During a focus group among foodservice professionals, one participant said to another …

… “your restaurant is never going to make money. I’m just saying.” The second participant neither appreciated nor agreed with this statement. But it started a good, if emotional, conversation.

At one point I quoted what the first participant had said, including the ‘just saying’ part, and asked why he had added that. He thought a bit and admitted that he had included it without thinking about it. Eventually he realized that he was trying to be less harsh. This led to further discussion about the intense emotional commitment restaurant owners make to their businesses, which surfaced important insights for the client, a food manufacturer.

‘Just saying’ is one of those phrases we sometimes use without thinking. It’s what’s technically called a discourse marker – something that indicates how somebody wants a statement to be interpreted. Specifically, it signals that the speaker wants the remark to be heard in a particular way – or to avoid responsibility for how it might be taken. As a qualitative researcher, I pay close attention to these markers, as they can be clues to hidden meaning. I’ve learned that when somebody adds in ‘just saying,’ they’re probably not just saying. While ostensibly it means that somebody is merely making an observation, it usually means more.

Specifically, it might indicate the speaker is trying to:

Soften criticism by making it seem less personal or confrontational.
Create plausible deniability if the remark is challenged or poorly received.
Imply something without stating it outright leaving the listener to connect the dots.

So, by exploring these markers when we encounter them and questioning why the speaker included one in a statement, we can learn more about a person’s true meaning and feelings.  In addition to ‘just saying,’ here are a few more discourse markers that I watch for, as they suggest veiled subtext:

‘For what it’s worth…’ signals modesty while asking the listener to take the opinion seriously.
‘No offense, but…’ acknowledges that offense is likely while attempting to soften it.
‘Don’t take this the wrong way, but…’ is a way to soften criticism.
‘With all due respect…’ marks disagreement while paying deference.
‘Not for nothing…’ suggests a point deserves more attention than it’s getting.
‘I’m just asking the question…’ frames an implication or challenge as mere curiosity.

So, when you notice a discourse marker in the course of conversation, dig in. You’re likely to learn a little more, and maybe even a lot more.

There’s no substitute for experience and expertise.

We have been collaborating on research that combines qualitative methods and advanced technology for about 15 years. However, we’ve never actually told the world about this. So, here goes.

Market research is a team effort. High-quality outcomes require that all participants do excellent work and know how to work together. Today’s evolving landscape often requires the integration of traditional qualitative research with behavioral and emotional measures such as eye tracking and biometrics.  A high degree of experience working with these tools – and working seamlessly – is essential to producing quality results that yield unexpected insights.

Combining advanced technology with qualitative methods is an unbeatable combination. It allows us to uncover what people really notice and respond to – often beyond what they can articulate themselves. But only if everybody involved understands the tools and techniques.

We have worked together dozens of times on this type of research. Bob provides the advanced technology. Tom handles the qualitative research design, execution and analysis. This combination yields outstanding results because IVP is the leading provider of eye tracking and biometric technology to the market research world, and Tom is widely known for combining these tools with qualitative methods.

People often view biometrics as a plug-and-play solution. But success depends upon more than sophisticated equipment. If the qualitative researcher moderating the study doesn’t understand eye tracking or biometrics, important opportunities will be missed. The study design could be flawed, important questions might not be asked, perceptions might not be probed, and valuable insights will never surface.

What’s more, collecting and analyzing biometric data is both art and science. If the people responsible for the technology aren’t experienced, you could easily end up with useless data and wasted time and money.

The same principle applies on the back end. Biometric data has little value unless those responsible for its analysis understand marketing strategy, motivation, and decision-making. This allows data to be translated into meaningful stories and actionable insights.

That’s why collaboration matters. Successful studies occur when all parties understand one another’s disciplines. The difference between a good study and a great one is ensuring that every link in the chain is strong from the beginning to the end.

Remember when we all thought the world was flat?   

We don’t believe things because they’re true. We believe them because they’re easy to believe.  As a qualitative researcher, one of the main things I do is help my clients understand how people form opinions and make decisions. Do this long enough and you’ll notice that people believe some crazy stuff. So, I regularly need to figure out why people believe things that are demonstrably untrue.

We live in a world inundated with information. What’s more – newsflash! – a lot of the information we encounter is incorrect. Sometimes this inaccuracy is inadvertent, sometimes it’s deliberate. Figuring out what’s true is increasingly important. And one thing that can make this particularly challenging is that sometimes things that aren’t true just sound like they are.

Cognitive psychologists have a term for this: ‘the illusory truth effect.’ It’s our tendency to believe something simply because it’s familiar – we’ve heard it repeated many times over a long period. This repetition increases what’s called ‘processing fluency,’ which is a fancy way of saying that something is easy to think about. Our brains then mistake that ease for accuracy. If you’ve been told your entire life that the earth is flat, that doesn’t just sound true, it sounds obvious.

I see this as being a problem. When something intuitively sounds true, we’re likely to take it at face value and not challenge it. And this is how lies spread virally. I’m reminded of that remark attributed to Mark Twain about how a lie can travel halfway around the world before the truth can put its pants on. (Actually, there’s no proof he ever said that, so maybe this is illustrative of my point.)

The increasing importance of social media and artificial intelligence makes this a particularly urgent issue, as these tools play a significant role in perpetuating untruths. Social media algorithms amplify repetition, and repetition drives the illusory truth effect. These algorithms also magnify saliency – they make things seem more significant than they are. These factors put a lot of responsibility on each of us individually to vet information.

This isn’t something for which any of us has the power to effect broad change. We need to focus on our own thinking patterns.  This means getting in the habit of questioning conventional wisdom. Because  a lot of conventional wisdom out there is complete nonsense.

So, when something is easy to believe, be suspicious. The fact that it’s easy doesn’t make it true.

Probability Isn’t Intelligence. 

If you’ve been to a marketing or market research conference recently, you’ll have noticed that most of the content is either expressly or indirectly about artificial intelligence and how it applies to our field. Same for the trade press – it’s heavily focused on AI.

As with pretty much every other profession, AI tools have significantly changed market research. From writing a first draft of a questionnaire to streamlining analysis, they can be extremely valuable. As a qualitative researcher, I’ve found them to be quite helpful in certain, specific situations. For instance, they’re great for automating repetitive tasks and are also very good (probably better than humans) at identifying latent themes in qualitative data.

As indispensable as these tools are, it’s important to remember what they can and can’t do. AI pioneers like Judea Pearl and Gary Marcus have pointed out that the term ‘AI’ is something of a misnomer, as artificial intelligence isn’t truly ‘intelligent’ in the most commonly understood senses of the word.

Rather, AI tools are high-dimensional probability calculators. They are good at yielding output that eerily resembles intelligence and are amazingly good at finding correlations and hidden patterns. As such, these tools can help us come up with new, unexpected hypotheses for further investigation.  However, it’s essential not to skip that ‘further investigation’ part.

Using technology to automate tedious, recurring tasks or to sift through a huge, disorganized dataset is a smart practice. But, if you let a microchip think for you, not only are you asking for something it can’t actually do, but you are making yourself – as a carbon-based life form – superfluous.

Drawing new insights from data requires thinking. Managing a conversation in a spontaneous manner that leads to unexpected, insightful findings requires thinking. For now, at least, people will need to continue to do these jobs. So, if we want to stay relevant as humans, we need to lean into some uniquely human skills: critical thinking, inference, and nonlinear reasoning. Remember, probability and insight are not the same thing. True wisdom comes from things like intuition and lived experience.

When it comes to AI, a lot of the conversation seems to focus on efficiency. I like saving time and money as much as the next guy, but truly transformative qualitative research isn’t about efficiency, it’s about inference and insight in the face of uncertainty. For now, at least, that’s what the human mind is for.

Do you really need that?   While conducting qualitative research on lightbulbs, a participant told me about her grandmother’s 98-year-old boyfriend, Chuck. He had recently bought replacement bulbs for his home and had paid a premium for ones that would last 15 years. While I admired Chuck’s optimism, I’m not sure that paying extra for bulbs that will almost certainly outlive you is a great idea for somebody on a fixed income.

Chuck is not unusual. We often seek more than we need. I was talking recently to a guy who has two cars. One is an SUV fully equipped for off-road driving, even though he admitted that has never taken the thing off-road and probably never will. The other is a Lamborghini that has a top speed of more than 150 MPH. For myself, I’ll share that I have a home theater system so powerful that, turned up to maximum volume, would flake the paint off the walls and damage my hearing.

Why do we do this? Several instincts drive this sort of behavior:

The safety margin instinct. Surplus capability feels like security (‘you never know!’)

Identity signaling. Excess capability is a way to say something about yourself. That guy with the SUV might like being able to drive offroad, even if he never does. And his Lambo signals something about virility and success, even if he never drives faster than 85.

The ‘more is more’ instinct. We often associate ‘more’ with ‘better,’ despite what Mies van der Rohe used to say. Over-the-top specifications feel meaningful, even if they go beyond practical requirements. This is linked to the fact that we evolved as a species under conditions of deprivation.

Fear of regret. It’s common to worry that, when making a purchase, if you don’t buy the top-of-the-line, you might regret it. You might miss out on capabilities that you turn out to need (again, ‘you never know!’).

The power of the quantifiable. That a car can go 150 MPH is a clear, numerical fact. The possibility of getting a speeding ticket is not readily quantified. Numbers feel objective and are easier to think about than squishy possibilities.

Sometimes investing in what seems to be overkill is smart. Sometimes it’s an indulgence. And sometimes it’s a misinterpretation of risk. The key to making good choices lies in thinking through such decisions with care. So, if you think you might be about acquire more than you need, ask yourself this:

“Am I buying this because I really need it, or because it represents how I would like to think about myself or how I want others to see me?”

Here’s a final thought. By now, you’ve probably already broken all your new year’s resolutions. So, as you’re thinking about the rest of the year, maybe a good goal would be to emphasize necessity over excess.