In today’s digital world, market research is not limited in targeting consumer behavior or getting insights obtained from data. In fact, with the initiation of the internet and stock of new types of data, there is an increasing demand for more approachable strategies and methods for better and quick insights, (have a glance at top BI tools and techniques in 2020)
Consequently, Data Science comes into the picture, it became relevant due to its processing to select, gather, explore, and draw insights from the limitless size of data. (Don’t you want to learn the 5-steps process of qualitative data analytics)
Data science also includes statistical methods, but data was unlike the data used by marketers in market research. As a result, a new set of skills and roles are required which gives existence to “Data Science”.
“Research is to see what everybody else has seen, and to think what nobody else has thought.” - Albert Szent-Gyorgyi
In the course of this blog, you will obtain the essence of market research and data science, in ways, they are crucial in business, various factors which relate them and also have a difference in some aspects, how clients would get the benefit of the approach to combine market research and data science to leverage fortunate businesses.
Though market research and data science need to be thought of interconnected entities, their combined insights can direct to a better understanding of market issues as no organization can sustain without experiencing past behavior or future predictions separately.
A vast understanding of both is required to make a responsive and productive decision for company growth.
Traditionally market research is applied for solving business problems and driving a business to lead in the competition, it includes everything about consumer behavior from the consumer segmentation to purchasing behavior and finishes by the use of statistical methods or approaches that assemble and analyze data to make inferences about any business issue. This is how consumer behavior analytics gets performed.
No doubt, many organizations have proved that infusing data analysis along with an appropriate chunk of statistics and a huge amount of consumer data and behavioral data can give tremendous outcomes, in fact, it is superior to earn a rival position. It is based on one’s strength to produce customer’s necessities and demands on time in ways that are better, faster, and cheaper.
We all know that Data science has moved beyond the capabilities of market research as it uses more vigorous scientific and technology-enabled methods.
The methods that data science uses are basically machine learning algorithms, so as an outcome, data science is higher than to be research and analysis and usually a portion of programming also. As discussed earlier data science also estimates different types of data like unstructured, structured or semi-structured so analyzing process initiates with; you can deeply learn easy to understand data exploratory analysis here
Deciding what type of data or method needed for analysis, and incorporated with specific organizational objectives.
Assessing and selecting dataset.
Cleaning the data, explore and investigate data applying statistical methods, machine learning, data modeling.
Understanding results to communicate insights.
Market research is basically roamed around to consumers, customers, and competitors through the information. This information has a critical role to recognize and establish various opportunities and complication arise in the marketing, this helps in the following way:
Generate and analyze actions for marketing,
Engaging marketing performance, and
Improving the marketing process.
(You must read a case study of Netflix that includes digital marketing to maximize customer experience using data handling).
Market research is important to address these issues as it sketches the outline for gathering information, controls, and executes the process of data collection. It also analyzes and transmits insights and implications. Moreover, market research is conducted in two ways;
As the data is increasing exponentially with time, its analysis is a difficult task which is needed to be handled precisely, again, you have seen how data analysis and market research operate in ways to tackle a different form of data in respective types of analysis method and get tremendous benefits.
Market research is deploying means into the target to collect data as per the need, the information accumulated from this time-bound activity is later refined and investigated to withdraw key insights. This would turn benefits as;
Inference into the market viewpoint.
Recognize various business opportunities for better investment and growth.
Outline marketing activities.
Proffer an appropriate strategy for decision making.
We know that data science is exploring, analyzing, interpreting and transferring raw data into useful information that gives the following benefits;
Immediate and controlled findings within less duration of time.
Deeper insights for improving efficiency.
Faster decision making based on the predicted outcomes.
Enhance revenue with the lesser cost for better improvement.
Market research and data science have variations in their real-time practical applications, skills in demand but having similar goals. Both investigate for information and insights to build better decision-making capacity of any organization providing skills difference to work on any issue.
Market research comprises conducting interviews, market surveys, etc. to get an idea about the customer’s story whereas data science consists of testing hypotheses, regression analysis, data modeling, etc. to analyze the pattern of consumer’s data. Let’s have a deep look at their distinctness;
Market research explores to learn human behaviors and rules that drive the action of consumers using data visualization tools whereas Data Science tries to use analytical modeling to predict new and emerging patterns from different sources.
Market research encompasses the skills that are designing surveys, people or time management, and qualitative and quantitative analysis of data whereas Data Science covers data analysis, software engineering, machine learning, and data visualization.
Market Research uses various strategies and techniques such as one-to-one interviews, focus groups, surveys or making question, hypothesis testing, regression analysis, data collecting, and analysis, explaining recommendations whereas Data Science is based on testing hypotheses, regression analysis, time-series forecasting or model deployment, clustering, revealing recommendations, data storage, and analysis.
I hope this blog gave you insights about the transformation of market research to data science, even though no business is succeeded without the implementation of both market research and data science as both have specific functions to perform in any organization for better efficiency.
“What is research but a blind date with knowledge?” - Will Harvey
It can be observed that market research conducts a market survey and that uses sampling and statistics for findings whereas data science use statistics and algorithms to get insights and predict future outcomes.
By the time technology augmented, Data Science has connected with IoT that are influencing digital marketing combinedly in various industries including the food industry, fashion industry, etc. For more blogs in Analytics and new technologies, subscribe to the Analytics Steps newsletter, and connect with us at Facebook, Twitter, and LinkedIn.
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