What happens when your AI actually understands research methods
Editor's note: This article is an automated speech-to-text transcription, edited lightly for clarity. For the full session, please watch the recording.
Most AI tools can help you rewrite a survey question or summarize an open-end. But what happens when your AI actually understands the methodology behind your research? When it knows how to apply complex methods, recommends the right approach for your objective and constructs structured projects in minutes?
During a session in the Quirk’s Virtual Sessions – DIY Research series on September 24, 2026, Dr. Lindsey Guzman, senior solutions manager and Philipp von Sethe, full cycle senior solutions consultant at quantilope answered these questions.
The two speakers showcased quantilope’s AI platform, quinn, and how the AI understands methods like MaxDiff, TURF and conjoint.
Session transcript
Joe Rydholm
Hi everybody, and welcome to our session, “What Happens When Your AI Actually Understands Research Methods?” I'm Quirks Editor, Rydholm, and before we get started, I wanted to quickly go over the ways you can participate in today's discussion.
You can use a chat tab to interact with other attendees during the session, and you can use the Q&A tab to submit questions for the presenters during the session, and we'll answer as many as we have time for during the Q&A portion at the end.
Lindsey, take it away.
Dr. Lindsey Guzman
Thanks, Joe. Welcome everyone, and thanks for joining.
I'm Lindsey Guzman, a senior solutions manager here at quantilope. I've been with quantilope for almost five years, but I've spent more than 15 years in the research industry. So, I've had a front row seat to how AI is changing the way our clients get to decisions faster. And really what I do at quantilope is help new and emerging brands, as well as more established brands, transform the way that they do research, leveraging the power of our platform.
Today I'm joined by my colleague, Philipp.
Philipp von Sethe
Yes, thank you very much.
My name is Philipp. I'm a full cycle solution consultant; meaning I support at the stage where we try to figure out if a partnership makes sense. So, trying to figure out if we can solve your business questions that you have with all the methods that we have in the platform. But I'm also supporting our clients where we already have a partnership with all the new developments that we have in the app. So, are there new methods available? Are there new approaches to research and so on? And then I discuss with our clients if these approaches make sense for them, if they want to use us or not, just trying to figure out does it solve a need that they have, or should we continue the way we work together so far?
Dr. Lindsey Guzman
Thanks, Philip. All right, so let's go over just this slide and then we'll hop into the platform.
Most of us have already used general purpose AI for research. We know that it can explain what a MaxDiff is, it can suggest survey questions and it can even summarize a transcript, which is useful. But there's a gap between describing a method and running one to a standard you can confidently present to your stakeholders.
A survey isn't just a well-written list of questions. Someone has to decide who qualifies, which question type fits each measure, how the scales are built, what gets randomized, where routing and piping go and how the data comes out the other end ready to analyze.
Quinn is built for that work because it lives inside the platform where the projects and data already are.
Some of the benefits of using quinn rather than a general LLM are that it already has my project context. So, I'm not pasting my objective and my question wording into a separate chatbot every session and going back and forth from one window to another, which I'm sure we're all familiar with. It can build my study directly into the platform.
In comparison, a general tool hands you suggestions to copy somewhere else while quinn constructs the project with me.
It's also grounded in quantilope’s marketing science so it knows what TURF, MaxDiff and conjoint each require to run properly instead of guessing at the design needed for the project.
Everything I've described so far is quinn working inside a single project, but we also have an exciting new feature, which Philip will show you in a little bit called quinn search, which reads across your entire research library at once, years of studies, your concept test, your tracker, all of it.
So, imagine a world where instead of reopening old decks and sorting through thousands of PowerPoint slides, you can ask a question and pull an answer from all of the research that you've ever run on the quantilope platform.
Quinn search is helping our clients make the most out of the platform by having a centralized research hub where knowledge is shared instead of siloed.
All right, let's pivot into the platform.
This is what the quantilope platform looks like. We're going to start a new project. I'm going to call it my skincare study. I'm going to work from a blank slate instead of one of our prebuilt templates, and let me go ahead and share that tab.
So, as you can see, there's templates available. I'm going to title my project Skincare Study and I'm going to click ‘Create.’
Once I've created my project, you can see that we're in the ‘Manage’ section, and this is where you can attach a brief or any other external context that you want quinn to have when building a survey.
For this example, we're not going to attach a brief, we're just going to jump into the survey editor and I'm going to paste a prompt into quinn, and I'm going to ask it to plan a survey for me with my specific specifications because imagine that you are working with a client or you are that client that just has a business question. Maybe you're a skincare brand operating in a crowded market, you want to understand the consumer journey, perhaps you want to identify which advertising channels will maximize reach and in the same survey, determine which product messages to prioritize.