Business Marketing Social Media Marketing

How to Apply Data Science for Social Media Marketing

Image courtesy of Pixabay

Data science is a rapidly progressing field of study whose relevance is only slowly being realized in different industries. In 2012, Harvard Business Review described data science as the “Sexiest Job of the 21st Century”. And as they had thought, it resulted in a massive growth in the space, resulting in several subdisciplines which complement the larger discipline of data science. As an umbrella term, data science can be used to refer to a broad spectrum of approaches which concern specific datasets and expected results – you can learn about all of them through our data science courses.

Data science is often confused with data analysis or analytics, but these are overlapping yet distinct things, with the latter being a part of the former. Data analysis consists of descriptive statistics, and a data analyst visualizes data and communicates meaningful data points extracted from a particular source to reach a certain conclusion. This can be understood as being only the first level of data science, which is a much broader category. A data scientist’s job involves collecting data from multiple sources and applying various techniques to analyse it. These techniques include machine learning, predictive analytics, as well as sentiment analysis. Their job, moreover, involves going deeper than communicating meaningful data points – they have to understand the data from a consolidated business perspective and then provide accurate predictions and insights which form the basis of crucial business decisions. The various fields in which data science finds real-world application include healthcare, retail, education, banking, and consumer analytics.

Yet another field in which data science has become particularly useful is social media marketing. Data science holds a lot of promise for social media since it can provide a wide spectrum of analyses, ranging from an advanced analysis of all social media activity related to branded content campaigns to acute social media listening through which insightful user personas can be created. Data science can also solve the potentially unsolvable problem of ad fraud by analysing the patterns behind clicks or impressions.

Mapping the way forward

In terms of social media, the exciting prospect that data science offers is the potential to map out the future for us. It takes us away from traditional and more blunt tools like word clouds, which offer signposts at best, but no tangible predictions which can be held accountable. Word clouds used to trusted tools through which social media marketers could understand and analyze various social conversations, but word clouds often misrepresented data unless there was a huge volume of activity. 

With data science, social media marketers can leverage the power of data in a more concrete way than word clouds could: with natural language processing algorithms, word usage can be contextualized and precise insights can be delivered. With the power of this certain information, any number of decisions can be made – from which words will be the most useful to employ in a social media campaign to which words to absolutely avoid.

Understanding communities 

Data science can help group certain movements on social media as belonging to a particular category; one of these categories is that of a community. One of the advantages of this is that if the members of a particular community are targeted in an ad campaign, it is much more likely to produce better results. 

The way to begin working on community groupings is to identify key areas that are discussed positively and set them as a base for your social media marketing campaign. These topics can be analyzed across different social media platforms and then identified. Through this identification, the next stage of analysis – cluster analysis – can be conducted. This will inform the marketer of the relation between any two people having a conversation on, for example, Facebook or Twitter. If they are connected strongly within a community, they can be targeted for specific ads, but if they are held loosely together then they can be approached by a data scientist through another nodal point to link them together more strongly.

Better visualizations for greater insights

One way for marketers to better understand their potential consumers is by understanding their life stories, and this can be achieved through better visualizations. With the amounts of data to be found online reaching new heights everyday, nuanced algorithms are required to understand their depths and represent them in enriching ways. This will lead to more focussed marketing campaigns with much better results.

Visualizations through data science can also be made with different axes and with different purposes than are commonly imagined. Social graph visualizations are one example, with the focus not squarely on an individual but rather on the larger social world in which they’re located. A whole host of different graphs can also be created to serve different purposes, ranging from scatter plots (used to represent correlations), line graphs (usually used for trends), pie charts (for proportions) and tables (for exact values). 

Social media ‘listening’ 

With the help of data science, social media marketers can perform what is called social media listening. It goes beyond simply monitoring conversations on different platforms and replying to incoming questions or comments – its focus is about extracting key insights from these conversations which can be applicable to a marketing strategy.

Social media listening platforms can give marketers access to global conversations, and in the process bring together diverse data banks. This allows them to have an accurate sense of customer opinions and trends and how to create them, by following the natural language of the market.

The future of marketing

For all the reasons stated above, data science is all set to determine the future of social media marketing! It can be so broad as to map an entire community’s preferences, or as specific as one person’s inclinations. It can lead you to better insights on data you already have as well as determine trends that will take place in the future. 

Data science has changed social media marketing as we used to know it, and now there’s so much knowledge still to gain! You can learn all the precise ways in which data science is impactful for social media marketing through our data science courses.

About the author

avatar

Vivek Kumar

Vivek is the President of Consumer Revenue at UpGrad, an online education platform providing industry oriented programs like courses like Big Data, Digital Marketing etc in collaboration with world-class institutes, some of which are MICA, IIIT BANGALORE, BITS and various industry leaders which include MakeMyTrip, Ola, Flipkart to name a few. He has 19 years of experience in diversified industries like Consumer goods, Media, Technology Products and Education Services. He has been leading businesses & multi-cultural teams with a consistent record of market-beating performance and building brand leadership. His previous engagement has been with Manipal Global Education services as Sr General Manager, Education Services (Digital Transformation Strategy & Global Expansion).