Practitioners and analysts alike know social media by its many websites and channels: Facebook, YouTube, Instagram, Twitter, LinkedIn, Reddit and many others.
Social media analytics is the ability to gather and find meaning in data gathered from social channels to support business decisions — and measure the performance of actions based on those decisions through social media.
Social media analytics is broader than metrics such as likes, follows, retweets, previews, clicks, and impressions gathered from individual channels. It also differs from reporting offered by services that support marketing campaigns such as LinkedIn or Google Analytics.
Social media analytics uses specifically designed software platforms that work similarly to web search tools. Data about keywords or topics is retrieved through search queries or web ‘crawlers’ that span channels. Fragments of text are returned, loaded into a database, categorized and analyzed to derive meaningful insights.
Social media analytics includes the concept of social listening. Listening is monitoring social channels for problems and opportunities. Social media analytics tools typically incorporate listening into more comprehensive reporting that involves listening and performance analysis.
IBM points out that with the prevalence of social media: “News of a great product can spread like wildfire. And news about a bad product — or a bad experience with a customer service rep — can spread just as quickly. Consumers are now holding organizations to account for their brand promises and sharing their experiences with friends, co-workers and the public at large.”
Social media analytics helps companies address these experiences and use them to:
These insights can be used to not only make tactical adjustments, like addressing an angry tweet, they can help drive strategic decisions. In fact, IBM finds social media analytics is now “being brought into the core discussions about how businesses develop their strategies.”
These strategies affect a range of business activity:
The first step for effective social media analytics is developing a goal. Goals can range from increasing revenue to pinpointing service issues. From there, topics or keywords can be selected and parameters such as date range can be set. Sources also need to be specified — responses to YouTube videos, Facebook conversations, Twitter arguments, Amazon product reviews, comments from news sites. It is important to select sources pertinent to a given product, service or brand.
Typically, a data set will be established to support the goals, topics, parameters and sources. Data is retrieved, analyzed and reported through visualizations that make it easier to understand and manipulate.
These steps are typical of a general social media analytics approach that can be made more effective by capabilities found in social media analytics platforms.
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