Customer Experience

Photo Diary Study: Product Use in Context

A repeatable diary entry participants complete each time they use your product in real life: a photo of the moment, what they were trying to do, and what got in the way — with an AI probe on the day's friction. Run it daily or weekly to see usage where it actually happens, not in a lab.

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샘플 질문

템플릿에 포함된 내용을 미리 확인해 보세요. 모든 질문은 설문 공개 전에 자유롭게 수정할 수 있습니다.

질문 8개 · 약 5분

Q01

메시지

Diary check-in time! This takes about 6 minutes. Your responses are completely confidential and anonymized. Answer for the most recent time you used the product — today if possible. Photos are hugely helpful: where you were, what was on your screen or in your hands.

Q02

객관식필수

When did this usage session happen?

In the last hour
Earlier today
Yesterday
Longer ago

Q03

질문

Share a photo of the moment — your setup, surroundings, or what you were working with. No faces or private info needed.

Q04

단문형필수

In one sentence: what were you trying to get done?

Q05

의견 척도필수

How smoothly did it go?

척도: 1 – 5

최소:Major friction — nearly gave up최대:Completely smooth

Q06

질문

In your own words (30–60 seconds): walk me through what happened, like you're telling a colleague.

Q07

AI 인터뷰

Probe today's diary entry: the exact moment friction appeared and what the participant did next, anything they used alongside the product (other apps, paper, asking someone), and whether this session was typical or unusual for them. Keep it short — two or three focused follow-ups; this is a recurring diary, not a full interview.

Q08

메시지

Entry logged — thank you! See you at the next check-in. Patterns across your entries (and everyone else's) build the real picture of how the product lives in the world.

포함된 기능

AI 후속 질문
정형화된 설문이 놓치는 세부 내용을, 주관식 답변에 맞춰 AI가 심층 질문으로 끌어냅니다.
주의력 확인 장치
성의 없는 답변과 저품질 응답자를 걸러내는 내장 안전장치입니다.
AI가 작성한 문안
문구, 질문 순서, 분기 로직까지 AI가 연구 목표에 맞춰 작성합니다.
자동 리포트
응답이 모이면 주요 주제, 인용문, 이해하기 쉬운 요약이 자동으로 작성됩니다.

다른 서비스와 비교

다른 설문 도구의 가장 유사한 템플릿을 검토했습니다. 그 도구들이 잘하는 점과, 이 템플릿이 한발 더 나아가는 지점을 정리했습니다.

이 템플릿을 선택하는 이유

Each entry pairs a photo of the real moment with a short AI probe on that day's friction — in-context evidence, not lab recall
Voice-memo option captures the story the way participants would tell a colleague
Entries are deliberately 3 minutes so longitudinal participation survives busy weeks
Cross-entry patterns are assembled automatically into a usage-in-the-wild report

dscout

Diary Studies for Longitudinal UX Research

A purpose-built longitudinal diary platform that captures photo, video, screen-recording, and text entries over days to years, with automated pacing reminders and playlist/highlight-reel analysis. Very strong on in-context multi-media capture and participant management, and the closest direct competitor to a guided-task style study.

잘하는 점

Rich in-context capture: photo submissions, video, screen recordings, and text reflections from participants in the moment
Multi-part study structures with automated pacing reminders to sustain engagement over long periods
Analysis tooling: playlist builder with exportable highlight reels, collaborative commenting, and expressiveness ratings
Precise participant targeting/recruitment for longitudinal panels

아쉬운 점

Entry prompts are fixed forms; no AI that reads a submission and asks an adaptive follow-up on that specific entry
No live voice-AI interview to debrief a participant conversationally about a logged moment
Synthesis relies on manual tagging and highlight-reel building rather than an auto-written report
Prompt/question logic is not exposed transparently to the researcher

User Interviews

Diary Studies (UX Research Field Guide)

A methodology chapter/template that covers the full diary-study lifecycle (planning, recruitment/onboarding, monitoring, debriefing, analysis) and defines interval-, signal-, and event-contingent logging protocols with sample prompts. Strong on rigor and entry-format variety, but it is guidance plus static forms rather than an adaptive interviewing engine.

잘하는 점

Full five-phase lifecycle: planning, recruitment/onboarding, monitoring, debriefing, analysis
Defines three logging protocols (interval-, signal-, and event-contingent) so studies match the behavior being observed
Supports written, photo, and audio/video entry formats plus structured forms
Sample prompts and a bias-avoidance emphasis (clear instructions without steering responses)

아쉬운 점

It is a field guide plus static entry forms, not a tool that adaptively probes each logged entry
No voice-AI interviewer to run the debrief phase automatically
Debrief/monitoring depend on the researcher's manual check-ins rather than automated follow-up
Analysis is a manual code-and-synthesize step, not an auto-generated report

자주 묻는 질문