Launch Timeline
Estimate when your project will be ready to launch. Answer a few questions and get a phase-by-phase timeline with built-in risk analysis.
Why estimate your launch timeline?
- Factor in real risks — not just optimistic developer estimates
- Align stakeholders around a data-backed launch date
- Identify schedule risks before they become delays
Industry Timeline Benchmarks
Based on CodeFormers project data from 40+ MVP launches in 2024-2025. Times reflect dedicated mid/senior development teams.
| Product Type | Avg (weeks) | Fast (P25) | Slow (P75) | Typical Team |
|---|---|---|---|---|
| SaaS B2B/B2C | 16 | 12 | 24 | 3-5 people |
| Marketplace | 24 | 18 | 36 | 4-6 people |
| Mobile App | 18 | 12 | 26 | 3-5 people |
| Internal Tool | 10 | 6 | 16 | 2-3 people |
| Landing + Waitlist | 4 | 2 | 6 | 1-2 people |
Updated Q1 2025. Source: CodeFormers internal project data (n=40+ MVP projects).
"The time-to-market calculator helped us realize we needed a bigger team or a smaller scope. We chose the latter and launched 8 weeks earlier."
"The phase breakdown was exactly like reality. The only surprise was that discovery took less time than we assumed."
Get Your Launch Timeline Report
Phase-by-phase timeline with risk assessment, resource needs, and milestone tracking.
Includes Gantt chart and critical path analysis
How the time-to-market calculator works
Define requirements
Select project type, complexity level, and must-have features.
Configure team & approach
Choose team size, engagement model, and development methodology.
Get your timeline
See estimated delivery date, sprint breakdown, and critical path milestones.
Frequently asked questions about time-to-market estimation
How does the time-to-market calculator work?
The calculator uses data from 40+ CodeFormers projects to estimate your timeline based on product type, team size, design readiness, technical decisions, and risk factors. The timeline is broken down into 6 phases: discovery, design, core development, feature development, testing, and launch preparation.
Do the estimates include a risk buffer?
Yes. The algorithm separately calculates a confidence level based on your selected risks and blockers. Factors like unclear requirements (-15%), incomplete team (-12%), or no designs (-5%) lower confidence, suggesting you add a 10-20% buffer to the timeline.
How long does it typically take to launch an MVP?
Based on CodeFormers data: SaaS MVP takes 10-14 weeks (team of 3-4), marketplace 15-23 weeks, mobile app 11-18 weeks, internal tool 6-9 weeks, and landing page 3-4 weeks. These ranges are for standard MVPs with mid/senior development teams.
What team composition is recommended?
The calculator suggests a team composition based on your product type. A typical SaaS MVP needs: Project Manager (50%), UX/UI Designer, Frontend Developer, Backend Developer, and QA Engineer. Smaller projects (landing, internal tool) can start with 1-2 people.
How does team size affect the timeline?
It depends on the velocity multiplier. A team of 1-2 has a 1.8x multiplier (slower), 3-4 is baseline 1.0x, 5-6 is 0.75x (faster), and 7+ is 0.65x. However, larger teams have more communication overhead, so the speedup is not linear.
What's the difference between this and the MVP Scope Calculator?
The MVP Scope Calculator helps decide WHAT to build — which features to include and what budget to allocate. The Time-to-Market Calculator answers WHEN — how many weeks the build will take, considering your team, design readiness, and risk factors.
What do the individual phases mean?
Discovery & Planning: requirements gathering, user stories. UX/UI Design: wireframes, mockups, prototypes. Core Development: architecture, database, auth, API. Feature Development: business feature implementation. Testing & QA: manual and automated tests. Launch Preparation: deployment, monitoring, documentation.
Can I use the calculator for an existing project?
Yes. Select 'Partial Codebase' or 'Migration / Refactor' in the existing code step. The 0.8x multiplier for partial code reflects time savings from existing components, while the 1.3x for migration accounts for additional refactoring overhead.