Data science is a relatively nascent field that emerged to cater to the explosion of data at the intersection of various fields like economics, social science, statistics, environment, marketing, and statistics among others. It is defined as utilizing modeling tools to analyze and predict patterns that enable businesses to garner more return on investment (ROI).
Marketing of products and services is described as advertising/promoting the same. Digital marketing adds an online promotion mode to traditional marketing with more focus on attracting customers through advertisements in digital media like the internet, smartphones, e-mail and other digital media.
Combining data science and digital marketing makes a lot of sense in the 21st century due to reasons such as:
Thus if digital marketing campaigns employ data scientists or add data science skill-sets to their marketing staff through training then they really have a significant edge over competitors and can enable their clients to attract more customer and get better ROI. It is not essential for marketers to get a formal data science degree. Adequate training and willingness to learn are sufficient.
To transform a traditional marketing/digital marketing professional into a data science utilizing digital marketing professional, one needs knowledge of tools that help comprehend and filter large data sets for the useful bits of information. Some of the advanced marketing automation tools are:
Data science tools are not always seen as beneficial. There have been cases where companies circumvent local laws and misuse personal information.
In recent times, big data or also referred as meta-data analytics has run into issues especially when US companies perform such activities abroad. Facebook, Twitter, Google are all major companies that employ or have begun employing data scientists to research their customer data. They have run into legal trouble in Europe due to differing concepts of data as a material to be used or not to be used.
While in the US, the concept of data is utilitarian, which means that personal data is viewed and accepted as something that can be analyzed and used to improve ROI for companies. But in Europe, the prevailing culture is that a person’s personal data is only allowed to be seen and used by that person alone. Hence American companies like Facebook, Google, Twitter face issues with European regulators when employing data science research in marketing and analyzing personal data of Europeans. This ethical vs. legal dimension of data science in digital marketing needs to be accounted for since businesses are global in today’s world and have to take into account local sensitivities and sensibilities with regard to mining personal data.