Meet Persona Agents: Always-on intelligence for insight-led innovation
Editor's note: This article is an automated speech-to-text transcription, edited lightly for clarity. For the full session, please watch the recording.
Consumer segmentation has been around for a long time, but now AI is playing the part of various consumer segments. The result is a short timeline for insights.
In this 2026 Quirk’s Virtual – AI and Innovation series session, Joseph Rini, director of product management of Market Logic Software, explains how DeepSights™ can help researchers explore their consumer segments. Attendees walked away with knowledge on the difference between persona agents and traditional personas, where they add the most value, how test ideas and challenges using existing research and how real research teams use persona agents.
Session transcript
Joe Rydholm
Hi everybody and welcome to our session, “Meet Persona Agents: Always-on intelligence for insight-led innovation.”
I'm Quirks Editor Joe Rydholm. Before we get started, I just 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 a Q&A tab to submit questions for the speaker during the session and we'll answer as many as we have time for during the Q&A portion at the end.
Our session today is presented by Market Logic Software. Enjoy the presentation!
Joseph Rini
Hi, thank you so much for joining today for Market Logic's persona presentation entitled, “Meet Persona Agents: Always-on intelligence for insight-led innovation.”
My name is Joe Rini. I'm a Director of Product Management at Market Logic Software and I'm really excited to speak to you today about our persona offering.
Before we get started, just quickly, who is market logic, what do you do, and so on.
Many of you will know us in this space. We are a SaaS software company. A market leading SaaS provider of an insights management solution that is used by some of the largest and best known brands in the world as you can see on the screen.
We help them manage and make sense of all of their insights connected globally to ultimately empower business decisions, new product ideas, strategic approaches and so on, when it's time to make a decision in the field.
We offer a host of capabilities powered by gen AI and large language models, including our DeepSights™ knowledge assistant, which provides instant answers to business questions based on our customer's repository of knowledge, AI agents and of course our DeepSights™ persona agents, which I specifically want to speak to you about today.
Before I get into the personas offering, I want to talk a little bit about the overall challenge that we see.
And that's all around connecting the dots between all of the types of content that our customers hold and going from a passive consumption of all of those reports and market research documents to more of a forward looking, always on consumption of that content, leveraging the power of technology to help our consumers, our customers make the best use of all of the content that they hold.
So, what are DeepSights™ Personas Agents?
These are really large language models powered, synthetic or synthesized customers or B2B experts, built on our customer's unique proprietary data and understanding of their customer segments brought to life in the platform. A
s I said, with the power of gen AI and with these synthesized personas, users are able to explore the lifestyle and views of the customer segmentations, investigate and get feedback on early product ideas, concepts, marketing approaches, you name it. It's really like being able to speak to a version of your customers or your, let's say B2B stakeholders at any time, anywhere and get immediate feedback. Rather than waiting for costly and timely sessions with real customers, you're able to go into the system and speak to these synthesized personas AI built based on your data.
Now, I want to come into the platform and immediately show you what this AI persona is offering is all about.
I'm in a demo platform now and I'm currently looking at some snacks and beverages personas that have been set up in the system.
Let's just hover over one of them. Maya Lopez, she might be one of our customer's segmentations named the wellness oriented snacker. So, all of these personas are probably going to exist in a PowerPoint presentation somewhere, maybe in the Market Logic knowledge repository on behalf of our customers or elsewhere within the organization. And prior to solutions like the AI persona agents, customers would be expecting stakeholders internally to understand these personas and try to use them in marketing research and other subject activities.
Let's hover over and take a look at Maya.
She's a 32-year-old UX designer based in London. This is going to be fictional information but strongly based in the understanding of this particular customer segmentation.
And the big difference with the large language model powered nature of these AI personas is rather than reading about Maya in a static way in a PowerPoint presentation similar to what I was just showing you, you can actually go speak and interact with her.
So, I'm going to jump into a group chat in a second. As you can see on the left here, all of our chats are stored, and customers can also set up projects if they're working on particular tasks and topics.
Let's come into the snacking concept area where I've had an ongoing chat with a couple of the personas.
And the first thing I'll notice, I have been speaking to both Maya and Sophie simply asking them to first of all tell me a little bit about themselves just to further explore and understand them before I go ahead and expose them to some new product concepts that I've been working on.
So, Maya tells me a bit about herself, as does Sophie. I could of course go further here and spend some time really digging into each of the personas and try to understand the whole segmentation approach that's behind each of them. I'm going to start steering the conversation towards their snacking routine before showing them some concepts. I just want to understand how they snack and again, this is going to be based on the data and the real customer's understanding of how these two personas segmentations will be snacking.