MVP testing doesn't require enterprise-level coverage. Learn which types of testing matter for early-stage products and what you can skip until later.
September 19, 2024 9 min read
# Testing Your MVP: What's Actually Necessary
Slug: testing-your-mvp-whats-necessary
Date: 2024-04-20
Tag: Software Development
Meta Description: MVP testing doesn't require enterprise-level coverage. Learn which types of testing matter for early-stage products and what you can skip until later.
---
You're building an MVP. Speed matters. Every week in development delays validation. Your development team mentions testing, and you wonder: is this essential infrastructure or scope creep?
Testing is real work with real value. But the testing appropriate for an MVP differs significantly from what a mature product needs. Knowing which testing matters at your stage helps you allocate resources appropriately.
This guide covers what testing means, which types matter for MVPs, and how to have informed conversations with your development team.
What Software Testing Actually Is
Testing verifies that software works correctly. That sounds obvious, but the methods vary enormously.
Manual Testing
Someone uses the product and checks if it works. Click buttons, fill forms, verify results. This is intuitive but slow and inconsistent.
Manual testing catches obvious problems but misses subtle bugs. It depends on the tester's attention and doesn't scale—testing every scenario manually takes enormous time.
Automated Testing
Code that tests other code. Developers write programs that verify the product behaves correctly. These tests run automatically, repeatedly, without human attention.
Stop planning and start building. We turn your idea into a production-ready product in 6-8 weeks.
Automated tests are consistent—they catch the same bugs every time. They're fast—running thousands of tests takes seconds. They enable confidence—developers can change code knowing tests will catch mistakes.
The downside: automated tests require time to write and maintain. This is investment that pays off over time but costs upfront.
Types of Automated Testing
Different types of tests serve different purposes.
Unit Tests
Unit tests verify individual pieces of code work correctly. A function that calculates prices gets tested with various inputs to verify correct outputs.
What they catch: Logic errors in isolated code. If a function is supposed to add 10% tax, unit tests verify it does.
What they miss: Problems with how pieces fit together. A function might work perfectly but receive wrong inputs from other code.
Effort: Relatively quick to write and maintain.
Integration Tests
Integration tests verify that components work together correctly. If one function passes data to another, integration tests verify the handoff works.
What they catch: Miscommunication between components. Incorrect data formats, missing fields, wrong assumptions about how systems interact.
What they miss: User-facing issues. Components might integrate correctly but produce confusing interfaces.
Effort: More setup than unit tests, but still manageable.
End-to-End (E2E) Tests
End-to-end tests simulate real users. Automated browsers click buttons, fill forms, and verify the complete user experience works.
What they catch: Anything a user would experience. If a button doesn't work, E2E tests fail. If a flow is broken, E2E tests fail.
What they miss: Nothing user-facing, but they're slower and more fragile than other tests.
Effort: Significant to write and maintain. E2E tests break when the interface changes, requiring updates.
Testing Philosophy for MVPs
Enterprise software has comprehensive test coverage. MVPs don't need that—but they do need some testing.
The MVP Testing Principle
Test what matters most. Skip what can wait.
For MVPs, "what matters most" typically means:
Critical user flows: Signup, login, core product actions, payment
Data integrity: User data saved correctly, calculations accurate
Comprehensive coverage: Testing every possible path
Why Not Skip Testing Entirely?
Some founders argue: "We're moving fast. We'll add tests later."
Tests rarely get added later. By the time you have users, you're fighting bugs, adding features, and handling emergencies. Retroactive testing competes with every other priority.
More importantly, bugs in production are expensive. Finding and fixing a bug during development takes minutes. Finding the same bug after users report it takes hours—plus the damage to user trust.
A small testing investment prevents larger problems.
Why Not Test Everything?
Comprehensive testing is expensive. Writing tests takes time. Maintaining tests takes time. Running large test suites takes time.
For an MVP, extensive testing is premature optimization. You might throw away features that don't validate. You might pivot to different functionality. Testing code that gets deleted is waste.
Balance matters. Test enough to prevent embarrassing bugs. Don't test so much that you delay validation.
What to Test in Your MVP
Specific guidance for early-stage products:
Always Test
Authentication flows. Login, signup, password reset. If users can't authenticate, nothing else matters. If authentication has bugs, security problems follow.
Core product actions. Whatever makes your product valuable. If you're a scheduling app, test that appointments actually save and display correctly. If you're a payment app, test that transactions process correctly.
Data operations. Creating, updating, and deleting data. If a user saves information and it disappears, trust is lost.
Payment processing. If you charge money, test that charges work, amounts are correct, and failures are handled gracefully. Payment bugs are especially damaging.
Test If Resources Allow
Email and notifications. Test that emails send and contain correct information. Missing notifications frustrate users.
Third-party integrations. Test that external services connect correctly. If your product depends on external APIs, verify those connections work.
Permission systems. Test that users can access what they should and can't access what they shouldn't. Permission bugs can be security issues.
Can Wait Until Later
Edge cases. What happens with unusual inputs or extreme values? These matter eventually but rarely break MVP validation.
Performance testing. How fast does the product handle high load? Important for scale, not for proving product-market fit.
Cross-browser exhaustive testing. Major browsers should work. Testing every browser version combination can wait.
Visual regression testing. Automated checks that screens look correct pixel-by-pixel. Useful for mature products, overkill for MVPs.
How Much Testing Is Enough?
There's no universal percentage. "80% test coverage" means little without context. Some code is critical; some is trivial.
A Practical Framework
Critical paths need automated tests. If a bug here would break the product for all users, write tests.
Important features need some tests. Not comprehensive, but enough to catch obvious breaks.
Convenience features can rely on manual testing. Spot-check during development. Add automated tests if problems recur.
Warning Signs: Too Little Testing
Deployments frequently break working features
The same bugs keep recurring
Developers are afraid to change code
User reports reveal bugs that should have been caught
Warning Signs: Too Much Testing
Test writing significantly delays features
Tests break constantly from minor changes
More time fixing tests than fixing bugs
Testing edge cases before core features are validated
New feature verification. Before any automated tests exist, someone needs to verify the feature works.
Exploratory testing. Trying unusual combinations, edge cases, and unexpected paths. Humans are better at creative exploration.
User experience evaluation. Does the flow feel right? Is anything confusing? Humans judge experience better than code.
Visual appearance. Does it look correct? Automated tests can check structure; humans verify aesthetics.
Balancing Manual and Automated
For MVPs, start with manual testing. As features stabilize, add automated tests for the most critical paths. Expand automated coverage as the product matures.
Manual testing catches problems during active development. Automated testing prevents regression—ensuring old problems don't return.
What to Expect From Your Development Team
Professional developers should include testing in their process. Here's what to look for:
Included in Estimates
Testing time should be part of feature estimates, not separate. "This feature takes 3 days" should include testing.
If estimates never include testing, testing isn't happening.
Test Coverage Discussion
Your team should be able to explain what's tested and what isn't. They should make conscious decisions about testing priorities.
If the team can't articulate testing strategy, they may not have one.
CI/CD Integration
Tests should run automatically when code changes. Breaking changes should block deployment.
If tests exist but don't run automatically, their value is limited.
Test Maintenance
As features change, tests need updates. Budget for this in ongoing development.
Unmaintained tests become false positives (failing when nothing is wrong) or false negatives (passing when things are broken).
Questions to Ask About Testing
Useful questions for development discussions:
"What's our testing approach for this project?"
The answer should describe which types of testing are used and for what.
"What happens if this feature breaks after launch?"
Good answers involve tests catching problems before users see them.
"How confident are you that this won't break existing features?"
Confidence should come from automated tests, not just hope.
"What's not tested, and why?"
Conscious decisions about testing priorities are fine. Not thinking about testing is concerning.
"How do we know when something breaks?"
There should be monitoring and alerting beyond just tests.
Common Testing Mistakes
Awareness of typical problems helps you recognize them.
Testing After Everything Else
Teams that leave testing for "when we have time" rarely find that time. Testing should be integrated into development, not scheduled separately.
Testing Implementation Details
Tests that verify how code is written (rather than what it does) break whenever code is refactored. Good tests check behavior, not implementation.
Flaky Tests
Tests that sometimes pass and sometimes fail for no clear reason. Teams learn to ignore them, making all tests less valuable.
No Prioritization
Testing everything equally means critical features get the same coverage as trivial ones. Testing should focus on what matters most.
Tests as Security Theater
Having tests isn't the same as having useful tests. Tests that don't verify important behavior provide false confidence.
Testing and Development Speed
Testing and speed aren't enemies. Proper testing actually accelerates development.
Short-Term Costs
Writing tests takes time. For any individual feature, skipping tests is faster.
Long-Term Benefits
Developers move faster when tests catch mistakes. They're not afraid to change things. They're not debugging problems that tests would have caught.
The payoff timeline varies. For a throwaway prototype, tests might never pay off. For a product you'll iterate on for months, testing investment typically pays off within weeks.
The MVP Balance
For MVPs: test enough that you're not constantly firefighting bugs, but don't let testing delay validation. Expand testing as the product matures.
Key Takeaways
Testing matters for MVPs, but the scope should match your stage.
Test critical paths: Authentication, core features, payments, data operations. Bugs here are disasters.
Skip comprehensive coverage: Edge cases, performance testing, and exhaustive scenarios can wait until you've validated product-market fit.
Expect testing in estimates: Development time should include testing time. If it doesn't, testing isn't happening.
Balance manual and automated: Manual testing catches problems during development. Automated testing prevents regressions.
Test what you'll keep: Don't extensively test features you might throw away. Increase coverage as features stabilize.
At NextBuild, we include appropriate testing in every MVP—enough to prevent embarrassing bugs without delaying validation. If you're unsure about the right testing balance for your product, we can discuss what makes sense for your stage.
Document automation can cut drafting time from 3 hours to 15 minutes. But most MVPs fail by building too much too soon. Here are the 5 features that actually matter.
