Social media analytics involves the use of social media analytic tools to gather, decipher, and analyze data on social media platforms. This data is often collected and then used in making informed decisions about businesses. These tools are also useful in mining customer sentiments, the end support marketing, and other customer activities.
Steps in conducting social media analytics
Social media intelligence often takes into account the various goals that the analyzed data benefits from. The business goals that are commonly identified include the ability to increase revenue, getting the necessary feedback on products and services, and also the reduction of customer service costs. Through analytics, you are also able to improve your products and services based on the feedback you receive. Once you identify these goals, businesses then define key performance indicators (KPIs). These KPIs are useful in the evaluation of business data in analytics.
You are also able to identify various business metrics. Some of these metrics include customer engagement, which is defined by the number of followers on your social media tools and handles. It often means tracking the number of followers in your Twitter account, the re-tweets, and also the number of times your company gets mentioned in a tweet.
Social media analytics can also combine with social media monitoring. This monitoring means studying the number of people that follow your product or business on Facebook or Instagram. Through monitoring, you will also identify the times that people interact with your post through liking or sharing.
It also involves the use of sentiment analytics. Through this analytical mechanism, you can decode and understand natural language and machine learning tools. You are then able to clearly understand the hidden meaning in a social media post about your product and services. Through machine learning, a company will understand the attitude of customers towards their company. The management will then learn how well their products are familiar to customers.
Common tools in use
To analyze various unfamiliar and unstructured data in your social media, you will need to use several social media analytics tools. Some of the means might include text analysis, while others might consist of tools used in harvesting and storing necessary information. You might get these tools from several individual firms, while others come in the form of software packages that provide social media intelligence packages. Machine learning is a popular analytics platform and encompasses various tools such as Python, R, and TensorFlow.
Benefits of social media analytics
Social media data often comes in large quantities. Data were analyzed differently in the past, where various business ventures spent a lot of money paying research customers to get feedback from their clients. These days, it is quite easy and fast to get feedback through social media postings. However, information posted on social platforms becomes difficult to understand since it is in the form of natural language and free text. However, through machine learning and artificial intelligence, this kind of communication becomes easy to use and understand.
Through the use of social analytics tools, business ventures get the needed information about their brands and the products and services that their customers enjoy. Business enterprises can understand a lot about the future of their brands. Businesses are also able to reduce the financial costs involved in hiring a team of research experts who get feedback through focus group discussions.
