Qualitative Market Research Trends to Track in 2024

As we welcome 2024 and all its possibilities with open arms, we thought now would be the perfect time to explore some of the trends — current and emerging — we believe will have the biggest impact on qualitative market research. Let’s start with the trends we see as gaining momentum in the year ahead.

Digital Qual Research Continues to Dominate

Ushered in by the pandemic, digital qualitative research is now the new norm — and will continue to be so in 2024 and well beyond. Survey findings show that 87% of researchers did over half of their qual research online in 2023, with 85% of them saying they’ll continue to do so over the next 12 months.

We go into the pros (and cons) of remote focus groups and interviews here, but the bottom line is this: digital research can help companies expand their reach of respondents more easily, conduct interviews more quickly and conveniently, while saving resources and money. Digital research extends beyond online focus groups, as well. In 2024, we expect researchers to keep using digital tools for all manner of activities including surveys, social media listening (more on that below), online discussion forums, data-mining, and more.

Smart Use of Mobile Market Research

Mobile devices are a key part of the digital conversation. Smart phones are ubiquitous; in 2023, 92% of Americans owned a smart phone, and spent around four hours a day on these devices. Researchers have realized that mobile phones provide an excellent platform to engage with respondents who are perfectly comfortable communicating via screens, taps, and swipes.

There are advantages to mobile phone research, starting with a low barrier to entry. Respondents don’t have to be at a specific place at a certain time to participate in a mobile-based interview or focus group, respond to a survey, or provide in-app feedback. They can just whip out their phones on the spot to provide in-the-moment, real-time reactions.

Respondents can also share responses in a wide range of ways — via text, voice messages, video, emojis, and even gifs. Mobile devices also allow researchers to conduct location-based research (thanks, GPS), as well as ethnographic research via daily video journals and notes apps. As such, we expect the mobile research trend to continue building steam.

More Social Media Research

The use of social media is also part and parcel of the shift toward digital qual market research. Researchers have already been using social media as a platform for asking questions, conducting polls and surveys, soliciting feedback, testing concepts and messaging, and showcasing prototypes. With Americans spending around two hours a day on social media apps, these platforms are an obvious place to find and connect with respondents.

In 2024, we predict advances in technology will make it easier and more attractive for qual researchers to embrace social media listening for sentiment analysis. There’s a growing list of shiny new tools that enable researchers to track keywords, hashtags, mentions, reviews, and sentiment across multiple social media platforms. Tracking this info can provide valuable insight into emerging trends, unmet needs, consumer preferences, and brand perception.

Ethnographic Research for B2B

Ethnographic research that’s immersed in the actual real-world environments where respondents live, work, and play has been around since the 1950s. So while it’s long been a staple for consumer research, we believe ethnographies offer great potential for B2B research as well — particularly in the field of technology.

We’ve recently tested out this theory ourselves, by using an ethnographic approach with one of our technology clients. For this particular study, we had respondents — specifically, software engineers — take over and physically use our moderator’s computer to play around with an application and provide real-time feedback. The insight we gleaned from this exercise was invaluable, and our clients were thrilled with the results.

Emotion Recognition and Neuromarketing Research

Emotion recognition technology uses algorithms and machine learning to identify and classify micro facial expressions that signify joy, sadness, surprise, fear, anger, disgust, contempt and more. Neuromarketing research takes it a step further, employing medical procedures including functional magnetic resonance imaging (fMRI) and electroencephalograms (EEG) to track and measure physiological changes in the brain to indicate and identify emotional responses.

Emotion recognition and neuromarketing research aren’t new concepts; some of the largest market research firms even have their own in-house labs set up for these kinds of studies. And if you don’t have the budget for these methods, there are lower-cost and less obtrusive devices that can track and measure a participant’s heart and respiration rates which indicate an emotional response as well.

With the emergence of AI, it will be interesting to see where these types of research approaches will go. AI-enabled eye tracking, for example, maps out eye gaze and movement to understand where a person is looking, what they’re looking at, where their gaze lingers, as well as pupil dilation (an indication of arousal). This is definitely a space we’ll be keeping our eye on.

Merging Qual and Quant

We’ve seen an increased need for and openness to a hybrid research approach that combines qualitative and quantitative, and we expect this merging to continue in 2024 and onward. And we’re here for it.

While they may seem diametrically opposed, quant and qual together can strengthen each other while providing a more holistic view of the research. Quant alone can get bogged down in data, making it harder to connect the dots and reveal the insight. Qual, on the other hand, can sometimes be hard to measure, with a lack of quantifiable “proof” to clarify how conclusions were drawn.

Integrate the two research worlds, and you have the what, why and how behind the data. This can result in more meaningful reports that also provide clients the proof-points they need to believe in the insight. Advances in technology and systems are making it easier for researchers to combine qual and quant data in a single platform, which also make it faster and less cost-prohibitive to do both.

A Case for Agile Market Research

Agile market research has been around for a while, as well, and there’s been some debate as to its effectiveness as a methodology. We see the increasing value of agile market research, but also the need for it to be done exceedingly well.

In the current business reality, things change very fast. As such, companies need answers to their questions now, which means they need quick, focused research studies and lots of them. Agile market research responds to this demand by taking an iterative approach to gathering consumer feedback to very specific questions along multiple points in the development of a product, service, or campaign.

Instead of taking weeks or months to test and collect respondent reactions, agile market research delivers answers in days. This allows companies to make on-the-fly tweaks as they go, and ideally launch their product/service/campaign more quickly.

In the hands of an inexperienced firm, agile market research can end up sacrificing quality for the sake of speed. That’s why it’s important to have researchers with first-hand industry knowledge and experience, who know exactly the right questions to ask and how to extract the critical insight quickly.

Now that we’ve addressed some of the current trends, let’s turn our vision toward those we see emerging in the year ahead.

AI As a Collaborative Tool

There’s no doubt that artificial intelligence will play an increasingly larger role in qualitative market research. We expect more research firms to embrace AI technology, apps, and services as a collaborative tool to help them drive efficiencies and productivity. A recent Qualtrics survey supports this, finding that 46% of researchers say they’re “very confident” with using AI in research, and 26% reporting they feel “extremely confident.”

We predict a turn toward AI for a broad range of research activities, from developing screeners, surveys and discussion guides, to weeding out bogus or unqualified respondents, to transcribing interviews, to quickly analyzing massive amounts of data from multiple sources, to generating attractive and compelling reports. But we caution that AI should not and cannot replace the human element when it comes to revealing actionable insights that businesses need to make strategic decisions. You can read more about that in our recent blog post here.

Prioritizing Data Privacy

All the hype about AI leads us to the next emerging hot topic for market research: data privacy, for both consumers and clients.

Today’s consumers are ever-more aware of and concerned about protecting their private data — especially online. According to Pew Research, 72% of Americans believe that almost all their online activity is being tracked, which understandably makes them uncomfortable. It can also make them less willing to participate in qual research studies.

In response to rising fears around data privacy, countries around the world are enacting stricter guidelines designed to protect personal information and give consumers more control over their own data. Moving into 2024, researchers need to be aware of and respond to the concerns of consumers as well as the compliance requirements of their governments. That means having clear and formalized data security protocols in place, as well as complete transparency on how data is collected and used.

Researchers will also need to take measures to protect themselves and their clients against malicious actors. GreenBook reports that upwards of 30% of market research qualifies as fraudulent, propelled by respondents who lie about their qualifications, bots and fake traffic completing surveys, and widespread identity theft. As such, it will be critical for researchers to implement robust safeguards from here on out.

We delve deeper into safeguarding data in our recent blog post here.

Let’s Hear it for Voice of Consumer (VoC) Research

Modern VoC research involves using technology and tools that analyze text and consumer sentiment across a range of digital and traditional channels and methods including surveys, interviews and focus groups, social media, feedback forms, online reviews, customer support interactions, customer journey mapping, and more. The goal is to capture what customers are saying about your product, services, and/or brand for authentic insight.

We expect VoC research to gain traction as companies continue to place an emphasis on customer experience and customer-centric strategies. VoC also plays a key role in developing customer personas that help companies better understand and respond to different audience segments.

VoC research, however, can be challenging and complex since it requires an omni-channel approach and sophisticated tools in order to reveal the complete picture of customer preferences, sentiment, and behavior. It’s also important to make sure the VoC data you collect truly represents your target audience, and that you maintain customer privacy and data security.

Diversity and Inclusion in Market Research

In 2022, 44.1% of the U.S. population was non-White. By 2044, over half of Americans is projected to belong to a minority group. The percentage of Americans who identify as LGBTQ+ is growing as well, especially among younger generations; in 2022, 10.5% of Millennials in the U.S. identified as LGBTQ+, while 20% of Gen Z did.

Our country’s population is aging, as well, with the median age coming in at just under 40 years — a number that’s expected to rise. Even as we get older as a country, younger generations are gaining power as consumers. Millennials now represent the largest group of consumers, and Gen Z’s buying power is going up.

All this to say: in 2024, it will be imperative for researchers to make sure their research samples and respondents reflect the diversity of their audiences — including ethnicity, cultural background, lifestyle, gender, age, and sexual preference. It will be especially important to include traditionally underrepresented populations such as women of color, people with disabilities, and members of the LGBTQ+ community.

Focus groups comprised of respondents who have similar experiences, preferences, and biases can often lead to skewed results. We get it: sometimes you need to find respondents who check off specific attributes — a certain age group, profession, demographic. But within the confines of the screener, and whenever possible, diversifying your groups and interviewees can help reveal richer, deeper insight that leads to better decisions.

Diversity and representation are an even bigger challenge when we consider how difficult it’s becoming to find respondents. Today’s consumers are increasingly likely to ignore phone calls, emails and texts from unknown sources, including field managers trying to recruit for research studies. Which leaves only those self-selecting consumers to respond and participate — and who often lack diversity. To address this challenge, qual researchers will need to lean hard into relationship-focused recruiting.

Beyond diversity, researchers must also work to ensure inclusivity with their studies. That requires creating environments where every participant feels listened to, valued, respected, and involved — regardless of who they are.

What Did We Miss?

Call us optimists (we certainly embrace that title), but we’re excited about the emerging tools, technologies, and methodologies researchers can leverage to unlock even greater insights that drive tomorrow’s innovations. As is the nature of our industry, we’re sure this list will continue to evolve as the year advances, and we’re curious to see what develops. We’d also be interested to hear about any trends you’d add to the list. Reach out, and let’s discuss.

9 Tips for Using AI Safely in Market Research

There’s been plenty of hype around Artificial Intelligence (AI) and how it’s going to transform our world — including the world of market research. What’s lacking is practical guidance for using AI in our daily work as researchers. For the next series of Thinkpiece blog posts, we’re focusing on less hype-ful and more helpful AI insight.

For the first of this series, we’re sharing our top tips for using AI safely. True, AI offers the potential to help make research more efficient and effective. But AI technology also comes with a host of potential risks, particularly when it comes to data protection and privacy. After all, AI apps are designed to collect as much information — including sensitive info — as possible to keep learning and becoming “smarter.”

Before you invest in that shiny new AI app or tool, here are nine basic safety practices to keep your, your clients’, and your respondents’ data secure and protected.

1. Choose Your AI Apps Wisely

Before you start using any AI app or tool, take some time to research the company behind it. You’ll want to make sure the developer is legitimate, offers good customer support, and has a solid reputation particularly around security.

Avoid fly-by-night and sketchy apps, and do some digging into the tools you’re considering. Check out the company’s portfolio to see what they’ve done before, and the quality of those products or services — keeping a lookout for any bad press or reviews. Make sure the company is well versed in the latest AI and machine learning frameworks, and is clearly an expert in the field. Last but not least, scrutinize their commitment to security (see tip number 3).

2. Don’t Overshare

Assume that any data you share with an AI app will be used to improve its machine learning — and is at the mercy of the app developer. Which means you should also assume that this data is vulnerable to breaches.

To that end, avoid sharing any personal, confidential, or sensitive data — especially your clients’ or respondents’ info. For example, any proprietary client information, such as a new product that’s being held under wraps, should definitely not be shared with any AI app or tool. A general rule of thumb we follow: if you don’t want it blasted on social media, don’t share it with an AI app. And if you come across AI-generated content that requests sensitive information, run the other way.

You might also want to invest in additional security tools designed to prevent oversharing of confidential and sensitive data. LLM Shield, for instance, prevents language learning machines (LLMs) like ChatGPT from leaking your clients’ or respondents’ personal or private information.

 3. Peruse the Privacy Policy

Reading the fine print may be a pain, but it’s important to know what you’re signing up for. So be sure to peruse the privacy policy, terms, and conditions for any AI app you’re thinking about using. This will let you know how the app plans to collect, store, protect, and use any data you share with it.

As previously mentioned, most apps use the data you share to make it “smarter.” But the app’s developers may also be exploiting data for other purposes, such as selling personal information to third parties who want to completely freak you out with personalized ads. The app’s privacy policies should give you confidence that the developers won’t do anything dubious with your data and are taking thorough measures to protect your info from hackers.

4. Customize Your Security Settings

After carefully reviewing the app’s privacy policy and deciding you’re comfortable with it, don’t stop there. Go into the app’s privacy and security controls and change any settings to meet your preferences.

For example, the app may give you the option to have data automatically erased after a certain amount of time, or you may be able to choose to delete the data yourself manually. You might also be able to review and erase search histories and clear conversations to delete anything you and the AI app might have “chatted” about.

5. Train Your Team

It’s a good idea to formalize your own security policies and practices for using AI apps and tools, as well. Guidelines can cover a wide range of topics, including how the app should be used in alignment with your or your clients’ values; complying with laws related to data privacy; identifying and addressing potential AI biases; reducing risks of exposing or mishandling sensitive data; the role of humans in ensuring AI app safety; and steps to take in the event of AI-related errors or disputes.

Train your team and anyone who will be using the AI app on these policies, practices, and guidelines to make sure they’re understood and followed.

6. Keep Up with Compliance

It’s a good idea to familiarize yourself and any other users on your team with current compliance and regulatory requirements around the use of AI. The Health Insurance Portability and Accountability Act (HIPAA), for example, enforces strict guidelines around protecting patient information and privacy which might easily be violated using AI. If you’re conducting research in Europe, you’ll want to be aware of any potential General Data Protection Regulation (GDPR) issues when using AI tools.

Compliance and regulations around the use of AI are ever evolving, so it’s important to stay on top of these changes to protect yourself as well as your clients and respondents.

7. Follow Good IT Security Practices

The growing prevalence of AI makes robust IT security protocols and hyper-vigilance even more critical, now that the area of attack is much larger. Keep employing the usual security best practices, such as creating strong passwords for all apps and websites, making sure all your software is up to date with the latest versions, and employing reputable anti-malware and anti-virus software.

This last point is especially important since it’s now possible to create malware that observes what you enter into an LLM like ChatGPT and then sends that information to a malicious actor for the purpose of stealing sensitive data. It’s also possible to use prompts engineered to “hypnotize” or trick an AI tool into doing things it normally wouldn’t, such as compromising the user’s data or producing incorrect or malicious responses.

These hypnotized AI apps can be used in phishing attacks to steal data from a user who thinks they’re interacting with a reputable source. Following good IT security practices will help protect you against this new crop of AI-enabled hacking.

8. Remember: AI Isn’t Perfect

Far from it, in fact. AI algorithms are subject to bias, which can lead to inaccurate, unfair, and even offensive results — all of which we definitely want to avoid in market research. Case in point: you might have read about the New York-based law firm that used ChatGPT for legal research and submitted a filing that referenced six completely fabricated legal cases, complete with bogus decisions, quotes, and internal citations — putting the firm in legal jeopardy as a result.

Which is why it’s critical that you don’t rely or make decisions based on AI alone. Have an actual human review, vet, and confirm any content or results generated by an AI app — paying close attention to potential inaccuracies, prejudices, or outright lies.

9. Just Keep Learning

One lesson we can glean from AI: the more we learn, the smarter we get. If you’re interested in leveraging AI for market research, we recommend learning as much as you can about the subject before you invest in and start using any AI tools or apps.

One good source of knowledge is Amazon, which recently launched its “AI Ready” initiative with free courses that teach you how to use generative AI (GenAI) to create text, images, and other media. Think ChatGPT and DALL-E. We just completed Amazon’s Generative AI Learning Plan for Decision Makers course, and recommend it for anyone interested in understanding more about using GenAI in their organizations.

You can also schedule a no-cost tutorial session with our in-house AI expert and Director of Technology Research, John Dibling, and download our free resource guides including “Understanding AI & Why It Matters for Market Research” and “8 Tips for Using ChatGPT in Market Research” here.

While one of the aims of AI is to simplify our lives, in reality it’s added a lot of complexity. And that complexity is constantly changing. We’re here to help you safely leverage AI as an effective, collaborative market research tool — human to human. Let us know if you have questions or are looking for more guidance.

Remote Vs. In Person Focus Groups: Is One Better Than the Other?

There’s no question COVID has changed the world of work. One of the most obvious shifts is the significant number of people who continue to work remotely at least part of the time. According to a recent McKinsey study, upwards of 25% of workforces in advanced economies work from home between three and five days a week — representing four to five times more remote work than in pre-pandemic days.

The qualitative market research workforce is no exception. Not only are more researchers working from home, but they’re doing more focus groups and interviews remotely as well. Research from Take Note, an interview transcription service, tells us that around 93% of market researchers are using online and video focus groups more often than they were three years ago. Which makes complete sense. During the pandemic lock-down days, market researchers were forced by necessity to move their studies to online platforms like Zoom.

The question now is: will focus groups continue to be conducted remotely — and should they? The answer to the first part of that question is, without a doubt, yes. The answer to the second part, however, calls for a deeper exploration of the upsides and downsides of virtual interviews and focus groups. So let’s dive in.

Jettison the Jetlag

Clearly, the most compelling advantages of remote research studies are convenience and flexibility — for all parties involved. With a virtual group or interview, there’s no need for the respondents, moderator, or client to travel, when all you have to do is pull up a chair and turn on a computer. While avoiding airport hassles and jetlag, clients can still view remote focus groups and interviews behind the scenes and provide feedback or direction to moderators in real-time. Less travel time also means lower costs for the client — with no plane tickets to purchase, cars to rent, hotel rooms to reserve, or per diems to dole out.

Remote interviews and focus groups also make it easier to reach and attract a wider geographic range of respondents while also simplifying the scheduling (and field managers love that). For instance, we found it much easier to get a larger size of respondents for an online group — easily finding 50, when we were originally targeting just 30.

Distraction-Free Zone

Remote interviews and focus groups can also provide a more distraction-free setting that allows both respondents and moderators to stay focused on the topic at hand. After all, there are no windows to stare out of, no thermostats blasting freezing air, no neighbor in the next seat to annoy you with the weird way they suck their teeth.

That being said, online respondents can also get distracted by what’s going on around them at home — a toddler crying, a dog barking, a delivery person knocking. So even with remote groups, it’s important to minimize disruptions as much as possible by making sure respondents have set aside the dedicated time and space to focus solely on the discussion.

Remote or In Person? Great Question.

For pure practicalities, we find remote interview and focus groups a great option when respondents are scattered across multiple states. Virtual platforms are particularly well suited for our B2B respondents, including software engineers, technologists, and clinicians who are comfortable with online meetings. Offering a remote option can also make it easier and faster to replace respondents on the fly when one doesn’t show or drops out.

We find that remote interviews are ideal for respondents who prefer to retain their anonymity, since they don’t have to reveal their face or name. However, when the topic being discussed is of a sensitive nature, an in-person moderator who displays empathy, compassion, and strong listening skills can be more effective than a talking head inside a square on a screen.

 Consider the Respondent

Remote platforms may be the preferred option for one-on-one interviews that require drilling down into complex subjects with high-level professionals who have incredibly busy schedules and limited time. For example, we typically conduct our interviews with physicians and clinicians online, and find the remote set-up works best for discussing complicated medical procedures, products, and research that require the focused attention of moderator and respondent alike.

On the other hand, certain consumer respondents — such as older patients — seem more comfortable with in-person settings. These types of groups tend to respond better to the reassuring physical presence of a skilled moderator who can guide the discussion with compassion and care.

For respondents, like our hypothetical older patients, an in-person setting may also make them feel more relaxed and at ease. While a screen can create a sense of distance and remoteness, in-person groups and interviews may feel less formal and structured. Respondents who are inclined to give truncated answers in a virtual setting like Zoom may be willing to talk more freely and openly in person. This in turn can further the conversation and lead to deeper insights. It can also be easier for moderators to see and read respondents’ facial expressions and body language in person versus online, which can provide additional shading, insight, and guidance in steering the conversation.

Controlling the Group Dynamic

It’s also important to consider the group dynamic of the respondents participating in the study. As any moderator can tell you, there’s generally one or two people in every group who tend to dominate the discussion, while others may be too intimidated to contribute and thus fade into the background. You may also have respondents whose strong, outspoken emotional reactions overly influence the responses of other participants. Every group dynamic is different, and it’s up to the moderator to make sure one single person isn’t monopolizing or skewing the conversation.

To that end, moderators will want to consider which platform puts them in the best position to steer the group dynamics in order to get the most complete, in-depth, and representative insights from all respondents. Some moderators feel they’re better able to do this in person, while others may find a virtual group (with less interplay between the respondents and access to a mute button) allows them to more easily exercise control and make sure everyone has a say.

Testing Concepts and Technical Know-How

In our experience, in-person settings often work best when testing messaging, concepts, and creative visuals. Sometimes, there’s just no substitute for having a physical board or document to put in front of person, without the barrier of a screen. That’s not to say you can’t present concepts online (we’ve done our fair share of that as well), but we find we often get more extensive and genuine responses when we do this work in person.

When deciding on remote vs. in-person, it’s also a good idea to consider the technical know-how and comfort levels of the respondents when it comes to remote platforms like Zoom. The last thing you want is a flustered respondent who can’t get their mic to work or figure out how to turn on their camera.

The Final Verdict? Be Good at Both.

So back to our original question. Yes, we believe that remote focus groups and interviews are here to stay, and that’s a good thing. Virtual platforms can make it easier and more cost-effective for researchers and clients to find, reach, and recruit a wider range of respondents. Given the challenges around recruitment, any advantage is welcome.

But we also believe there is still a time, place, and need for in-person research studies — and that there will continue to be so. So rather than picking one over the other, we recommend seeking out research partners who embrace and excel at both. Your research partner should also understand which option will generate the best results and insights based on the topic, the respondents, and the client’s goals, and make recommendations accordingly.

We’d love to talk remote vs. in-person with you to see what your experience has been. Reach out to continue the conversation.

To Get from Findings to Insights, You Need an Actual Human

With all the buzz (and, in some cases, panic) around artificial intelligence (AI), we thought it would be a worthwhile endeavor to examine the impact of AI on a subject near and dear to our hearts: qualitative market research.

As researchers, should we be warily eyeing AI with suspicion? Could AI eventually replace us carbon-based lifeforms when it comes to gathering and distilling research (once it’s done taking over the planet, of course)? While the continual evolution and emergence of AI will no doubt have a significant impact on how market research is done, we may be focusing on the wrong questions.

Instead of asking: “Will AI make us obsolete as researchers?” — let’s reframe the query. What we should be asking ourselves is, “How can we leverage AI to be even better at what we do?” In other words, rather than panicking over AI, let’s plan and prepare for it as a collaborative tool in the hands of people who know how to use it.

Findings Vs. Insights, Humans Vs. AI

Our deeply felt belief is that AI will not, should not, and cannot replace humans when it comes to qualitative market research that delivers real, meaningful value to clients. Here’s why. As a tool, AI offers tremendous potential in helping researchers uncover, gather, organize, and present research findings with greater speed and efficiency. But it takes a human with a specific set of expertise, an understanding of why people behave the way they do, and — perhaps most importantly — empathy to translate those findings into actionable insight.

Before we go any further, let’s take a moment to clarify the difference between findings and insight — because, while related, they are not one in the same. Findings refer to the facts or cold, hard data that are discovered during the course of the research. A finding could be shared by a respondent you’re interviewing one-on-one, voiced by a participant in a focus group, or observed by the researcher. “This respondent preferred concept A over concept B,” for example. That’s a finding.

Insight goes a layer deeper than a finding, to reveal an unspoken truth, belief, or reality supported by the facts or data. While findings focus on the “what,” insights illuminate the “why,” allowing us to better understand what motivates that hypothetical respondent to prefer concept A over concept B. This information is invaluable in helping clients make decisions and move forward with greater confidence.

As researchers we need to get past the findings to explore those insights that provide true value and direction our clients can act on. This process takes time and imagination, which is why we need humans to lead qualitative research, no matter how advanced AI technology gets. More precisely, we need humans with a particular set of skills, talents, and experiences. Let’s dive into that a bit more.

Speaking the Language

Ideally, the human leading the qual market research should bring first-hand experience relevant to the subject at hand — something AI simply can’t provide. Yes, AI can scrape the vast universe of data and “learn” how to mimic an industry-specific expert, but there’s no substitute for in-the-trenches, hands-on experience.

We’ve found this to be particularly true with the research projects we’re involved with, which typically center around complex challenges and questions in the fields of healthcare, technology, and finance. Because our researchers started in these very same fields (as software engineers, clinicians, and fintech brainiacs), they don’t have to “learn” the language of the industries they’re researching; they’re already fluent.

This industry-insider advantage also means our researchers know how to connect with the respondents they’re interviewing (often other clinicians and technologists) in an authentic, peer-to-peer manner. This level of trust and understanding leads to better questions, more meaningful conversations, more relevant findings, and yes, deeper insights.

Understanding Our Fellow Humans

There’s one other area where humans excel and AI flounders: understanding people — the way we think and feel, the reasons we make decisions and have certain preferences, the motivation behind our behaviors. As much as AI can sound like a human, it simple doesn’t know what it means to be human — the desires, fears, wants, and needs that drive us. And thus, it lacks the capacity for understanding human behavior that is so essential to revealing truly impactful insight.

People — being people — already have a basic understanding of what it means to be human. But when it comes to turning findings into insights, it helps to have a researcher who is fluent in sociology and human dynamics. This added layer of expertise enables the researcher to delve beyond industry-specific language and pick up on what is often unarticulated. So for example, even if a respondent may not precisely know why they selected concept A over concept B, a researcher with a sociology or human behavior background can often uncover the motivating factors and share this critical insight with the client.

The Element of Empathy 

Perhaps the most important quality unique to humans, and absent in AI, is empathy. In the world of qualitative market research, being able to empathize is key to making the leap from findings to insights. That’s where researchers who come from the industries they’re researching have another advantage.

A researcher who is a former nurse has sat by the patient’s bed and walked the hospital halls. As such, she has the capacity to empathize not only with patients and their families, but with the clinicians who care for them and the companies innovating the drugs and devices to treat them. A researcher who burned copious amounts of midnight oil as a software engineer in a previous life will be able to empathize with CIOs, IT staff, and developers as well as the people using their technologies and products. What’s more, researchers with industry experience will have empathy for the client who seeks answers to challenging problems and is faced with difficult decisions that have a direct impact on the success of their company.

Applying Insights to Brands

If you’ve seen this horrifying AI-generated ad for a pizza delivery service, you’re familiar with the limitations (more like aberrations) of artificial intelligence when it comes to branding. And while AI is getting smarter with every passing day (hey, it can even recreate human-like hands now), it’s still a long way from winning any Clio awards.

For that, you still need creative, brilliant, brand-savvy humans. In the qual market research world, researcher may tend to overlook branding — being so wrapped up in the findings and insights part of it. But we would argue that branding is the natural progression of market research; that’s where the insight ends up getting implemented in messaging, concepts, creative, and campaigns. You need that human researcher who is able to not only reveal and articulate the insight, but demonstrate how that insight can be used to build resonant, effective brands that connect with — you guessed it — real, live people.

Collaborating with AI

The debate around findings vs. insights is a fascinating one. But at the end of the day, for researchers it’s really all about getting results our clients can act on. Findings without insights are just facts; interesting, yes, but so what? Insights without implementation are just reports that sit on a shelf in someone’s office, gathering dust.

As expert and empathetic researchers, we have a responsibility to our clients to deliver outcomes they can act on. That involves analyzing, collecting, and presenting the data and insights with a clear strategic direction. And that’s where AI can help. There are a wealth of AI tools and technology — with more immerging daily — that researchers can leverage to be more efficient, productive, wide-reaching, and accurate in how and where we collect data.

AI tools can help us identify and locate hard-to-find respondents more quickly. They can assist us in putting together effective screeners and simplify the process of developing discussion guides so we can focus our time and talents elsewhere. They can help us scale our reach, enabling more conversations with more target audiences.

AI can be our tireless intern, working without the need for coffee or bathroom breaks to create and cull through focus group transcripts, survey responses, social media posts, reviews, and more. AI tools can help us identify trends and patterns that might take the human eye much, much longer to see. They can collect and synthesize data across a wide range of sources in a way that makes it easier for us to draw out those insights. And they can help us create reports that equip clients with clear answers and strategic recommendations.

What they can’t do is replace us — us being human researchers who bring to the table years of lived experience, an in-depth understanding of human behavior and dynamics, the know-how to pull insights from findings and apply those to brands, and above all else, empathy.

AI is here to stay, and we must come to terms with it in market research. But this can be a collaborative rather than adversarial partnership, one that benefits all parties involved — from the researcher to the respondents to the client to their customers.

We’d love to talk more about findings vs. insights and the role of AI in MR with you. Reach out with any questions or thoughts.

Unveiling the Multifaceted Moderator: Navigating Qualitative Research

In our previous blog post, we explored a different approach to thinking about the definition of “interviewer” versus ‘”moderator.” Now, let’s delve deeper into the role of the “moderator” and why they are indispensable, especially from a client’s perspective.

Moderators, as defined in our last blog, assume a broad role that goes beyond asking questions and eliciting responses as dictated by a script or guide.

Indeed, moderating requires a multifaceted skillset.

So when your research requires looking for in-depth insights — the why behind what — you need someone who knows when to ask questions that aren’t on the script, and how to dig deeper for answers buried beneath the obvious. In other words: a moderator. And not just any moderator. To be truly effective, moderators must be part business advisor, part market insights generator, part psychologist. You can add brand guru and circus ringmaster to that list, as well. Let’s take a closer look at these roles, and why each one is necessary to maximize the value of your research.

Business Advisor Who Gets Your Industry

In addition to understanding the art of asking questions, a moderator should understand the client’s industry, market dynamics, and business objectives. Ideally, your moderator will have first-hand, in-the-trenches industry experience they can call on. Need someone who can talk confidently about molecular biology with a focus group of physicians? Make sure your moderator speaks the language. Along with industry-specific knowledge, it helps to have a moderator with enough business acumen to translate research outcomes into actionable strategies.

Market Insights Generator Ready to Dig Deep

More than reading questions off a script, a skilled moderator uncovers rich market insights in the answers they elicit. To do this, they employ a multitude of techniques to stimulate discussion, encourage participants to share their perspectives, and excavate insight beyond surface-level responses. They help reveal unspoken thoughts, emotions, and motivations, providing a holistic understanding of the target audience that powers better business decisions.

Psychologist and Empathetic Listener

Understanding human behavior and motivations is a core aspect of moderating. Moderators need to create a comfortable and non-judgmental environment where participants feel encouraged to express their thoughts and emotions openly. That requires having active listening skills and empathy, as well as a toolkit of psychological techniques that enable them to connect with participants and delve into their underlying attitudes and beliefs.

Brand Guru in the Room

Moderators need to have a deep understanding of the client’s brand, its values, and its positioning in the market — as well as a familiarity with the importance of branding in general. This brand fluency enables them to steer discussions towards brand-related topics and explore participants’ perceptions, associations, and experiences with the brand. This additionally allows moderators to identify gaps, strengths, and opportunities to strengthen the brand’s positioning.

Circus Ringmaster and Focus-Group Tamer

You thought we were joking about this one? Have you ever seen a focus group? A moderator worth her title knows how to facilitate and manage the complex group dynamics that, when unguided, can quickly derail focus group discussions. Moderators ensure that everyone has a chance to contribute (including that shy person in the corner), manage the group’s time effectively, and steer the conversation towards the research objectives. They also navigate potential conflicts and dominant participants while creating an atmosphere conducive to open and respectful dialogue. All that’s missing is the top hat and bullhorn.

The Moderator You’ve Been Missing

If you’ve been less than thrilled with the outcomes and insights generated from your qualitative research studies, the missing piece may very well be the moderator — or lack thereof. A moderator who has the freedom, skills, and experience to assume multiple roles beyond question-asker and answer-taker will seek out, find, and extrapolate the truly valuable insight you need to make decisions and move forward.

Can we add quick-change artist to our list? A truly skilled qualitative researcher will know when and how to switch between being a moderator and an interviewer to achieve research objectives and help move your business forward. If you’d like to dive deeper into the role of a moderator versus an interviewer and which one best meets the needs of your research study, don’t hesitate to reach out to us. We love answering questions as much as asking them.

And keep a look out for our next blog post, in which we scrutinize one of moderators’ most vexing tools: the discussion guide.

Reimagining Discussion Guides in Qualitative Research: A Path to Deeper Insights

In our previous blogs, we explored the roles of “interviewers” and “moderators” in qualitative research, shedding light on their subtle but profound distinctions. Building on that foundation, let’s delve into an intriguing aspect of qualitative research: discussion guides. Are they a blessing or a curse? Well, that’s a question we’ll navigate together.

Discussion guides are often seen as essential tools to steer interviews or focus group conversations. They aim to provide structure and ensure researchers cover all the necessary topics. In theory, they’re fantastic. In practice, they can sometimes be a double-edged sword. Here’s why.

Too often, discussion guides are treated as rigid scripts, akin to structured surveys, particularly in studies that require more of an “interviewer” approach, where predefined questions are asked to gather specific information or opinions. This rigidity can hinder the natural flow of conversation between moderators and participants, preventing us from capturing the nuanced responses that are the essence of qualitative research.

The Discussion Guide, Redefined

So, does this mean we should toss discussion guides out the window and rely on spontaneity? Not quite. Instead, let’s consider a subtle shift in how we perceive discussion guides. What if we viewed them as flexible tools that guide rather than dictate conversations? What if they were references that provided guardrails to prevent veering too far off course while allowing for organic discussions?

In more exploratory studies, discussion guides can take on a different form as “topic outlines,” something that conveys the fluid nature of the moderated conversation. This shift allows for a dynamic and adaptable approach, where the guide acts as a reference point rather than a strict script.

Imagine empowering moderators to utilize their active listening skills, intuition, and adaptability to create an environment where participants express themselves freely. This shift can enhance the authenticity and richness of qualitative research, keeping it true to its core purpose: to uncover meaningful insights.

Moreover, what if we shifted our focus from meticulously crafting discussion guides to truly understanding research objectives? Rather than obsessing over what we ask, let’s emphasize why we ask it. This shift could lead to a more personalized, adaptive, and fruitful approach to qualitative research, yielding:

1. Better Goal Alignment: A deep understanding of research objectives empowers moderators to adapt their questioning techniques, delve deeper into relevant areas, and have more targeted and insightful discussions.

2. Improved Participant Engagement: With a strong grasp of research objectives, moderators can connect better with participants, creating an environment conducive to open and honest dialogue.

3. Contextualized Analysis: Moderators who understand research objectives can effectively synthesize information, identify key patterns, themes, and insights that align with research goals, resulting in more valuable outcomes.

The question now becomes: how do we make this shift from focusing on the discussion guide to fully understanding research goals? It’s simpler than you might think, and it involves a three-step process:

1. Clearly Define Research Objectives: Start by establishing well-defined research objectives in collaboration with the client. This crucial first step ensures that both parties are aligned on the purpose and desired outcomes, providing added guidance for the moderator as they structure the research and facilitate more focused and meaningful discussions.

2. Create a Research Outline: Instead of providing a rigid, script-like, full-scale discussion guide, outline the main research components or themes to be covered during the discussions. This approach offers a loose structure that guides the moderator while allowing for flexibility, exploration, and unexpected insights as the conversation naturally evolves.

3. Pretest Interviews: Consider including three to four pretest interviews to give clients a better understanding of how the moderator will conduct the actual research. This can help manage expectations and create trust by demonstrating the moderator’s understanding of the research objectives, interviewing style, and ability to adapt on-the-fly.
By embracing this approach, you pave the way for more personalized, adaptive, and fruitful qualitative research, leading to a deeper understanding of the subject matter and more valuable outcomes.

Overcoming Trust Issues

There’s another reason clients can be reluctant to relinquish control of the discussions guide: trust issues. As experienced as a moderator may be in leading discussions, they don’t always have a deep understanding of the topic that’s being discussed — especially if that topic is highly technical, complex, or specialized. In these cases, clients may feel the need to dictate the tone and language of the discussion guide — down to the last word and punctuation mark.

This is completely understandable, especially in a new and untested relationship. By maintaining tight control over the discussion guide and using it more like a script, clients can compensate for a moderators’ lack of knowledge about the topic being discussed. But again, this can end up stifling the conversation and impeding quality insight.

Letting go of this control is an exercise in trust on the part of the client. Partnering with a moderator and research team that bring a high level of understanding, ideally gleaned from first-hand experience, of the topic can help clients feel more comfortable with releasing the reins. Pretesting interviews (step three above) can also be an effective tool in building that trust.

Let Moderators Moderate

Ultimately, as researchers we should strive for that balance between providing structure and allowing for natural conversation within the research process. By recognizing the discussion guide as a flexible tool rather than a strict must-follow script, we can leverage its benefits while preserving the value of organic qualitative research.

This approach gives moderators the ability to be more attentive and responsive to the dynamics of the discussion, enabling them to probe deeper into relevant areas and follow interesting tangents that emerge naturally during the conversation. In other words, to become better moderators. And that leads to better insights.

Thinkpiece Certified by the Women’s Business Enterprise National Council

Thinkpiece, a business specializing in B2B qualitative market research, is proud to announce national certification as a Women’s Business Enterprise by the Women’s Business Development Center – Midwest, a regional certifying partner of the Women’s Business Enterprise National Council (WBENC). WBENC Certification is the gold standard for women-owned business certification in the United States.

“I look around our industry, and while many amazing market researchers are women, I see few in the C-suite of MR companies. We need representation, affiliation, and solidarity. It’s my hope that our certification and success will inspire a wave of women researchers to start their own company if they have it in their hearts.

I’m excited for the future of Thinkpiece and know that this certification will open doors and connections to help us achieve our audacious goals.” – Bonnie Dibling, Founder and CEO

The WBENC standard of certification implemented by the Women’s Business Development Center – Midwest is a meticulous process, including an in-depth review of the business and a site inspection. The certification process is designed to confirm the business is at least 51% owned, operated, and controlled by a woman or women, and that the business has appropriate structure and strategic business planning and implementation in place.

By including women-owned businesses among their suppliers, corporations and government agencies demonstrate their commitment to fostering diversity and the continued development of their supplier diversity programs, which in turn empowers women as leaders and brings about a more diverse, balanced, and sustainable economy.

WBENC Certification combined with professional development and engagement in the WBENC network provides unsurpassed opportunities year-round, both virtually and in-person, for women-owned businesses to grow and expand their business and innovation through events, programming and connections with major corporations and other WBEs.

To learn more about Thinkpiece, please visit thinkpiece.com.

 

About Thinkpiece:

In the editorial world, a think piece refers to an in-depth analytical article with a forceful point of view – written to inspire and provoke thought and discussion that delves beneath the surface.

Thinkpiece builds on this concept and applies it with a focused lens to the world of B2B qualitative market research. More than simply serving up raw research for our clients to decipher, we reveal the deeper meaning hidden beneath the surface.

With moderators who came from the industries we serve, we bring an ‘insider” point of view that doesn’t shy away from complexity. And with analysts who are experts in human behavior and relationships, we add context that illuminates connection. We dive relentlessly into the research, exploring and interpreting it from every angle and multiple perspectives: as industry peers, research experts, and insatiable learners.

We take apart the research, examining each piece on its own without bias, then we put the pieces back together to reveal the whole picture that tells a cohesive story. Ultimately, we challenge our clients to think deeply and differently about their products, services, and audiences. We provoke new ideas and innovations. And we provide the insight to power better business decisions that better the world.

 

About WBENC:

Founded in 1997, WBENC is the nation’s leader in women’s business development and the leading third-party certifier of businesses owned and operated by women, with more than 18,000 certified Women’s Business Enterprises, 14 national Regional Partner Organizations, and more than 500 Corporate Members, most of which are Fortune 500. Thousands of corporations representing America’s most prestigious brands, as well as many states, cities, and other entities, look for and accept WBENC Certification. Through the Women Owned initiative, WBENC also is a leader in supporting consumer-oriented female entrepreneurs and those who do business with them by raising awareness for why, where and how to buy Women Owned. For more information, visit www.wbenc.org and www.buywomenowned.com.