Data Science, in essence, refers to the methods of extracting meaningful insights from a large set of data. The last few decades have seen a tremendous increase in the overall data, and the ways in which this data is collected; which has eventually given rise to much more advanced and sophisticated tools and techniques for studying data. Today, Data Science encompasses terms like statistics, data analysis, machine learning, and more, and is used in order to perform business analytics, business intelligence, predictive modelling, or any other use of data, usually to enhance productivity and performance.
This data deluge has also given rise to an increased demand for up-skilled data scientists. Before we proceed further, it’s essential to let you know that if you wish to embark on your journey to tame the data, you can get yourself enrolled in our data science courses.
Despite being similar and often overlapping with concepts like data analysis and data analytics, data science is still quite distinct from the latter being a part of the former. A data analyst job involves visualization of data and communicating meaningful data points extracted from a particular source to reach a certain conclusion, whereas a data scientist’s job involves collecting data from multiple sources and applying various techniques to analyze it. These techniques could vary from machine learning to predictive and sentimental analysis.
Moreover, a data science analyst has to dig deeper than simple communication of meaningful data. They need to process the acquired data. understand it from a consolidated business point of view, and provide accurate predictions and insights which will form the basis of crucial business and marketing decisions.
This leads us to the realization that data science indeed plays a vital role when it comes to social media marketing. Data science is the answer to a wide array of social media analysis processes, ranging from the branded content campaigns to acute social media listening, all of which can help create insightful user personas. It can also help solve the issue of ad frauds by accurately analyzing the patterns behind clicks or impressions.
Let’s look at how exactly data science and analytics can help in implementing successful content marketing strategies:
Understanding Customers
It is always a better idea to target specific online communities for certain products/ad campaigns, Rather than bombarding the public with your ad campaigns, a better approach will be to research and find out the exact target audience, and gracefully approach them. Data science can help with this by helping group certain movements on social media as belonging to a particular group, thereby identifying communities This can help you solve the question of “who to” target, “how to” target them, and even “when to” target them, for the most effective marketing campaign.
The proper way to begin working on community group dynamics is to identify key areas that are discussed positively and setting them as the base for your social media campaigning, very much similar to any successful election campaign strategy. Data science can help analyze and identify this across various social media platforms, making it easier to conduct the next step of data analysis, which is cluster analysis. This can inform the marketer of the relation between two users across different social media platforms, say Facebook and Twitter. If held together by strong community links, they can be targeted for a specific ad campaign. and if not, then data science can provide for a better nodal link to connect them more strongly, thus allowing for the creation of more effective content for the marketing strategies.
Enhancing visualizations and improving insights
One way to understand your potential customers better is to have an improved idea of their interests, including likes and dislikes. In today’s day and age, with the infinite sea of information available online across various social media platforms, better visualization is the key to achieve the goal of creating an improved target based marketing strategy. Data science can be utilized to target this information and analyze it, in order to produce the most effective target based content marketing strategies. Such strategies will allow the content creators to churn out the content best suited for effective marketing campaigns, which will eventually result in largely improved outcomes.
Data science can also be used to understand a person’s social interests, including the places they’ve visited, the people they interact with, and such. All of this is possible using social graph visualization and this greatly enhances the spectrum of the content marketing strategies. A whole host of different graphs can be used to serve this purpose including scatter plots, line graphs and even basic statistical tools like pie charts and tables. Knowing these finer details about your potential customers will help you roll out better strategies every day.
Social Media Listening
Social media listening is essentially the process of monitoring conversations to understand how customers online are reacting to a particular entity, brand, product, or even a campaign. Using Data Science, social media marketers can not just effectively monitor online conversations, but also extract key insights from these conversations to create improved marketing strategies.
Social media listening gives marketers access to diverse data banks, across globally present social media platforms. This, in turn, provides them with an improved sense of customer opinion and gives them the opportunity to create more reliable and effective campaign strategy, fueled by the added benefit of knowledge of the natural language of the market.
In conclusion
With the onset of digitalization in today’s era and the increasing presence of technology in every aspect of life, it is not surprising that data science will prove to be the key to any successful content marketing strategies. Be it mapping an entire community’s preference or focusing on an individual’s inclinations, data science can help marketers cover a wide spectrum of customer related issues.
Data science is not only capable of providing you with such answers and new information but also help you better utilize the information and resources already at your disposal.
