Use this when you need to understand behavior, experiences, or routines over time -- not just at a single moment. Diary studies capture what happens in context, across days or weeks, when a researcher isn't watching. Produces a complete study plan: objectives, prompt design, check-in cadence, participant guidance, and analysis approach. Best for understanding habits, pain points in workflows, emotional journeys, or adoption patterns that unfold over time.
Related skills: Use
/research-prioritizeto decide whether a diary study is the right method. Feeds into/research-synthesizefor cross-participant analysis and/research-readoutfor stakeholder presentation. For one-time evaluative testing, use/usability-test-planinstead. References method selection inpractices/user-centered-design/research-ops-method-chooser.md.
Process
Step 1: Gather inputs
Ask the user to provide:
- Research questions -- what do you need to understand over time? (e.g., "How do users integrate the product into their daily workflow?" or "What triggers users to abandon a habit-forming feature?")
- Behavior window -- what timeframe captures the behavior? (One-time events need days, habit formation needs weeks, seasonal patterns need months.)
- Target participants -- who should participate? Role, segment, experience level, relationship to the product or behavior being studied.
- Decisions this informs -- what will change based on what you learn? (If nothing, don't run a diary study.)
- Constraints -- budget, participant incentives, tools available (dscout, Indeemo, Google Forms, Slack channel, dedicated app), team capacity for ongoing engagement.
- Prior research -- what do you already know? (Diary studies work best when you've done enough qualitative work to know what to look for.)
Step 2: Define study structure
## Diary Study Plan -- (Topic, date)
### Objectives
1. (Primary objective -- the most important behavior or experience to understand over time)
2. (Secondary objective)
3. (Tertiary objective -- nice-to-have)
### Study parameters
| Parameter | Detail |
|---|---|
| Duration | (3-14 days typical. Habits: 2-4 weeks. Seasonal: 4-8 weeks.) |
| Participants | (8-15 typical. More than interviews because some will drop off.) |
| Entry frequency | (1-3 entries per day, or event-triggered) |
| Entry effort | (Target 2-5 minutes per entry. Maximum 10 minutes.) |
| Incentive | (Per-entry micro-incentive + completion bonus. e.g., $5/entry + $50 completion.) |
| Tool | (dscout, Indeemo, Google Forms, WhatsApp/Slack, custom app) |
Step 3: Design diary prompts
Write prompts for participants to respond to at each entry point. Prompts should be:
- Short and specific (participants are logging in the moment, not writing essays)
- Grounded in observable behavior ("What just happened?") not abstract reflection ("How do you feel about productivity?")
- A mix of structured (quick to answer) and open-ended (rich but optional)
### Diary prompts
**Trigger:** (When should participants make an entry? Time-based: "Every evening before bed." Event-based: "Each time you use [feature/product]." Or both.)
**Required fields (every entry):**
1. **What happened?** (Free text, 1-2 sentences describing the moment or activity)
2. **When?** (Timestamp -- auto-captured or self-reported)
3. **Where were you?** (Context: at desk, on phone, commuting, in a meeting)
4. **How did it go?** (Scale: 1 = Frustrating ... 5 = Smooth)
5. **Photo/screenshot** (Optional but encouraged -- "Show us what you see right now")
**Rotating prompts (vary across days to reduce fatigue):**
- Day 1-2: "(Onboarding prompt -- e.g., 'Walk us through what you did today related to [topic]')"
- Day 3-5: "(Deepening prompt -- e.g., 'What workaround did you use today?' or 'What almost stopped you?')"
- Day 6+: "(Reflection prompt -- e.g., 'Has anything changed in how you approach [task]?' or 'What would you tell a new user?')"
**Weekly reflection (if study > 7 days):**
- "Looking back at this week, what stands out?"
- "What patterns are you noticing in your own behavior?"
Prompt design rules:
- Front-load easy prompts. Build participant confidence before asking for deeper reflection.
- Alternate prompt types to prevent fatigue. Don't ask the same thing every day.
- Include at least one photo/screenshot prompt -- visual data is often more revealing than text.
- Keep required fields to 5 or fewer. Make rich prompts optional.
- Write prompts in second person, present tense: "What are you doing right now?" not "Describe your experience."
Step 4: Plan check-in cadence
### Researcher check-in schedule
| Timing | Action | Purpose |
|---|---|---|
| Day 0 | Onboarding call (15-20 min) | Walk through tool, set expectations, answer questions |
| Day 1 | Review first entries | Catch misunderstandings early. Send encouragement. |
| Day 2-3 | Individual check-in (message) | "Great entries so far! Quick question about [specific entry]..." |
| Mid-study | Mid-point review | Assess entry quality, adjust prompts if needed, re-engage dropouts |
| Day N-1 | Closing reminder | "Last day tomorrow -- thanks for sticking with it!" |
| Day N+1 | Exit interview (30 min) | Deep dive into patterns. Ask about entries that surprised you. |
### Dropout mitigation
- **Day 1 silence:** Send personal message within 24 hours. Offer tech support.
- **2+ missed entries:** Send encouragement, not guilt. "No pressure -- even a quick note helps."
- **Day 3+ silence:** Direct outreach. Offer to simplify entries or switch to voice memos.
- **Recruit 20-30% over target** to account for expected attrition.
Step 5: Plan analysis approach
### Analysis framework
**Phase 1: Entry-level coding**
For each diary entry, code:
- Activity type (what they were doing)
- Context (where, when, with whom)
- Sentiment (positive, negative, neutral, mixed)
- Pain points (friction, confusion, workarounds)
- Bright spots (delight, efficiency, satisfaction)
**Phase 2: Participant journeys**
For each participant, map their entries chronologically:
- How did behavior change over the study period?
- What patterns emerged? (Daily routines, weekly cycles, one-time events)
- What triggered changes in behavior or sentiment?
**Phase 3: Cross-participant themes**
Across all participants:
- What behaviors are universal vs. segment-specific?
- What pain points appear repeatedly?
- What workarounds do multiple participants invent independently?
- Where do participant journeys diverge, and why?
**Phase 4: Reporting**
- Use `/research-synthesize` for cross-participant synthesis
- Use `/research-readout` for stakeholder presentation
- Include representative quotes, photos, and journey visualizations
Step 6: Logistics and participant guide
### Participant guide (share with participants)
**What we're asking:**
- (1-2 sentences explaining the study purpose in plain language)
- (Duration and expected time commitment per day)
**How to log entries:**
- (Tool-specific instructions -- where to go, what to tap/click)
- (Screenshot or walkthrough if helpful)
**Tips for great entries:**
- Log in the moment, not from memory later
- Short is fine -- a sentence and a photo beats a paragraph from memory
- There are no wrong answers. We want to see your real experience, not what you think we want to hear.
- If nothing happened today related to [topic], that's useful data too -- tell us.
**Questions or tech issues?**
- Contact: (Researcher name, email, phone/Slack)
- Response time: Within 4 hours during business hours
**Incentive details:**
- (Payment schedule, method, and any completion bonus)
Step 7: Review and validate
Ask the user:
- Is the study duration long enough to capture the behavior you care about? (Too short misses patterns. Too long causes dropout.)
- Are the prompts answerable in 2-5 minutes? (Time yourself.)
- Is the trigger clear? Will participants know when to log an entry?
- Do you have capacity for daily check-ins during the study? (Diary studies require active researcher engagement.)
- Is the incentive appropriate for the effort? (Under-incentivized studies have high dropout.)
- What will you do with the data? (If you can't articulate the analysis plan, simplify the prompts.)
Diary study design rules
- Diary studies measure behavior in context, over time. If you only need a snapshot, use interviews or usability testing instead.
- Entry fatigue is the enemy. Keep required prompts short. Rotate optional prompts. Thank participants frequently.
- The exit interview is where the magic happens. The diary entries are raw material. The exit interview is where you explore patterns with the participant and validate your interpretation.
- Recruit heavy, expect attrition. Plan for 20-30% dropout. A study that needs 10 completions should recruit 13-15.
- Photos and screenshots are underrated. They capture context that words miss. Make media prompts easy and optional.
- Don't run a diary study when you should run interviews. If you already know what happens and just need to understand why, interviews are faster and cheaper.
Output location
Present the study plan as formatted text in the conversation. The user adapts it to their research documentation and tool of choice.
Example Output
Input
- Research questions: How do mid-market sales reps integrate Copilot for Microsoft 365 into their daily deal workflow? What triggers them to use or skip it on any given day? Where does it break down or get abandoned mid-task?
- Behavior window: 3 weeks — long enough to capture initial adoption, the "trough of disillusionment," and any recovery or habit formation
- Target participants: 12 inside sales reps at Veralink Financial (B2B SaaS, 500-2,000 employees) who were given Copilot licenses 2 weeks ago; mix of high and low CRM activity levels
- Decisions this informs: Whether to expand Copilot licenses company-wide (800 seats, ~$240K/year decision), and which onboarding interventions to build before rollout
- Constraints: Budget for $15/entry + $75 completion bonus; tool is dscout; researcher has 1 hour/day for check-ins during the study; prior research includes 6 discovery interviews with sales reps about their current workflow pain points
- Prior research: Interviews surfaced three known friction points: meeting summary quality, CRM auto-fill accuracy, and email drafting for cold outreach
Output
Diary Study Plan — Copilot for M365 Adoption, Veralink Financial — June 2025
Objectives
- Primary: Understand how and when sales reps at Veralink actually use Copilot across their deal workflow — including moments of use, avoidance, and abandonment — over a 3-week adoption window
- Secondary: Identify which triggers cause reps to reach for Copilot vs. revert to prior habits, and what friction or trust failures drive abandonment
- Tertiary: Surface any informal workarounds or self-taught shortcuts that could inform onboarding design for the broader 800-seat rollout
Study Parameters
| Parameter | Detail |
|---|---|
| Duration | 21 days (3 weeks) |
| Participants | 12 recruited; target 9 completions (recruit 30% over target) |
| Entry frequency | Event-triggered: each time rep uses or consciously skips Copilot; max 3 entries/day |
| Entry effort | Target 3 minutes per entry; 7 minutes maximum |
| Incentive | $15/entry + $75 completion bonus (est. $150–$225 total per participant) |
| Tool | dscout (mobile + desktop) |
Diary Prompts
Trigger: Log an entry each time you use Copilot for any reason — or each time you started to use it and stopped. Aim for at least one entry per workday, even if it's "nothing happened today."
Required fields (every entry):
- What did you just do or try to do with Copilot? (Free text, 1–2 sentences — e.g., "Tried to get it to summarize my 11am call with Patterson Group")
- Which task? (Select: Meeting summary / Email draft / CRM update / Deal research / Something else)
- Did it work for you? (Scale: 1 = Completely failed me … 5 = Nailed it)
- Where were you working? (At desk / On laptop remote / On phone / In a meeting)
- Screenshot or screen recording (Optional but encouraged — "Show us what Copilot gave you, even if it was wrong")
Rotating prompts (vary by day to reduce fatigue):
- Days 1–3 (Baseline): "Walk us through the last time you completed this task without Copilot. What did that look like?"
- Days 4–7 (Friction): "Did anything almost stop you from using Copilot today? What did you do instead — or what made you push through?"
- Days 8–12 (Workarounds): "Did you change or edit what Copilot gave you before using it? Show us or describe what you changed and why."
- Days 13–17 (Comparison): "Think about a moment this week where Copilot saved you real time. Now think of one where it cost you time. What was different?"
- Days 18–21 (Reflection): "If a new rep asked you whether to bother with Copilot, what would you tell them? Has your answer changed since week one?"
Weekly reflections:
- End of Week 1: "What's surprised you most so far — good or bad?"
- End of Week 2: "Are you using Copilot more or less than last week? What shifted?"
- End of Week 3: "Looking back across the whole study — what does your Copilot use actually look like now compared to day one?"
Researcher Check-In Schedule
| Timing | Action | Purpose |
|---|---|---|
| Day 0 | Onboarding call (20 min via Zoom) | Walk through dscout, demo a sample entry, set expectations, answer questions |
| Day 1 | Review all first entries by EOD | Catch prompt misunderstandings; send personalized Slack note to each participant |
| Day 3 | Individual message to each participant | "Loved your entry about the Patterson call summary — can you tell me more about what you expected vs. got?" |
| Day 7 | Mid-week 1 review + prompt adjustment | Assess entry quality; if CRM entries are thin, add a targeted CRM prompt for week 2 |
| Day 11 | Mid-study check-in (10-min async Loom) | Share a non-identifying pattern with participants to sustain engagement: "You're not alone — here's what others are noticing" |
| Day 20 | Closing reminder | "Final day tomorrow — you're almost there. Your entries have been incredibly useful." |
| Days 22–24 | Exit interviews (35 min per participant, Zoom) | Explore patterns from entries; validate interpretations; probe the three known friction areas (meeting summaries, CRM, cold outreach) |
Dropout mitigation:
- Day 1 silence: Personal Slack message within 24 hours — offer to do a quick 5-minute screen share to resolve any dscout setup issues
- 2 missed entries: "No pressure — even a 30-second voice memo counts. We just want to hear your real experience."
- Day 4+ silence: Direct outreach from study lead; offer to switch to voice-memo entries or a simplified 2-question daily SMS form
- Recruit 15–16 participants to reliably hit 9–10 completions
Analysis Framework
Phase 1: Entry-level coding
For each diary entry, code across:
- Task type (meeting summary, CRM, email, research, other)
- Outcome (used successfully / used but edited heavily / abandoned / skipped preemptively)
- Sentiment (1–5 rating + qualitative tone)
- Friction type (output quality, trust, speed, discoverability, irrelevance)
- Workarounds (manual edits, reverting to prior tools, prompting attempts)
Phase 2: Individual adoption journeys
Map each rep's 21-day arc:
- Days 1–5: Initial use frequency and confidence
- Days 6–12: Friction peak — where do entries go negative or sparse?
- Days 13–21: Recovery, plateau, or abandonment — and what drove the trajectory?
Flag reps who show a "day 8 cliff" (a common pattern in SaaS adoption where initial curiosity drops before habit forms).
Phase 3: Cross-participant themes
- Which of the three known friction areas (meeting summaries, CRM auto-fill, cold outreach) appear most in diary entries — and how severe?
- What workarounds do multiple reps invent independently? (Signals a fixable product or onboarding gap)
- Do high-CRM-activity reps and low-activity reps show different adoption curves? (Segments the 800-seat rollout population)
- What language do reps use when Copilot works vs. fails? (Feeds messaging for the expansion business case)
Phase 4: Reporting
- Run cross-participant synthesis using
/research-synthesize - Build stakeholder presentation using
/research-readout— primary audience is VP of Sales and IT leadership who own the expansion decision - Deliverables: adoption journey map per segment, friction heatmap by task type, 3 onboarding recommendations