How Ai is disrupting the market research industry?

This is indeed a very interesting subject that is being discussed for quite sometime now. As I was doing my study on this subject, I came across a very interesting report that was prepared by Qualtrics, a customer management company. They did a survey of 250 market research decision makers to ask them how much they believe AI will impact the industry. The results were interesting and should give B2B market research companies a sense of how Ai can disrupt market research.

·         93% of researchers see AI as an industry opportunity and 7% see it as a threat

·         80% say AI will make a positive impact on the market-research industry. Both older and younger researchers share this view.

·         26% say AI will create more market research jobs than today while 35% believe it will reduce the overall number of jobs. 39% don’t think it will change the job market.

There are different roles that Ai can make redundant. Some of the results from that question are:

·         97% respondents felt that Market Research Assistant jobs can become redundant

·         94% people feel that Research Analyst jobs can become redundant

·         95% feel that Statistician jobs can become redundant

·         65% feel that data scientist jobs can become redundant

·         60% feel that Market Analyst job can become redundant

 However Ai is not going to make an impact on strategic jobs such as Product Managers, VP of Market Research and Market Research Project Manager. Market intelligence companies will still require these roles to fulfill client requirements. 

·         99% respondents felt that VP of Market Research will not be affected

·         98% people feel that Product Manager jobs will not be affected

·         71% feel that Customer Insights Manager job will not be affected

Overall, about half of market researchers feel confident they know what AI is but nearly all predict that AI will have a significant impact on the market-research industry within 10 years.

Some of that optimism may be due to high-tech hype, but what used to be hype is starting to look like real-life as we are can have conversations with our phones and climb into cars with no driver.

The technologies that will have most impact on ai driven market research are:

·         Advanced data analysis

·         Automated stats analysis

·         Natural language processing

·         Text Analysis

·         IoT

The survey also indicates that technologies such as survey design tools, chatbots like Facebook Messenger, Virtual reality, Facial recognition and basic data analysis are least likely to affect the Market Research Industry.

The industries that will be most affected by ai and the technologies are listed below:

·         Education, Financial Services, Retail and High Tech will be affected by NLP

·         Healthcare and Media will be affected Advanced Data Analysis

The next part of this blog will try and uncover the skills that are required to support the growing demand for Ai. The figure below gives us a very clear trend of the skill requirements for Ai. 

We clearly see in this figure that the demand for Scala, Python and R is rising over the years as compared to Java, PHP and Perl. Python is one of the most commonly used in Artificial Intelligence as is R for Data Analytics. These 2 technologies will be in demand in the near future to support Ai and Data Analytics in Market Research and other industries.

The key skills that I have identified by referring to a blog on Done are as follows:

·         Excellent knowledge of Algorithms that are suitable for solving the problems at hand. The skills required are a broad set of algorithms and applied maths.

·         Excellent knowledge of Probability and Statistics to understand different AI models

·         As mentioned above the programming languages required are Python, C++, R, Java, etc.

·         Distributed computing knowledge is essential for Ai because the data sets are spread across the entire cluster of machines and not limited to a single machine.

·         The other technical skills required are good command over UNIX tools and expanding the knowledge of advanced signal processing techniques.

·         There are some other skills that Ai professional need to possess and these include curiosity and creativity, ability to stay updated and grasp new concepts and finally perseverance and patience. 

In my closing comments, I want to summarize a few things based upon my own experience of developing projects and based upon research that has been done.

·         Ai is a forward looking technology that gives decision makers a lot of clarity of what may happen based upon already existing data sets. Solutions such as heat maps help us determine where the incidents or data agglomeration is happening.

·         When working on Ai solutions be very clear on the final objective that you want to achieve out of the solution.

·         Ensure that the right data sets are shared with the development team and they are clear on the algorithms that will generate the final results.

·         Run large data sets to test the results and ensure that the final objectives are met.