated and identifies consumer trends based on past analytics; sentiment analysis techniques sift through the data to find out and track the truth of what consumers are feeling when (this data can then be cross-referenced with other marketing campaign data to see if they’re having any effect on consumer attitudes towards the brand); and keyword analysis allows insight professionals to track many different things at once, such as response to campaigns/products/services, as well as attempts to interact with the brand.
From this, insight professionals can keep up to date with consumer perceptions in real-time, and thus generate actionable insights for stakeholders to act upon; insights such as what content to create and when (this is especially useful for seasonal content), what consumer sentiment is in regards to a new product or experience, how consumers want to be interacted with, or even how to rebrand the organisation to connect more with customers.
How does Social Media Analysis Fit into Market Research?
How does this fit into market research? Well, there are many ways in which social media insights can overhaul an organisation, but the best way to make sure a brand is making the right decision is to fuse different research methods together. Social media analytics, like any other research method, has it’s flaws that can easily be covered by other research methods: behavioural research techniques, for example, have proven valuable when pursuing a true understanding of consumer behaviour on all platforms, not just social; virtual and augmented reality techniques are great for immersing a participant in a situation to see what they will truly do rather than having to rely on what they say they will do.
There are a few mistakes that an insight professional might make during social media analysis, but along with resources and guides to help you, blending social media insights with other research methods will open up a full spectrum of insights so we might work towards a true understanding of our audience.
This article was originally published on the FlexMR Insight Blog and can be accessed here.