Tanzania Finance

Sep 30 2017

What is social media analytics? Definition from #social #media #analytics #companies


social media analytics

Social media analytics is the practice of gathering data from social media websites and analyzing that data using social media analytics tools to make business decisions. The most common use of social media analytics is to mine customer sentiment to support marketing and customer service activities.

Download this free guide

Download Our Guide: Create an Analytics Success Story

Learn how to gain executive approval and drive operational, cultural changes within your organization.

By submitting your personal information, you agree that TechTarget and its partners may contact you regarding relevant content, products and special offers.

You also agree that your personal information may be transferred and processed in the United States, and that you have read and agree to the Terms of Use and the Privacy Policy .

The first step in a social media intelligence initiative is to determine which business goals the data that is gathered and analyzed will benefit. Typical objectives include increasing revenues, reducing customer service costs, getting feedback on products and services, and improving public opinion of a particular product or business division.

Once the business goals have been identified, businesses should define key performance indicators (KPIs ) to objectively evaluate the business analytics data.

Metrics to track

Business metrics derived from social media analytics may include customer engagement. which could be measured by the number of followers for a Twitter account and number of retweets and mentions of a company’s name. With social media monitoring. businesses can also look at how many people follow their presence on Facebook and the number of times people interact with their social profile by sharing or liking their posts.

More advanced types of social media analysis involve sentiment analytics. This practice involves sophisticated natural-language -processing machine learning algorithms parsing the text in a person’s social media post about a company to understand the meaning behind that person’s statement. These algorithms can create a quantified score of the public’s feelings toward a company based on social media interactions and give reports to management on how well the company interacts with customers.

Popular tools

There are a number of types of social media analytics tools for analyzing unstructured data found in tweets and Facebook posts. In addition to text analysis. many enterprise-level social media analytics tools will harvest and store the data. Some of these tools come from niche players, while more traditional enterprise analytics software vendors offer packages dedicated to social media intelligence.

As more social media analytics rely on machine learning, popular open platforms like R. Python and TensorFlow serve as social media analytics tools.

Importance of social media analytics

There is a tremendous amount of information in social media data. In decades past, enterprises paid market research companies to poll consumers and conduct focus groups to get the kind of information that consumers now willingly post to public social media platforms.

The problem is this information is in the form of free text and natural language, the kind of unstructured data that analytics algorithms have traditionally. But as machine learning and artificial intelligence have advanced, it’s become easier for businesses to quantify in a scalable way the information in social media posts.

This allows enterprises to extract information about how the public perceives their brand, what kind of products consumers like and dislike and generally where markets are going. Social media analytics makes it possible for businesses to quantify all this without using less reliable polling and focus groups.

This was last updated in June 2017

Continue Reading About social media analytics

Related Terms

big data analytics Big data analytics is the process of examining large and varied data sets — i.e. big data — to uncover hidden patterns. See complete definition data scientist A data scientist is a professional responsible for collecting, analyzing and interpreting large amounts of data to identify ways. See complete definition single source of truth (SSOT) Single source of truth (SSOT) is a concept that an organization can apply as part of its information architecture to ensure that. See complete definition



Written by admin

Leave a Reply

Your email address will not be published. Required fields are marked *