Quirk’s New York 2026: key takeaways on AI, quality data and Gen Z

August 12, 2026By Marie Haaland

Marie Haaland and Livy Beaner at the Quirk's Event 2026

My colleague, Livy, and I had the opportunity to attend the Quirk’s Event in New York at the end of July. With ever-changing technology, it’s a fascinating time to work in market research — and we wanted to share some of our favorite takeaways from the many enlightening sessions at the conference.

Synthetic data

Synthetic data is artificial — but the goal is to mimic real, human-backed data. Presenters shared three key levels. Synthetic data can be used as a sampling substitute, where algorithms analyze a baseline of human data and use those findings to generate a new dataset; for augmentation, where synthetic data is used to expand an existing sample that’s too small to use; and replacing human data altogether. Sessions looked at how “boosting” existing data can be relatively accurate, but replacing human responses altogether leads to inaccurate data, particularly at a micro level.

We’d be remiss to not mention this: it was an important theme at the conference and should be, at the very least, in the back of every researcher’s mind as the technology continues to evolve. Should it replace real, human respondents today? No, but that doesn’t mean there aren’t currently any positive use cases, and we should all be prepared for synthetic data to continue improving. One presenter reminded us that every transformative technology starts as something unthinkable — and that’s about where we’re at with synthetic data.

Why does this matter?

Synthetic data may be a faster, cheaper option for brands looking to conduct research, but relying too heavily on this technology will lead to bad business decisions and skewed perspectives. Synthetic data can be used to inform general topics worth exploring, but human-led insights remain key to ensuring the highest data quality — which is why, at Talker Research, we still rely on a human panel to collect our data.

Digital twins

Another emerging technology, digital twins are personas that can be interacted with — they pull data from an individual or a group segment and are typically built over time with multiple inputs, used to create a well-rounded “twin.” This can be a great way to “speak” with a brand’s ideal customer to learn more about their purchasing decisions and what future products they may be interested in.

Digital twins are only as good as the data used to create them, though, so it’s important to ensure that when this technology is implemented, there are high-quality insights as the base. To put it bluntly, “garbage in, garbage out.” If the insights used to build these twins are low-quality and misleading, the twin will continue to share those inaccurate findings.

Why does this matter?

This technology relies heavily on the data being inputted, meaning it’s interactive, evolving and customized — which can be wonderful as an insights tool. This is a great resource for companies looking to gather more information on what their consumers are interested in, but caution should still be used as these twins are created and maintained.

The respondent journey

Because human-focused insights remain so important in market research, it’s key to consider how surveys are written and designed for respondents — something AI doesn’t always get right. Livy and I attended several sessions on this topic, and one key takeaway was to ensure surveys are engaging for respondents.

An example is how the questions are asked: instead of a standard Likert scale with a neutral middle option (“neither agree nor disagree”), how can we assign meaning to that option? Surveys written to be conversational led respondents to spend more time in the survey and provide higher-quality responses. And they have a point: when’s the last time you said “I somewhat disagree” to another human being during a casual conversation? Giving respondents options that correlate with how people actually speak leads to more usable, meaningful data points.

This is something AI can miss within a survey, and AI was also shown not to fully consider respondents’ attention spans and the cognitive effort that surveys can entail, overlooking the behavioral aspect that’s essential when polling real people.

Why does this matter?

As long as polling real humans is the backbone of market research, it’s imperative that surveys are designed in a thoughtful way, considering the impact the questions and design will have on respondents. This is how we ensure people continue to take surveys, and take them in a considered way.

Quality data

Quality-checking measures are an essential part of any survey — there’s no debate around that, but there are various ideas about the best way to implement these measures.

A negative survey experience won’t put off fraudulent respondents, who are there solely to earn money by completing the questionnaire, but high-quality respondents will leave as a result of a poorly-designed survey. Therefore, it’s key to ensure quality-checking measures don’t have a negative impact on the survey itself.

They should be in the background as much as possible — looking at concurrent activity, respondents’ mouse movements, etc. — instead of disrupting the survey experience. This helps remove both bots and low-quality human respondents, who can skew the data, resulting in misleading insights. It’s no longer just about ensuring respondents are real people, it’s also about ensuring they’re engaged in the content of the survey. Completion does not equal engagement!

Why does this matter?

There’s no reason to run research if the output isn’t reliable data that can stand up to scrutiny. Even if the results themselves don’t come out as hoped, quality data is still imperative — which makes it important to consider the various quality checks used on a survey. At Talker Research, we have a plethora of different measures, and we work to find the best balance between ensuring high-quality data and a seamless respondent experience.

Gen Z

When I started working in market research, millennials were the generation to watch: our surveys focused heavily on comparisons between millennials and baby boomers and explored all the ways in which millennials differed from the generations that came before.

Now, the focus is Gen Z.

But it’s important to recognize that Gen Z aren’t just “young millennials.” They’re a fundamentally different consumer — a generation of their own, with new habits, opinions and ideals. Money was a key focus in these sessions, knowing Gen Z’s financial views will influence how they shop and spend. While millennials were found to view finances as an exhausting journey, they still see the peak of the mountain — they can reach the top, even if it’s a slog. The same research found that Gen Z, on the other hand, view finances as something endless; they’re locked out of the journey (think of a tunnel or a staircase, where the end is obscured or may not exist at all).

Therefore, they’re focused on what they can control — they’re very particular about the products they purchase across various sectors (food, beauty, etc.). And with more young people living at home, Gen Z are also influencing the purchasing habits of other generations: they’re teaching their parents about clean eating and better-for-you options.

Why does this matter?

Gen Z will continue to be a dominating force, as more and more Gen Zers become adults: understanding who they are, without making assumptions, will be key to identifying new growth opportunities for companies, regardless of sector. Research on Gen Z may also help us identify trends that continue into Gen Alpha — though, just like from millennials to Gen Z, Gen Alpha will surely have their own group identity for researchers to learn.

In any industry, it’s important to stay informed about emerging technology and growth in various methods, and Quirk’s provided a wonderful opportunity for us to do exactly that. The conversations around synthetic data and digital twins were fascinating, and generational insights are always important to keep in mind — regardless of which generation is our focus at the moment.

But some things in research have stayed true year after year: a dedication to our respondents, and a high-value placed on the data we receive. Because of this, all of our surveys at Talker Research poll real, human respondents from our panel; that’s how we draw out the strongest insights and tell the best stories, for Gen Z and beyond.

A human-first approach can make all the difference in your next study. Get in touch with Talker Research to learn more about how we bring research to life. We’d love to talk.