Harvard Business Review famously described data science as the “Sexiest Job of the 21st Century” in 2012, causing a massive explosion in opportunities in this space. Today, data science has spread its hold over the digital marketing landscape.

Particularly for social media marketing, data science promises a lot. From advanced analysis of social media activity on branded content campaigns to create insightful user personas via social media listening, to complex data patterns made easy to understand via visualizations, to overcoming the perennial problem of ad fraud in advertising ecosystems, data science has potential applications that significantly improve social media for brands.

In this article, I’ll cover four ways in which brands can leverage data science for better social media marketing results in 2018.

It’s disappointingly common for people to use data science when they actually mean data analysis or analytics, and that’s not exactly right. Data science is not even business intelligence. It’s way broader in scope, and it involves exploration of multisource data to understand unseen underlying pattern that bring out important insights and relationships, which can be expressed through visualizations.

Moving beyond word clouds with data-science-powered tools

Word clouds have been trusted tools for social media marketers to analyze social conversations and understand what’s being discussed.

Although brands could often stumble upon an important pattern, word clouds are, in reality, pretty blunt tools. Unless you have a high volume of activity, word clouds can be misrepresentative, requiring marketers to carefully guard against irrelevant words.

Thankfully, marketers have access to tools that leverage the power of data science along with natural language processing algorithms in order to contextualize word usage and deliver meaningful insights.

BuzzGraphs, for instance, show you how words are linked, and which words are most frequently used. Entity analysis also helps, associating words and small word groups with their semantic types, such as a brand, a person, a website, etc. Deep diving into BuzzGraphs and entity analysis is possible in…