Five Ways AI Is Changing the Future of Marketing Research for the Better

The rise of artificial intelligence (AI) has fundamentally changed the way companies and brands understand and communicate their target audience. This applies no more than in the field of experience management (XM) and market research.

Artificial intelligence and machine learning can evoke polarized views in public discourse: for example, many welcome AI as a way to reduce repetitive and irrational work; others fear for the same reason and think that artificial intelligence combined with robotics will replace human work.

Researchers have reason to be optimistic about artificial intelligence. Here are five ways that AI can change the future of XM research for the better.

  1. Understand what customers really want

AI gives market researchers access to tools such as powerful automated text analysis, which can analyze millions of comments, both spoken and text, in minutes and create a differentiated understanding of what customers think and want.

Powerful algorithms can learn from respondents and ask appropriate follow-up questions and ask questions that are specific to the interests and needs of an individual interviewee.

With natural language processing and sentiment analysis, market researchers can see trends and feelings in real-time across multiple channels.

  1. Find respondents more quickly, accurately, and in ways that maximize existing data

Using artificial intelligence, market researchers can analyze a larger group of respondents and remove those that are not suitable, resulting in better and more personalized lists of potential candidates. Using techniques like access to social graphics and access to blockchain information (ironically) will catch “bots” pretending to be human. In this way, AI helps to speed up the process of finding the best possible respondents and, with other techniques, probability-based sampling.

If you find respondents in customer databases, you can also easily ignore the large amount of existing data that can occur, for example, in the form of past company data collections. AI can unlock and process operational data that may have been ignored and combine it with more recent experience data to finally gain clarity and insights.

Also, researchers work with companies to collect information from customers who choose to share their data to shape products and brands for the future. This data can include revenue, segmentation, and purchases, for example, from rewards programs organized and researched for AI insights.

  1. Remove the bias from customer feedback

Prejudice is a big risk – it can interfere with data integrity. However, AI can remove unconscious human prejudice from both respondents and studio design. For example, if you run data using an assessment tool that uses artificial intelligence, it analyzes the questions and provides real-time suggestions that address the potential bias and improve data collection.

  1. Conduct a thorough secondary search

Secondary research, such as syndicated studies or meta-analyses, and advice from management consultants are often essential for small and large companies to make financially sound decisions. But this type of research and consultant support can be time-consuming and expensive.

Primary research can be faster and cheaper with the help of AI. And the use of artificial intelligence means that companies can quickly analyze secondary research and identify the main trends and themes in the data, without the help of management consultants to do the heavy lifting.

  1. Constantly improve the quality of studies

The quality assurance aspects of AI cannot be overestimated. AI can identify areas where problems need to be improved or where there is prejudice. Machine learning can also be used to optimize feedback collection from future customers based on previous data.

As AI evolves and its use becomes more popular, the potential benefits for XM researchers and companies as a whole only increase. By integrating these technologies, marketers can develop more up-to-date, accurate, and, ultimately, more informative information about their customers, employees, products, and brands.