What “Problem Definition” Really Means in App Planning
Problem definition is the act of describing, in plain and testable terms, what user pain you are solving and under what conditions it happens. In app planning, it is not a slogan (e.g., “make productivity easier”) and it is not a feature list (e.g., “calendar, reminders, AI”). A good problem definition is a shared reference point that keeps screens, flows, and features aligned. It answers: who is struggling, what are they trying to do, what blocks them, and what “better” would look like in their real context.
A useful way to think about it: your app is a tool. Tools are chosen because they reduce effort, risk, time, confusion, or cost for a specific job. If you cannot state the job and the friction clearly, you will struggle to decide what to build first, what to cut, and how to measure whether you succeeded.
Problem vs. Solution (and Why Mixing Them Causes Rework)
Beginners often write a “problem statement” that is actually a solution statement. For example: “People need an app that scans receipts and auto-categorizes expenses.” That may be a solution. The underlying problem might be: “Freelancers lose billable time and miss deductions because they can’t reliably capture and categorize receipts while on the go.” When you define the problem at the right level, you unlock multiple possible solutions and can choose the simplest one that works.
Mixing problem and solution leads to premature design decisions. You might commit to scanning receipts before confirming whether the real pain is capture, categorization, retrieval, or reporting. Then you build a complex feature set and still fail because the main friction was something else (e.g., remembering to save receipts at all).
Characteristics of a Strong Problem Definition
Specific user and context: identifies who experiences the problem and in what situation (time, device, environment, constraints).
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Observable pain: describes what actually happens (missed tasks, duplicated work, errors, delays), not vague feelings.
Root cause oriented: points to why the pain occurs (information scattered, too many steps, unclear status, lack of reminders).
Neutral about solution: does not assume a particular feature or technology.
Testable: you can later check whether the problem is reduced using evidence (behavioral metrics, time saved, fewer errors, higher completion).
How to Define the Problem: A Practical Step-by-Step Process
The goal of this process is to produce a problem statement you can use to make product decisions and to define success criteria you can measure. You can do this even as a solo beginner, as long as you are disciplined about writing and validating assumptions.
Step 1: Choose a Narrow Target User Segment
Pick one primary user segment for the first version. “Everyone” is not a segment. A segment should be narrow enough that you can describe typical constraints and motivations.
Too broad: “Students”
Better: “First-year university students living off-campus who commute and juggle part-time work”
Too broad: “Small businesses”
Better: “Two-person home cleaning businesses that schedule jobs by phone and track payments manually”
Write your segment in one sentence and include at least one constraint (time pressure, low tech comfort, unreliable connectivity, shared device, etc.). Constraints often reveal the real problem.
Step 2: Describe the “Job to Be Done” in Plain Language
Write what the user is trying to accomplish, independent of your app. Use a verb and a clear outcome.
“Schedule cleaning jobs without double-booking and send confirmations quickly.”
“Track which assignments are due and finish them on time without last-minute panic.”
“Split shared household expenses fairly and settle up without awkward conversations.”
If you struggle to write this without mentioning app features, you are still thinking in solutions.
Step 3: Map the Current Workflow (As-Is) and Identify Friction Points
List the steps the user takes today to get the job done. Keep it short but concrete. Then mark where things go wrong.
Example (home cleaning business scheduling):
Customer calls or texts to request a date/time.
Owner checks a paper calendar or notes app.
Owner replies with available times.
Customer confirms.
Owner writes the job details in the calendar.
Owner sends address to cleaner (sometimes later).
After the job, owner records payment in a spreadsheet (sometimes days later).
Friction points might include: double-booking, forgetting to send details, losing messages, unclear job status, delayed payment tracking, and time wasted searching for information.
Step 4: Separate Symptoms from Root Causes (Use “5 Whys” Lightly)
Pick one major friction point and ask “why” until you reach a cause you can influence with product design. Do not overdo it; 3–5 layers is usually enough.
Example friction: “Double-booking happens.”
Why? Because the owner updates the calendar after confirming, not during the conversation.
Why? Because job details are scattered across texts and calls, and it’s slow to capture them.
Why? Because there is no single place to record requests and see availability in the same view.
Root cause candidate: “Scheduling information is fragmented and capture is too slow during live conversations.” That is more actionable than “double-booking.”
Step 5: Write the Problem Statement Using a Simple Template
Use a consistent format so you can compare ideas and avoid vague statements. Here are two templates you can choose from.
Template A (User + Job + Pain + Impact):
[User segment] is trying to [job], but [pain/root cause], which leads to [impact].Template B (Context + Trigger + Barrier + Outcome):
When [context/trigger], [user] can’t [desired action] because [barrier], resulting in [bad outcome].Example using Template A:
Two-person home cleaning businesses are trying to schedule jobs and keep clients informed, but scheduling details are fragmented across calls, texts, and a separate calendar, which leads to double-booking, missed details, and wasted admin time.Notice this does not mention “an app with a calendar.” It describes the problem in a way that multiple solutions could address.
Step 6: Add Boundaries (What You Are Not Solving Yet)
Boundaries prevent scope creep and make success criteria realistic. Write 3–6 “out of scope for v1” items. This is not a feature list; it’s a problem boundary list.
Not solving payroll or tax filing in v1.
Not building a full CRM; only basic client contact info needed for scheduling.
Not optimizing routes; only capturing addresses and job times.
Boundaries also help you avoid defining success criteria that depend on things you are not building.
What “Success Criteria” Means (and Why It’s Not Just Downloads)
Success criteria are the measurable signals that tell you whether your app is actually reducing the defined problem for the target users. They translate your problem definition into outcomes you can observe. Without success criteria, you can ship screens and features but still not know if you improved anything meaningful.
Success criteria should be tied to user outcomes (time saved, fewer errors, higher completion) and business viability (retention, activation, willingness to pay), but they must be chosen carefully so they reflect the problem you defined.
Outputs vs. Outcomes
Outputs: what you build (features, screens, integrations).
Outcomes: what changes for the user (fewer missed tasks, faster scheduling, less confusion).
A beginner trap is to treat outputs as success: “We built reminders, therefore we succeeded.” Real success is: “Users miss fewer deadlines because reminders are timely and actionable.”
Leading vs. Lagging Indicators
Lagging indicators confirm success after time passes (monthly retention, churn, revenue).
Leading indicators predict success earlier (activation rate, repeated use in first week, completion of a core task).
You typically need both. Lagging indicators keep you honest; leading indicators help you iterate quickly.
Good Success Criteria Are: Specific, Measurable, and Linked to the Core Problem
“Users love it” is not measurable. “Increase productivity” is too vague. Instead, define criteria that connect to the friction points you identified.
For the scheduling example, the core problem includes fragmentation and slow capture leading to double-booking and missed details. Success criteria might include:
Reduce double-booking incidents per month per business.
Reduce time from initial request to confirmed booking.
Increase percentage of bookings that include complete job details (address, time, notes) at the moment of confirmation.
Increase repeat usage: number of bookings created per active business per week.
How to Create Success Criteria: A Practical Step-by-Step Process
Step 1: Identify the “North Star Outcome” for the First Version
Pick one primary outcome that best represents solving the problem. It should be something users get value from repeatedly, not a one-time setup action.
Examples:
Scheduling app: “Confirmed bookings created without conflicts.”
Study planner: “Assignments completed by their due date.”
Expense splitting: “Expenses settled accurately within a week.”
Write it as a behavior/outcome, not a feature.
Step 2: Define 3–6 Supporting Metrics That Explain the North Star
Supporting metrics help you diagnose what’s working and what isn’t. Mix quality, speed, and reliability measures.
Example (confirmed bookings without conflicts):
Conflict rate: number of bookings that overlap / total bookings.
Time to confirm: median minutes from request created to booking confirmed.
Data completeness: % of bookings with required fields filled at creation.
Follow-up messages: average number of back-and-forth messages needed to finalize details (proxy for clarity).
Weekly active businesses: count of businesses creating at least one booking per week.
Choose metrics you can realistically track. If you cannot measure “messages,” use an in-app proxy like “number of edits after creation” or “number of times booking details are changed.”
Step 3: Set Baselines and Targets (Even If They Are Estimates)
Targets make success criteria actionable. If you have no baseline yet, start with an assumption and plan to revise after a small pilot.
Write targets in a time-bound way:
Within 30 days of first use, reduce conflict rate to under 1% of bookings.
Within 2 weeks, median time to confirm a booking is under 5 minutes for active users.
Within 1 week, 80% of bookings are created with complete required details.
Be careful: targets should be ambitious but plausible. If your target is unrealistic, you will either ignore it or chase the wrong changes.
Step 4: Define “Activation” as the First Moment of Real Value
Activation is not “sign up.” It is the first time a user experiences the core value related to the problem. Define it clearly so you can measure whether new users reach value quickly.
Examples:
Scheduling app activation: “User creates and confirms their first booking with complete details and no conflict.”
Study planner activation: “User adds an assignment with a due date and completes it before the due date.” (You may need a shorter proxy for early testing, such as “adds assignment and marks it done.”)
Expense splitting activation: “User creates a group, adds at least two expenses, and records a settlement.”
Activation should be a measurable event or sequence of events. If it takes too long to reach, define an early proxy but keep the true activation definition documented.
Step 5: Add Guardrail Metrics to Prevent “Winning” the Wrong Way
Guardrails ensure that improving one metric does not harm user experience or trust. Choose 2–4 guardrails relevant to your app’s risk.
Common guardrails:
Error rate: crashes, failed saves, sync conflicts.
Support burden: number of help requests per active user.
Uninstall rate: especially within the first 7 days.
Data integrity: duplicate records, missing required fields after edits.
Trust signals: for finance/health apps, track user-reported inaccuracies.
Example: If you reduce “time to confirm” by removing confirmation steps, you might increase errors. A guardrail like “booking edit rate within 24 hours” can catch that.
Step 6: Write Success Criteria as a Checklist You Can Review Weekly
Turn your metrics into a short checklist. This makes it usable during planning and iteration.
Success Criteria (v1, first 60 days after launch to pilot users): 1) North Star: At least 200 conflict-free confirmed bookings created. 2) Activation: 60% of new businesses create and confirm a complete booking within 24 hours. 3) Quality: Conflict rate < 1%. 4) Speed: Median time to confirm < 5 minutes. 5) Guardrail: Booking edit rate within 24 hours < 10% and crash-free sessions > 99.5%.Even if the numbers are placeholders, the structure forces clarity.
Connecting Problem Definition to Screens and Features (Without Repeating Earlier Planning Work)
Once you have a problem statement and success criteria, you can evaluate any proposed screen or feature by asking two questions:
Does this directly reduce the root cause or major friction?
Which success metric will it move, and how?
If you cannot answer both, the item is likely a distraction for the first version.
Example: Feature Triage Using Success Criteria
Suppose you are planning the scheduling app and considering these ideas:
Color themes
One-tap “Create booking” with required fields
Client chat inside the app
Automatic conflict detection
AI that predicts best time slots
Evaluate them against the problem and metrics:
One-tap create booking: likely improves time to confirm and data completeness.
Automatic conflict detection: directly reduces conflict rate (North Star quality).
Client chat: may reduce back-and-forth, but adds complexity; only prioritize if “follow-up messages” is a major pain and you can measure improvement.
AI time slot prediction: may help later, but not necessary to reduce fragmentation; hard to validate early.
Color themes: not tied to success criteria; can wait.
This approach prevents building impressive features that do not solve the defined problem.
Common Mistakes and How to Fix Them
Mistake 1: Defining the Problem as “Lack of an App”
“There is no app for X” is not a problem; it is a market observation. Users rarely suffer because an app does not exist; they suffer because a job is hard with current tools.
Fix: Rewrite the statement to describe the job, friction, and impact. Compare current alternatives and identify what fails in real usage.
Mistake 2: Writing Success Criteria That Only Measure Popularity
Downloads, page views, and social followers can be useful, but they do not prove the problem is solved. You can get downloads with good marketing and still deliver no value.
Fix: Tie at least one metric to the core job outcome (completion, accuracy, time, reduction in errors). Use popularity metrics as secondary signals.
Mistake 3: Choosing Metrics You Cannot Measure
Beginners sometimes pick metrics like “stress reduced” without a way to measure it. Or they choose metrics that require data they do not collect.
Fix: Use measurable proxies. If you care about stress, measure behaviors that correlate with it (missed deadlines, last-minute completions, number of reschedules). If you later add surveys, treat them as supplemental.
Mistake 4: Setting Targets Without Time Frames
“Increase retention” is not actionable without a time window and a definition of retention.
Fix: Define the period and event: “Day-7 retention: % of users who complete the core action again within 7 days.” Then set a target.
Mistake 5: Solving Multiple Problems at Once
If your problem statement includes “schedule jobs, manage employees, handle payments, do marketing,” you are likely trying to build a suite, not a first app. Success criteria become impossible because you cannot tell what caused improvements.
Fix: Pick one primary problem for v1 and set boundaries. Keep other problems as future opportunities.
Worked Example: From Vague Idea to Problem Statement and Success Criteria
Initial Idea (Too Vague)
“An app to help people eat healthier.”
Refine the User Segment
“Office workers who buy lunch near their workplace and want healthier choices but decide quickly under time pressure.”
As-Is Workflow and Friction
At lunch time, they search nearby options.
They check menus quickly, often incomplete or outdated.
They guess what is healthy based on names.
They choose fast, often defaulting to familiar meals.
Friction: information is unclear and decision time is short; they cannot confidently identify healthier options quickly.
Problem Statement (Template B)
When office workers have 10 minutes to choose lunch near work, they can’t quickly identify genuinely healthier menu options because nutrition information is unclear or inconsistent, resulting in defaulting to less healthy choices and frustration.North Star Outcome
“Healthy lunch choices made with confidence.”
Supporting Metrics
Decision time: median time from opening the app to selecting a meal option.
Confidence proxy: % of selections where the user views key nutrition details before choosing.
Repeat behavior: number of lunch selections per user per week.
Quality guardrail: % of menu items reported as inaccurate/outdated.
Targets (Example)
Within 14 days, median decision time under 2 minutes.
Within 30 days, 50% of active users make 3+ lunch selections per week.
Inaccuracy reports under 2% of viewed items (guardrail).
Notice how these criteria focus on the defined problem (fast, confident decisions under time pressure) rather than broad goals like “eat healthier” that are difficult to attribute to the app alone.
Documentation You Should Produce for This Chapter’s Work
To make your problem definition and success criteria usable during development planning, create these artifacts as short text documents:
Problem statement (1–3 sentences): using one of the templates.
Root causes list: 3–5 bullets explaining why the problem happens.
Boundaries: what is not being solved in v1.
North Star outcome: one line.
Success criteria checklist: activation definition, 3–6 metrics, targets, and 2–4 guardrails.
Keep these visible while you plan screens and features. When you face trade-offs, return to them and choose the option that most directly improves the defined outcomes.
