Customer discovery
Tailored hypotheses + questions
Generates a run-specific discovery kit (hypotheses, screening, interview questions) from the MVB packet.
Loaded from run #16
A digital platform that helps individuals plan their tasks and schedule on a day-by-day basis. It aims to simplify daily prioritization, time allocation, and follow-through.
People struggle to translate goals and responsibilities into a realistic daily plan, leading to missed priorities, overwhelm, and inefficient use of time.
Generate discovery kit
This uses the OpenAI model configured on the server. Run-specific generation is recommended.
Ready to generate a tailored kit from this run.
Hypotheses
These are the explicit assumptions we’re testing in interviews.
H1: Hybrid knowledge workers in the ICP experience day-to-day planning failure (not long-term goal setting) as a top-3 productivity pain, driven by meeting churn and shifting priorities, resulting in missed priorities at least 2 days/week.
problemcriticalIf daily planning pain is not acute and frequent, users will not change behavior or adopt a new daily-engagement tool.
Success signals
- >=70% of interviewed ICP users describe daily planning as a top-3 pain without prompting
- >=60% report missing a key priority at least 2 days/week due to unrealistic plans or meeting churn
- Users can cite recent concrete examples (last 7 days) of dropped tasks or late deliverables tied to planning breakdown
Failure signals
- <40% rank daily planning in top-3 pains; they attribute issues mainly to strategy/clarity or workload volume
- Most users say their current system works 'well enough' and failures are rare (<1 day/week)
- Examples are vague or historical, not recent and recurring
How to test
Run 15–20 semi-structured interviews with ICP individuals (not managers) recruited from 50–500 person firms using Google Calendar. Ask them to walk through yesterday/today planning, quantify missed priorities per week, and identify root causes. Validate with a 2-minute follow-up survey to quantify frequency.
H2: A calendar-as-source-of-truth workflow (time-blocking tasks into Google Calendar) is perceived as more realistic and trustworthy than list-only planning, and users will adopt it if it takes <=5 minutes/day to create and <=2 minutes to adjust after disruptions.
workflowhighThe product’s core differentiation is calendar-first planning; if users won’t time-block or won’t maintain it, the approach fails.
Success signals
- >=60% say they would prefer a time-blocked day plan over a task list if setup/adjustment is fast
- In a prototype test, median time to produce a day plan is <=5 minutes and users rate it >=4/5 for realism
- >=50% say they would adjust the plan at least once during the day if it takes <=2 minutes
Failure signals
- Users reject time-blocking as too rigid or stressful even with fast setup
- Prototype tests show median planning time >8 minutes or realism rating <3/5
- Users say they would not maintain adjustments; they revert to ad-hoc lists
How to test
Conduct 8–12 moderated usability sessions using a clickable prototype or concierge flow: import a sample calendar, capture 10–15 tasks, and have users create a plan for tomorrow. Time the flow, collect realism/trust ratings, and simulate a disruption (new meeting) to measure adjustment time and willingness.
H3: Users will trust AI-assisted scheduling only if changes are explainable and controllable (estimates, buffers, constraints, and user rules), and this reduces anxiety compared to opaque auto-schedulers.
solutioncriticalTrust and perceived control are prerequisites for adoption in scheduling; without them, users will churn or avoid automation.
Success signals
- >=70% explicitly request or positively react to 'why this moved' explanations and rule controls
- In A/B concept tests, explainable+controllable scheduling is preferred over opaque auto-scheduling by >=2:1
- Users report reduced anxiety/greater confidence (>=4/5) when they can lock blocks, set buffers, and approve changes
Failure signals
- Users prefer full manual control and see AI scheduling as unnecessary or risky
- No meaningful preference between explainable vs opaque scheduling concepts
- Users still report high anxiety (<3/5 confidence) even with controls
How to test
Run concept tests with two short demos: (A) opaque auto-scheduler, (B) explainable scheduler with rules (locks, buffers, constraints, approval). Collect preference, trust, and anxiety ratings; ask users to narrate what would make them comfortable using it daily.
H4: The strongest early adopters are individual contributors and managers who already live in Google Calendar and handle 15–40 tasks/week; they will engage daily (>=4 days/week) if the tool reduces rescheduling and protects deep work.
customerhighDaily engagement is required for retention; identifying the sub-segment with the highest pull reduces go-to-market risk.
Success signals
- In interviews, a clear sub-segment emerges that already time-blocks or wants to, and reports frequent meeting churn
- In a 2-week pilot, >=40% of invited users are active >=4 days/week
- Users cite 'protecting deep work' and 'less rescheduling' as primary reasons to keep using it
Failure signals
- Engagement concentrates only in a niche (e.g., productivity enthusiasts) not representative of the ICP
- 2-week pilot shows <20% active >=4 days/week
- Users say the tool is nice-to-have but not part of their daily routine
How to test
Recruit 20–30 users across roles (ICs, managers) in the ICP for a lightweight pilot (concierge or MVP). Track active days/week, number of plan adjustments, and self-reported deep-work protection. Segment results by role, meeting load, and task volume.
H5: ICP users will pay $6–10/user/month for Pro if the product saves at least 2 hours/week or measurably reduces missed priorities, and buyers (Ops/People/IT) will consider $15–30/user/month for team features (admin, policy controls, consent-based coordination).
pricingmediumWithout willingness to pay at target price points, the business model and positioning (individual vs team) may need to change.
Success signals
- >=30% of interviewed users indicate willingness to pay within $6–10/month after seeing the concept and value framing
- >=3 buyer-role interviews (Ops/People/IT) express interest in a team plan and name a budget owner/process
- In a pricing test, Pro price sensitivity clusters around $8–12 with clear value thresholds (time saved, fewer misses)
Failure signals
- Most users anchor to free or <$5/month and cannot articulate a value threshold
- Buyer roles say this is not a budget category or would require bundling into existing suites
- Team plan interest is weak unless priced near consumer levels
How to test
Run 15–20 pricing interviews using a value-based script and a Van Westendorp or Gabor-Granger exercise after a demo. For buyers, test willingness to run a paid pilot and identify procurement/security requirements and budget source.
H6: The most efficient initial acquisition channel is Google Workspace-centric distribution (Google Workspace Marketplace + targeted outreach to Ops/IT/People leaders) because the product’s core integration is Google Calendar/Gmail and adoption benefits from admin-enabled rollout.
channelmediumIf distribution is expensive or slow, CAC will be too high for $6–10/user/month and early traction will stall.
Success signals
- Outbound to 50–500 person firms yields >=10% positive reply rate for discovery when framed around Google Calendar planning pain
- At least 3 companies agree to a pilot via an Ops/IT/People sponsor within 6 weeks
- Marketplace listing (or waitlist) drives qualified inbound with >=5% conversion to demos
Failure signals
- Outbound reply rates <3% and sponsors deflect to 'individual choice' with no rollout path
- Security/admin concerns block pilots consistently
- Marketplace/inbound traffic is low-quality or converts poorly (<1% to demos)
How to test
Run a 4-week channel sprint: (1) 200-account outbound sequence to ICP firms with two personas (Ops/People/IT) and two messages (burnout/deep work vs execution predictability). (2) Create a Marketplace pre-launch page or integration landing page and measure conversion to demo. Track pilot commitments and blockers.
Screening questions
Use these to qualify people before scheduling a call.
In the last 14 days, did you have a workday where you started with a to-do list but ended the day missing at least one top priority because the day got reshuffled?
Qualifies if: Yes, at least once in the last 14 days.
Which best describes your role and work context?
Qualifies if: Hybrid knowledge worker at a 50–500 person company.
What tools did you use in the last 7 days to manage your schedule and tasks? (Select all that apply)
Qualifies if: Uses Google Calendar and/or Gmail weekly for work planning.
About how many work tasks did you personally track or complete in the last week (excluding recurring meetings)?
Qualifies if: Selected 15–40 or 41+ tasks last week.
In the last 30 days, did you try any method to time-block tasks on your calendar (manually or with a tool)?
Qualifies if: Yes, attempted time-blocking at least once in the last 30 days.
Interview plan
20 minutes. Start with a real recent incident. Avoid hypotheticals.
Outline
20 minutes
- 0–2 min — Warm-up: role, context, “good” looks like
- 2–10 min — Last time it happened: story + steps
- 10–15 min — Tools + alternatives + what broke
- 15–19 min — Value: impact, willingness to pay, buyer process
- 19–20 min — Close: referrals + follow-up
Q1: Think about the most recent workday (within the last 7 days) that felt chaotic or unproductive. Walk me through that day from the moment you started planning to the end of the day.
Reconstructs a real incident to identify breakdown points in day-by-day planning and downstream impact on execution predictability.
H1H6
Follow-ups
- What were the top 1–2 outcomes you intended to finish that day, and what actually happened?
- What specifically caused the plan to change (meetings, urgent requests, unclear priorities, underestimation, context switching)?
- What did you do in the moment to recover (replan, push tasks, work late, drop items)?
Q2: In the last 7 days, tell me about the last time you tried to turn your task list into a realistic schedule on your calendar. How did you do it step by step?
Surfaces current workflow, friction, and whether calendar-first planning is already a desired behavior.
H1H3
Follow-ups
- Where did the tasks come from (email, Asana/Jira, notes, Slack), and how did they get into your plan?
- How did you decide durations/estimates and buffers, and what was hardest about that?
- What part took the most time or felt most annoying?
Q3: Tell me about the most recent time (within the last 14 days) your calendar changed unexpectedly and it forced you to replan your day. What did you move, and how did you decide what to sacrifice?
Tests the need for fast, low-anxiety rescheduling with user control and reveals prioritization rules used in practice.
H1H3H6
Follow-ups
- What did you reschedule first, and what did you avoid moving (and why)?
- Did any tool help you replan, or was it mostly manual?
- What was the consequence (missed deadline, lower quality, after-hours work, stakeholder impact)?
Q4: In the last 7 days, describe a specific task that ‘fell through the cracks’ (forgotten, started too late, or never scheduled). How did it slip, and when did you notice?
Identifies failure modes of follow-through and whether daily engagement/review would be valuable.
H1H2
Follow-ups
- Where was that task originally captured (email, chat, tool, mental note)?
- What reminder or checkpoint would have prevented it?
- What did you do afterward to prevent a repeat (if anything)?
Q5: Think about the last time you used an auto-scheduling or ‘smart’ planning feature (e.g., Motion, Todoist scheduling, Notion Calendar, Google suggestions). What happened, and how did you feel about the changes it made?
Validates positioning against opaque auto-schedulers and probes what ‘explainable and controllable’ must mean to reduce anxiety.
H3H2
Follow-ups
- What did it do that you liked, and what did it do that you disliked?
- Did you override it? If yes, what exactly did you change?
- What would it need to show/explain for you to trust its scheduling decisions?
Q6: In the last 7 days, tell me about a time you protected deep work (or failed to). What did you try, and what got in the way?
Connects day planning to meeting creep/burnout and tests whether time-blocking with constraints/buffers is a must-have.
H1H3H6
Follow-ups
- Did you block time on your calendar? If yes, did it hold or get overridden?
- What rules do you wish your calendar followed automatically (buffers, no-meeting windows, focus time limits)?
- Who/what typically breaks your plan (clients, execs, teammates, emergencies)?
Q7: Think about the last time you hesitated to connect a tool to your Google Calendar/Gmail or share scheduling/task data. What were you worried would happen?
Directly tests trust barriers and privacy expectations using a real incident rather than opinions.
H4
Follow-ups
- What data felt most sensitive (meeting titles, attendees, email content, task names, availability)?
- What permissions or controls would have made it acceptable (scopes, on-device processing, redaction, audit logs)?
- Would your company require IT/security review for this? What did that process look like last time?
Q8: In the last 30 days, have you paid for (or requested budget for) any productivity/planning tool? Tell me about the most recent purchase decision and what triggered it.
Validates willingness to pay and identifies buying triggers, decision-makers, and price sensitivity grounded in recent behavior.
H5H2
Follow-ups
- What alternatives did you compare, and what made you choose (or reject) them?
- What would have to be true for you to pay $6–10/month personally vs. ask for a team plan?
- What metric would justify the spend (time saved per week, fewer missed deadlines, less after-hours work)?
Scripts + templates
These should match the specific hypotheses above.
Intro script
Hi—thanks for taking 20 minutes. I’m researching how hybrid knowledge workers plan their day when the calendar is already packed and priorities shift. I’m not selling anything today; I’m trying to understand your current workflow and what breaks. Quick context: I’m exploring a calendar-first day planner that turns tasks into realistic time blocks using transparent assumptions (estimates, buffers, rules) so your schedule stays current without constant manual rescheduling. I’d love to learn: (1) how you plan a typical day/week, (2) where things fall apart, (3) what you’ve tried, and (4) what a ‘better’ solution would need to do to earn daily use. If it’s okay, I’ll ask a few detailed questions and I may share a couple of concept prompts near the end to get your reaction. Before we start: what’s your role, what tools are in your stack (Google Calendar/Gmail, task tools), and what does a ‘busy week’ look like for you?
Recruit email
Subject: Quick research chat on daily planning in Google Calendar (15–20 min)
Hi {{FirstName}},
I’m doing user research with hybrid knowledge workers at {{Company}}-type teams who live in Google Calendar/Gmail and juggle shifting priorities.
I’m exploring a calendar-first day planner that converts task lists into realistic time-blocked days using transparent assumptions (estimates, buffers, rules) so schedules stay current without constant manual rescheduling.
Would you be open to a 15–20 minute call to share how you currently plan your day and what’s frustrating about it? I’m not selling anything—just trying to understand workflows and pain points.
If yes, what does your availability look like this week? I can also send a couple of time options.
Thanks,
{{YourName}}
{{Title/Org}}
{{LinkedIn or website (optional)}}LinkedIn DM
Hi {{FirstName}}—I’m researching how hybrid knowledge workers plan day-by-day when Google Calendar is packed and priorities shift. I’m exploring a calendar-first planner that time-blocks tasks with transparent rules (not opaque auto-rescheduling). Would you be open to a 15–20 min chat to share your current workflow and what breaks? Not selling—pure research.Call notes template
Participant - Name: - Title/Function: - Company/Industry: - Company size (50–500?): - Work mode (hybrid/remote/on-site): - Primary tools (Google Calendar/Gmail + task tools): - Meeting load (hrs/day or % of week): - Tasks/week (estimate): 1) Current workflow (day-by-day) - How do they capture tasks? (email, chat, meetings, docs) - Where do tasks live? (Asana/Trello/Jira/Sheets/Todoist/etc.) - How do they plan the day? (morning, night before, weekly) - Do they time-block? How often? - What triggers replanning? (new meetings, urgent requests, client changes) 2) Pain + impact - Top 3 frustrations: - Recent example of a day that went off the rails: - Consequences: missed priorities, late deliverables, stress, after-hours work: - Who else is impacted? (manager/team/clients) 3) Existing solutions tried - Tools used now and why: - What’s ‘good enough’ today: - What’s missing: - Experience with Notion-style DIY vs auto-schedulers (e.g., Motion): - Biggest reason they stopped/avoided a tool: 4) Requirements for a better solution - Must-have capabilities: - Non-negotiables (control, explainability, privacy): - Preferred interaction model (rules, prompts, manual override): - Tolerance for automation (low/med/high): - Data access comfort (calendar only vs email/tasks too): 5) Concept reactions (if shown) - Reaction to: calendar-as-source-of-truth + task-to-time-block conversion: - Reaction to: transparent assumptions (estimates, buffers, constraints): - Reaction to: user-controlled rules (e.g., protect deep work, no meetings after 4pm): - Reaction to: lightweight follow-through (focus flow, end-of-day review): - Biggest concern/anxiety: 6) Adoption + pricing - Would they use it daily? Why/why not: - Personal pay vs expensed vs team purchase: - Price sensitivity ($6–10 Pro; $15–30 Enterprise): - Buying path: who decides, security review, IT involvement: 7) Pilot interest - Would they try a 2-week pilot connected to Google Calendar? - What would success look like? (time saved, fewer missed priorities, less after-hours) - Any blockers to connecting data? Scorecard (0–3 each) - Acute pain + current workaround: - Calendar-first fit (Google stack + meeting load): - Task volume + complexity match: - Willingness to change behavior (daily engagement): - Trust + privacy comfort: - Differentiation pull vs existing tools: - Ability to pay / buying path: - Total ( /21 ): Key quotes - Quote 1: - Quote 2: Top insights - Insight 1: - Insight 2: Next steps - Follow-up needed: - Candidate for pilot? (Y/N): - Notes: