Leveraging AI to Assist Market Research: The Human Touch at the Core

It is a well-known fact that artificial intelligence (AI) is reshaping the landscape in market research. But here’s the thing: while AI is an incredibly powerful tool, it isn’t a magic wand. AI is not something that should drive us; it assists rather like an intern. It can be a great help, but you still have to give a careful brief and check the work thoroughly. It makes research faster and easier without compromising human intelligence at its heart.

The focus on AI should be on speeding up time consuming tasks, therefore allowing researchers to focus on what truly matters – drawing meaningful insights from complex data. Whether it’s analysing qualitative interviews or pulling patterns from massive datasets, AI helps to dive into the detail faster, enabling agility during projects and supporting compelling stories based on data.

There are so many tools out there, which are developing rapidly, it’s hard to keep up with what’s good and useful in the market. So, here’s a look at some of the AI tools we have discovered – not everything is what they claim to be – we want to share with you what we have learned and found useful. We hope these learnings will save you time, help you be more efficient, and empower you to deliver AI assisted research without losing the personal touch.

AI helps us improve the management and initial analysis of qualitative data. Traditionally, analysing qualitative interviews or focus groups is a very time-intensive task. Platforms are designed to assist researchers in analysing qualitative data more efficiently, serving as a tool for summarising, tagging, and extracting key insights from various types of research materials, such as text, video, and audio.

Our approach is to use AI to help us get to insights faster, without losing the human touch. AI can be seen as a springboard, to get us off the ground and kickstart the time-intensive initial analysis, and allow our experienced technical researchers to find the golden insights.

We also think AI has a great place for handling quick, automated transcriptions and summaries of meetings or interviews. You can now record, transcribe, and summarise sessions at the click of a button, making them especially useful for projects that require immediate, digestible insights.

There are lots of simple yet powerful platforms out there, offering the ability to search transcripts by keywords, identify recurring themes, and jump directly to specific sections of the audio or video. We think they are particularly handy for small projects where rapid data turnaround is essential.

While not all platforms offer the depth of analysis that others provide, it depends on your needs. Some are perfect for quick and easy transcription and data extraction, while others require more investment and are better able to understand themes and emerging insights in data.

As with all AI, whether it is being used for a simple or more complex task, outputs should be double checked be a human to validate. Context, emotions, and creativity which are so critical to impactful insights, cannot be achieved through AI.

AI also is useful in presenting data in creative and striking ways! AI-image generation tools work by generating custom images based on data and insights inputted. We can use AI to transform words and themes into vivid imagery that visually represents the essence of a brand or product.

An example we love, is using AI to generate mood boards based on consumer feedback. These can include colour schemes, product associations, and other sensory elements, creating a compelling visual representation of products and brands at the click of a button. This unique application of AI not only enhances presentations but also helps convey complex insights in an accessible way. Moreover, we have found some platforms have embedded AI chatbots to help refine search criteria, ensuring the images align perfectly with the insights that are presented.

Understanding implicit reactions and emotions to products and brands has always been tough. AI is helping drive the field forward by sophisticating algorithms in tools like facial coding, using advanced AI-assisted algorithms to analyse micro-expressions, as well as automation of previously manual processes such as head movement compensation and training. This means you can get under the surface of true emotional reactions quicker and make it more accessible.

Automating the coding of open-ended survey responses is another great example of AI for good, allowing us to process large datasets quickly, assigning themes and sentiments to thousands of responses in multiple languages – something which previously took a long time!

AI is also integrated into coding platforms to help us to learn from previous inputs, improving coding accuracy over time. Whilst it is critical to maintain human oversight to ensure the quality of the coding, AI helps us accelerate the process, allowing more time to focus on drawing meaningful insights from the data. It’s a game-changer for projects that involve open-ended feedback, turning what could be weeks of manual coding into just hours of review.

While all these AI tools offer significant benefits – speed, scale, and enhanced creativity – they do not replace human intelligence. AI helps to manage the data and perform tasks faster, but the real value comes from how we interpret and contextualise those insights. By maintaining human oversight and critical thinking, we ensure that the insights we deliver are not just efficient but also relevant, actionable, and nuanced.

AI may be the springboard that accelerates our work, but it’s our team’s expertise that ensures we deliver your project with precision and excellence. At the core, we are an expert R&D insight agency powered by human intelligence – AI simply helps us do it a bit faster.

If you’d like to learn more about the AI tools that we use as an apprentice to deliver exceptional research, please contact Hannah Over by email at [email protected]