Industry Insights

AI Trends in Qualitative Research



Research is fascinating; it allows us to dig deeper into the complexities of human beings to better understand what complexities make them tick. To paint that colorful picture, we need to know what humans are doing, how they are doing it, and the logical and emotional reasoning behind it. 

As the market research industry evolves and researchers gain access to more advanced technologies, artificial intelligence (AI) can empower human researchers with the tools to be even faster and more accurate and is rapidly becoming a major game-changer. With its ability to provide an unprecedented scale of data collection and analysis, AI has tremendous potential to revolutionize the way market research is conducted. 

Today, much of market research is driven by technology with online platforms enabling virtual data gathering at scale. From survey design to insights generation, every step of the research journey stands to be impacted by AI. The speed, efficiency, and time to value that AI brings to the entire market research industry is invaluable, promising enhanced data-driven decision-making for businesses and researchers alike. 

This article will dive into AI trends in qualitative research and will demonstrate the monumental impact of embracing the leverage that AI can provide.

Virtual Assistants and Chat Bots 

Probably the most popular AI trends, virtual assistants and AI-powered chatbots are used for various things, such as answering customer queries, customer service-related tasks, online community management, and engagement across multiple industries. In addition, chatbots can conduct virtual qualitative interviews and quickly summarize and categorize the data.

Automated Text Analysis

Automated text analysis uses machine learning algorithms and natural language processing to extract, organize, understand, conceptualize, and consume knowledge to formulate meaningful insights from text data at scale. It works by taking large data sets and analyzing them to recognize patterns and topics, summarize them, and identify sentiment. Text analysis is beneficial to market research strategy because of the ability to quickly process numbers of feedback surveys and extract concise and valuable information. This AI trend will provide researchers with a faster and more efficient way to analyze large data sets with improved sentiment analysis and categorization accuracy. In addition, it offers the opportunity to identify trends and correlations in customer feedback so that organizations can make better, data-driven decisions. It can also uncover customer preferences and insights that may have previously gone unnoticed.

As an example, InnovateMR’s award-winning Text Analyzer™ software uses AI to examine survey participants’ open-ended responses in real-time. This technology allows InnovateMR to provide high-quality sample for clients, as all respondents must go through it before being able to complete a live survey. TextAnalyzer™ tests for common issues in open-end data, such as gibberish, spelling errors, deduplication, copy/pasting, bot scripting, and context to ensure genuine human behavior.

Automated Image Analysis 

Automated image analysis technology uses computer algorithms to process and analyze images. This technology extracts and classifies valuable information from images and videos, such as facial features, objects, shapes, color, texture, and motion, saving researcher’s and analyst’s time. Automated image analysis is used in various industries and applications, including facial recognition, medical imaging, surveillance, and manufacturing. For example, facial recognition systems could use automated image analysis to identify and classify an individual’s face and later use this information to identify that individual in a database. 

This AI trend can help researchers detect brand or product logos in images that consumers post online to track customer behavior, as well as identify occasions where consumers are likely to use their products and determine which products or services are most likely to succeed in the market.

Computer-Assisted Qualitative Data Analysis (CAQDAS) 

CAQDAS, or Computer Assisted Qualitative Data Analysis Software, helps researchers analyze qualitative data. Gone are the days of analyzing text and audio with a pen and paper. Instead, CAQDAS takes the heavy lift from analysis and enables researchers to identify patterns and relationships accurately and efficiently in data and then transforms that data into digestible visuals like graphics, tables, and diagrams. 

CAQDAS tools are beneficial in narrative analysis. For example, have you ever had a conversation that covered many topics before circling back to the initial point? Focus groups and interviews are similar, as respondents may have many caveats and anecdotes that they dive into before fully answering the question. CAQDAS tools can take those sometimes-extensive stories from interviews and focus groups and restructure them into concise on-topic narratives.

CAQDAS is not only used in market research but in a variety of sectors such as healthcare, academia, government, commercial, and non-profit agencies. In addition, this AI trend helps to reduce errors, as it can automate some of the more tedious tasks associated with manual analysis. Finally, it can help to provide more comprehensive and meaningful insights, as it can provide deeper analysis and visual representations of data.

Predictive Analytics 

Predictive analytics uses artificial intelligence with statistical tactics like data mining and predictive modeling to analyze historical and current data to predict future trends or events. Predictive analytics can help researchers identify potential opportunities and risks in the market and make better decisions. This technology is beneficial because it can help drive strategic and tactical decisions based on consumer behavior. 

Natural Language Processing

Natural Language Processing, or NLP, allows computers to understand and interpret human language. NLP analyzes customer feedback, survey responses, and text-based data to help researchers understand customer sentiment and make better-informed decisions surrounding audience targeting and messaging. NLP provides that qualitative understanding of their audiences’ intentions enabling organizations to create more efficient strategies and compelling content.

Sentiment Analysis 

Sentiment analysis or opinion mining is a process of analyzing and categorizing text by the sentiment it expresses and can help determine emotional tones in conversations. This analysis works through NLP and machine learning algorithms to determine whether the text is positive, negative, or neutral. Sentiment analysis in market research helps researchers to understand customer sentiment, identify trends, and quickly uncover insights about customer needs and preferences which can provide insight into customer behavior and reactions to products, campaigns, and services. By automating this process, researchers can quickly get through vast amounts of data. 

Sentiment Analysis can analyze feedback from different communication methods across audiences to determine the most effective. However, sentiment analysis is an upcoming AI trend that is still developing. As a result, the data isn’t always accurate and needs to be corrected occasionally, so it is vital to quality-check your data.  

The Future of AI in Market Research 

Don’t fear, AI won’t replace humans in traditional research. Empathy, compassion, intuition, and intelligence in research require a human element that AI simply cannot duplicate. However, AI can help us streamline and automate our processes to derive and analyze our insights faster and with improved reliability.

“Technology has liberated research and analytics to be able to handle massively bigger samples and sets of data, perform vastly more complicated tasks and inform much wider audiences than ever before,” according to ESOMAR, 2022.

AI has the potential to revolutionize the market research industry by providing scale that was previously unimaginable. AI can greatly enhance the speed and efficiency of data collection and analysis, leading to a quicker time to value for research projects. Moreover, AI has the power to transform every stage of the market research journey, from survey design and respondent identification to data interpretation and insights generation. As technology continues to drive the industry, AI will play a major role in shaping the future of market research, unlocking new possibilities and opportunities for businesses and researchers alike.

It’s time we embrace AI trends and allow it to do the heavy lifting so that we can focus our efforts on the feedback and strategizing  improvements.

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About InnovateMR – InnovateMR is a full-service sampling and ResTech company that delivers faster, quality insights from business and consumer audiences utilizing cutting-edge technologies to support agile research. As industry pioneers, InnovateMR provides world-class end-to-end survey programming, targeted international sampling, qualitative and quantitative insights, and customized consultation services to support informed, data-driven strategies, and identify growth opportunities. Known for their celebrated status in customer service and results, InnovateMR combines boutique-level service with extensive global reach to achieve partner success.