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.
It’s disappointingly common for people to use data science when they actually mean data analysis or analytics, and that’s not exactly right.
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.
BuzzGraphs, for instance, show you how words are linked, and which words are most frequently used.
Based on the frequency of keywords observed, marketers can identify the most commonly discussed topics in social conversations.
Such analysis can then group people together, separating weakly connected groups.
Visualizations make it practical for marketers to understand these stories and generate insights that can massively improve social media marketing.
Data-science-backed tools can transform how brands conduct market research using social media data.
Social media listening platforms can allow marketers access to global conversations, bringing together large data volumes, capturing customer opinions and trends and feeding the data to a brand’s specific market research campaign: Begin with social media listening for researching a central topic.