We’re sure it’s on your mind right now. And not just sitting in the back of it. But right there, at the forefront. Because it sure as hell is for us. AI in Market Research, of course. Whether you’re a client who buys research or you’re the one who conducts it, it’s everywhere, right? It’s filling your email inbox. It’s all over your Linkedin feed. It’s the topic of every conference and industry podcast, and it’s on every single agenda of every single meeting you ever attend. And you might be asking yourself…

So, is this it then? Is this the next age of marketing and brand research? Has our business changed forever or is this just a passing craze? Will I wake up tomorrow morning and see that AI was not all it was cracked up to be — tossed into a cultural bin like so many other ‘revolutionary’ tech advancements?

 

Here’s the thing

It doesn’t really matter what we think. Frankly, it doesn’t really matter what anyone thinks. AI is here… and it’s making some major waves.

So, the most important thing we can do right now as a strategic brand consultancy is… think really hard. Not about whether or not we use AI in market research (that ship has sailed)… but to think about how we can leverage AI to learn more about people. 

Because as dedicated explorers of human behavior, we wouldn’t be doing ourselves, or the brands we work with, any favors if we lost sight of the bigger picture. The bigger picture being… how AI can help make us better at what we do, and give our clients an even better outcome, if we’re thoughtful about what it’s good for and what it isn’t.  

But first let’s remember… 

AI is nothing new…

If you think it’s new, you’d be fooling yourself. From Spotify giving you personalized music recommendations, to Google Home or Siri recognizing your voice and managing your lights, to the customer service chatbots that try (and usually fail) to solve your issues before escalating to a human… AI tools have been part of all of our lives for years.

Similarly, AI in market research has been around for awhile. Prior to the release of ChatGPT and the explosion of AI apps in the past year, our industry’s platforms and tools have incorporated AI, such as automatic transcripts, sentiment analysis tools, or simply Google Calendar suggesting meeting times that work for all parties.

…but it has gotten a whole lot smarter

It’s smarter now, primarily because we have more data than ever before, which helps AI learn more about the world. Advances in algorithms and better computer hardware allow these AI systems to process information faster and more effectively. Additionally, new model designs, like those used in ChatGPT, are particularly good at understanding and generating human-like text, making AI more “human-like” in its communication. (Here’s a great summary of the state of AI today, if you want to get up to speed quickly!).

Think of it like this: The first iterations of AI were like a hammer—useful as a tool for certain tasks but blunt and one-dimensional. Modern AI, however, is more like a Swiss Army knife, equipped with various tools and functions that adapt flexibly to a multitude of scenarios and needs. 

AI now has the ability to ‘think’ about concepts, ideas, and their relationships, which means it’s incredibly more useful to the work we do as market researchers than ever before. 

So as a strategic brand consultancy, it’s critical we leverage AI in the work we do to create more of an impact on the brands we work with 

Actually, that’s a lie. It isn’t critical that we leverage AI in the work we do; it’s our responsibility. Not only to the clients we serve but to the people our clients serve. Here’s what we mean. Very simply, our job is to help our clients understand people. Because when clients understand people better, they can make better decisions about their brands. And how we get to those answers requires tools. The right tools. Whether that’s a particular process, a methodology, a set of best practices, or a specific platform, tools help us generate human insights. And to deny “a tool” because it’s new, or because we don’t quite understand it, or because frankly it makes us a bit nervous, is not very human (or smart) of us. 

So in other words, AI is another tool on the old tool belt. But it’s not just any tool…

 

AI is an empowerment tool 

As research consultants (and human beings), we have limitations. There’s only so much data we can process in our brain at once. There are only so many connections we can make. There is only so much we can accomplish in a certain period of time. But it’s nothing to feel insecure about. Because along with these limitations come great strengths. We can make abstract connections in data. We can relate people’s stories we hear in fieldwork to our own. We can change our minds and switch directions quickly. And most importantly, we can have deep, deep empathy for the people we study.

But wouldn’t it be nice if we had a tool that could help us strengthen our weaknesses… and even strengthen our strengths? A tool that we could choose to use to open up even more opportunities for learning? So we can see deeper, broader, and more quickly what is going on in the world. Well, we’re starting to. And that’s AI. Empathizing and connecting with human experiences can’t be fully automated or replaced by AI. But, we’re embracing AI in market research as an empowerment tool to boost our capacity to think deeply and creatively about human experiences.

Here’s a few ways we’re already doing this…

Enhancing Efficiency

We are using AI to streamline and automate routine administrative tasks, allowing our team to spend more time on higher-level strategic work… you know, the bigger thinking stuff.

  • Fieldwork Scheduling: Managing logistics across multiple time zones efficiently.
  • Pulling Quotes: Extracting pertinent quotes from transcripts to support our narratives.
  • Re-mine Assistance: Distilling secondary research reports and background documents into relevant data points.
  • Trend Support: Pulling relevant data, cultural trends, helping to identify emerging opportunities and inform strategic decision-making.
  • Preliminary Qualitative Analysis: Identifying preliminary themes from fieldwork, setting the stage for deeper human-led analysis.
  • Open-ends Analysis: Summarizing themes and sentiment from open-ended survey questions.
  • Standardization of Stimulus: Making sure that stimulus such as positioning territories or messaging concepts are standardized, maintaining a consistent “apples to apples” comparison for unbiased exploration. 

Augmenting Creativity

We use AI like it’s another brain in the room to develop ideas (and bounce them off), enhancing the creative process. And we’re often pretty impressed by what it can produce. 

  • Discussion Guide Development: Aiding in crafting comprehensive discussion questions that align with objectives and probe deeper into subjects of interest.
  • Mood Board Creation: Generating images and assembling mood boards to visually articulate concepts and inspire creative direction.
  • Survey Development: Generating additional survey answer options that we might not have thought of and optimizing question structure. 
  • New Product Ideation: Generating innovative product ideas within our opportunity areas and against guardrails, expanding the creative scope, and providing fresh perspectives.
  • Workshop Activity Design: Helping in developing engaging activities for workshops, enhancing participant involvement and creative output.

Elevating Deliverables

We use AI to improve the final quality and presentation of project outputs, making sure we deliver professional and polished reports that align with The Sound’s tone of voice.

  • Copy Editing and Proofing: Assisting in refining text for clarity, grammar, and style, ensuring error-free and impactful communications.
  • Image Generation: Creating imagery that expertly represents our insights and supports our storytelling. 

 

And you better believe, we have a lot of mixed feelings about it 

The truth of the matter is, we’re thinking and feeling our way through this just like you. On one hand, there’s a palpable excitement about the possibilities that AI brings to our industry. On the other hand, there’s this little (or at times big) voice inside of us that says ‘’Ah ah ah, take it easy now.’ 

Here’s the thing. If we’re using AI to form the questions and synthetic respondents to answer them, and then AI to analyze the results, report on the results, and draw conclusions from the results… the more we enter a space of robots talking to robotsand the more we risk losing the humanity of insight. 

We (and our clients) need to tread carefully. AI, at least at the stage it’s at right now, should be used to inspire answers, not answer them. Otherwise, brands risk making big and expensive decisions solely based on the results of these tools, and face big and expensive repercussions. 

 

So, we know we need to proceed with caution 

As we integrate AI into our workflows, we recognize that AI is not a simple plug-and-play solution; it’s a complex new technology that requires thoughtful integration. The capabilities of AI are promising, yet it’s crucial to understand that these systems cannot yet match the nuanced quality of human output in many respects. Therefore, we’ve created some healthy boundaries for ourselves, or a set of guiding principles that our team follows, to ensure AI is implemented responsibly and effectively.

Complement (Don’t Replace) Human Insight

Yes, AI can understand ideas and context more than ever before, but it is very far from replacing human market researchers and strategic brand consultants. It’s great at processing and summarizing large datasets, but it struggles to uncover deeper insights, which requires fully capturing the nuances of human behavior, cultural context, body language, and local nuance. Additionally, while AI can automate routine research tasks, it lacks the human intuition, emotion, and creativity essential for generating innovative ideas, exploring new territories, and uncovering hidden opportunities. 

So: We will delegate certain parts of our process to AI when it makes sense (like the examples above), but we certainly won’t be using AI for the sake of using AI, even when some platforms promise to do all aspects of our jobs. The whole point is to free us up to have more time to be strategic and creative, not have AI badly attempt to do those things for us.

Don’t Blindly Trust the Algorithm

At best, AI for market research probably isn’t going to do as good of a job as a human for many tasks. As of now, the data set it’s drawn from is mostly written language, not verbal. That means it’s missing all the wider real-world context drawn from actual behaviors and the full sensory experience of being a human. Being largely sourced from online data also perpetuates hidden biases in terms of having a younger, male, and US-centric skew.

At worst, AI makes shit up. The hallucination problem (where AI very confidently tells you something that sounds plausible, but is entirely made up) hasn’t been solved yet. Plus, many of the current tools draw their knowledge from past data (e.g. ChatGPT is trained on data before 2023) and may not be aware of current context.

So: For every tool we adopt, we will run an experiment (without the flasks and beakers) where we humans perform the task (e.g. identifying themes from transcripts), and AI performs the task, and we compare results. That way, we can get a sense of which tools do a good job (we’ve certainly encountered some that don’t) and what the strengths and weaknesses of each tool truly are. 

Train Teams Thoroughly 

Just like with any new technology, it’s necessary to develop new skills to be able to use AI in market research. An AI tool is not going to magically think like The Sound. We’ve learned from AI experts that we need to think of AI like how we would think of briefing a new employee or a new team member on a project, to maximize the results. Prompt engineering in particular is key to quality of output and usability… and AI can be frustrating for people to use if they don’t know how to “talk to it”.

So: We’re facilitating tutorials and workshops to train our team members to feel comfortable using AI tools and get the most out of them. And we follow up with them regularly to ensure this is happening. 

Commit to Continuous Experimentation

AI in market research is constantly evolving. We may adopt one tool and then 3 months later, a much better tool comes out that does the same thing and more! 

So: We commit to continuously researching what’s out there and trying out new tools. Several team members are on our AI task force with this mandate. And after testing quality (AI vs. The Sound, where we review tools, is part of our weekly company-wide meetings now), we roll out tools for the whole team to use. 

 

So where does this leave us then? 

Well, right where we started… continuing to think really hard about how we can leverage AI in Market Research (the machine!) to learn more about people (us). 

So yes, we have a responsibility to use AI in the work we do. But we need to make sure we use it responsibly: using it as a bridge, not a barrier, between brands and the real human experiences they seek to understand. 

Striking this careful balance allows us to remain at the cutting edge of market research innovation while ensuring that our human insights remain deeply human.

So, what can us humans (and AI!) do for you?

 

 

clea awkward childhood photo
Written By:
Clea Stone Monsurate

Clea has always been fascinated by human behavior, especially our relationship with technology. For her college thesis, she produced a documentary video installation about Death on Facebook. At The Sound, she leverages her background in marketing, social psychology, and film to bring consumers to life and develop actionable insights for her clients in diverse industries all over the globe.

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