It seems like everyone and their cat has social media life now and the amount of data available is huge and updates every second. Such big amount of valuable information requires proper approach to its leveraging. In fact, handling these ever flowing streams of data is a daunting task.
However, it is a challenge which is worth accepting. If taken sensibly, the data can provide the insights into what customers think of brands, their new products, how they react to marketing strategies, adverts, offers. In fact, they can aid businesses in measuring their marketing effectiveness.
So how to deal with all these data?
For this purpose Social Media analytics tools are used.
Primarily, Social Media analytics tools focus on quantitative data, gathering numbers of likes, shares, posts and the main benefit it offers is juxtaposition of negative and positive feedback, predicting and (hopefully) averting the crisis if the negative response prevails. Social Media analytics tools spot keywords used in various Social Media, such as Facebook, Twitter and Linkedin.
Another (deeper) focus is sentiment analysis. Sentiment Analysis is used to extract opinions, attitudes and feelings, using language processing, text analyzing, computational linguistics, and NLP. Its aim is to identify how a product (for instance) is evaluated or the emotional state of the speaker or a writer while he or she was producing a text. Its aim is to retrieve the emotional effect targeted at the reader.
However, the technology isn’t advanced enough to tap into human brain, with all its complexities and contradictions, so the findings of Social Media analytics tools aren’t as trusty as we would like them to be. For example, we can’t say whether the users’ posts and comments should be 100% trusted and how much data is fake and disguised in masks.
Here are our tips for effective data mining
- The best strategy to deal with such amount of data is to define well your targets and then aim at them. Be specific. Don’t hunt just for the sake of hunting. Know what you are praying for. Use detailed search keywords and integrate dictionaries into your software tools
- In some aspects human touch can’t be faked by digital mind. Computers aren’t experts in sarcasm, slang, and other discourses misleading for computer logic.
- Teach your employees to use social media analytics tools.
- Stay up to date with new tools. Combine them.
- Before buying software media analytics software try it as a service.
And here is our takeaway:
Via Social Media companies you get access to customer data to benefit from. Social Media analytics tools enable you to structure it and retrieve the customer feedback.
However, the underlying motifs of such response is still a hidden treasure we are to learn to mine for.