Impact of Data Science over the Marketing Sector

By CIOReview | Monday, April 2, 2018
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Marketers find out the success of their decisions via data scientists, who use data points and trends in strategizing content, analyzing it to meet the requirements and measure the outcome.

• As data science insights are connected to marketing results, a truly powerful data scientist needs to connect people and business insights. Data science aids in mapping social networks to map customer personas. Identifying demographics and locations and analyzing customer demands helps in developing new approaches to traditional marketing strategies.
• A shortage of data scientists will require markets to adapt to the usage of data for their work across the globe, and they will need to use it more aggressively to use the information available to them. Marketing teams can take advantage of data in several ways, like:

1. Department- or division-wise silos create barriers, preventing the flow of useful data. There need to be ways for platform integration and data sharing within a company, such as systems to report data from one segment to another.
2. To be actionable, data needs to be timely, or at least include information about the past that helps in analyzing current trends and patterns. Real-time data analytics is the best possible way of streaming current data, as it allows marketers to act on information as it happens.
3. A data platform is required for accurate data gathering. The company’s data needs to be highly accurate as it showcases the return on investment (ROI) while being the ROI in itself. Dynamic visualizations aid in simplifying complex data by capturing numbers in a graphic representation. These visualizations pave the way for marketers and data scientists to unlock collaborative operations and interpret the meaning of data for future campaigns and marketing efforts.

The importance of data scientists does not reduce the importance of data science for marketing; rather, marketers should feel compelled to learn to analyze data alongside data scientists so that they can continue to benefit from data science.