Business

Introducing Diary Studies

Aaron Cannon

On Sunday, a participant tells you she doesn't eat sweets during the week. On Wednesday, mid-study, she mentions the cake she had after dinner.

Neither statement is a lie. The first one is memory, and memory is tidy.

The second one is what actually happened. That gap is why diary studies exist, and it's why no single interview can close it, however well moderated.

Running one, though, has always meant accepting two things: whatever answer participants initially submit, and waiting until the end to understand it all.

Diary studies are now live in Outset, and for the first time, every round of a longitudinal study can be a full AI-moderated conversation, with every session synthesized the moment it closes.

Every round is a real session

You design the study once: the cohort, the cadence, the rounds, and what each round needs to surface. 

Participants join each round and have a conversation with the Outset moderator, following the guide you wrote and probing the way you told it to.

When a participant says a product was "fine" or "pretty much the same," the moderator asks what she means while she's still there to answer. That's the first thing that changes. You're no longer accepting whatever gets submitted and sorting the useful from the useless weeks later. The depth gets built in while the session is still running.

The moderator can see, too

Diary rounds are integrated with Outset's Visual Intelligence, so the moderator works with more than what a participant types or says. It can watch what she does: the product in her hand, the shelf she's standing in front of, the thing she reaches for instead. Then it probes on what it saw.

For consumer insights teams, that’s the difference between reading an account of a routine and seeing the routine.

Analysis starts at round one

The second thing that changes is when you get to understand it. Every session generates an AI summary as it closes. Themes, topline findings, and the ability to chat with your data populate from the first round, automatically and at no extra cost, with no manual pass between rounds and no waiting on the final submission.

You can share a read after week one, see where your heavy and light users diverge in week two, and shape what you ask about in the rounds still ahead. Segment, filter, and cross-tab as the data lands.

Without adding another tool to your stack

Longitudinal research usually means assembling one. Something to recruit, something to capture entries, something to coordinate rounds, and something to make sense of it all.

In Outset it's one platform. Diary sits alongside interviews, concept tests, surveys, and usability studies, with the same AI moderator, the same analysis layer, and the same governance and permissions. Cohorts, rounds, and invites are handled in the platform instead of a spreadsheet, and you recruit through the panel integrations you already use.

What this means

Diary studies have always been the method that tells you the most and costs the most to run. Weeks of fielding. Entries of wildly uneven quality. Analysis that couldn't start until the last participant finished the last round. None of that stopped teams from running them. It meant running them selectively, and answering the other questions with recall.

Both of those costs came from the same constraint. A moderator can only be in one session at a time, and synthesis could only begin once everything was in. Remove the constraint and the method stops being something you have to spend carefully. 

Run it day to day, week to week, or month to month, with hundreds of participants or thousands, across the programs your team already runs in Outset.

The weekly shopping trip, the first weeks with a new product, the morning routine, the slow drift in how someone feels about a brand. Anything where the passage of time is the question, you can now have longitudinal depth, without the longitudinal overhead, where every response is a conversation and not a form.

Interested in learning more? Book a personalized demo today!

Interested in learning more? Book a personalized demo today!

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About the author
Aaron Cannon

CEO - Outset

Aaron is the co-founder and CEO of Outset, where he’s leading the development of the world’s first agent-led research platform powered by AI-moderated interviews. He brings over a decade of experience in product strategy and leadership from roles at Tesla, Triplebyte, and Deloitte, with a passion for building tools that bridge design, business, and user research. Aaron studied economics and entrepreneurial leadership at Tufts University and continues to mentor young innovators.

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