Social media is undoubtedly a big contributor to big data, but what can marketers do with the information they get from social media platforms and why is it important?
Social media has gained popularity in the past few years and many marketers have questioned the use of these platforms and the data gathered from them. Questions like “How many customers did I get from this campaign?” and “How much revenue is this platform generating for the business?” are all valid today. While many companies and individuals have collected data from these platforms in the past, the data gathered from social media platforms have become more sophisticated and advanced.
So, what is data mining and why should marketers care? This article explores the definition of data mining, why and how marketers can use it, and how the data can be incorporated into your social media strategy.
1. What is data mining?
According to Entrepreneur, “Social media data is the information collected from how people interact with your social media profiles. This data is measured through likes, shares, comments, follower growth, follower loss, mentions, hashtags, impressions, and more. When we mine the data from our social media accounts, we collect all these variables. The purpose is simple: We want to see how our consumers engage with our social media content.” It’s about utilising the networks you have at hand and pulling relevant insights and information from the immediate network.
It puts you in a sea of people where information can be given and received. This is truly the beauty of social media!
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2. Why is data mining important?
Data mining helps spark ideas, thoughts, and opinions you haven’t thought of before, especially because a lot of teams are still not inclusive or diverse. Data mining gives you an outside perspective on the world and helps you make informed decisions for your business.
Whatagraph, a marketing analytics and social media reporting company says, “Due to the massive amounts of user-generated data that is being collected and analyzed through this process, social media data mining has found wide usage and is increasingly being recognized as an invaluable asset in many fields. Although it has primarily been used for business purposes, this process is nowadays often employed by researchers and by government agencies as well.” Social media marketers find data invaluable as they use it to improve the customer experience from the start of their customer journey. You can use existing data from social media to create content and help ease the issues users face daily.
It’s always important to do proper in-depth research before creating or refining your social media strategy.
Data mining can assist with creating targeted content, products, and advertising to communicate to your social media audience. Data-driven content helps marketers to target current customers and potential prospects to improve your company’s overall ROI.
3. The pros and cons of data mining
While social media data are readily available to marketers, some pros and cons need to be considered.
- Listen to the public’s conversations around a specific brand or company and resolve all negative or positive comments.
- The data will help you with a competitive analysis and learn more about the strengths and weaknesses of your competitors.
- Identify patterns by analysing social media data and create a social media strategy to support your findings.
- You can create organic and paid campaigns addressing issues highlighted by your social media audience.
- Data from social media platforms can often be negative as it’s based on user opinions and feedback. Always investigate the problem first before you reply to any comments or messages.
- When companies implement social media strategies, they want to see quick, and speedy results. Unfortunately, you have to wait a few weeks to get results and think about ways to optimise further.
4. Social media data mining techniques
As mentioned, data mining can help us understand big data a bit better. Below are some data mining techniques which you can try out for your business:
Extract keywords from social media to analyse their context and the behaviour behind it.
Sentiment analysis in data mining is essential as it includes opinions around your product or business. The type of opinions can be used to inform your content strategy and create campaigns tailored to specific needs.
Analyse your social media audience
What is your audience passionate about and why should you care as a marketer?
Analyse past data to predict the future
Use historical social media data to inform future content or trends.
An example from LinkedIn:
See the image above, from LinkedIn. This is a way you can get a quick sentiment check , and gives you a start off point for your research for articles and other content concepts.
The example given was of authors asking for an opinion on 'this book cover or that book cover’, posting, for example, two versions of their book covers on Instagram and gauging audience reactions.
5. In conclusion
When you have a lot of data available, finding relevant information to inform your business decisions can be difficult. From brand loyalty to new product development, make sure you use data mining techniques correctly to process and collect unstructured information. Our advice is just to start somewhere and see what the data can give you!
Book an appointment with our Chief Executive Officer, Veronica Wainstein to discuss your data mining requirements: