Is it safer to build an experimentation platform in-house for data privacy?

In-house solutions ensure that sensitive revenue data and customer PII stay within your own infrastructure, avoiding third-party cookie dependencies and vendor data breaches.

How has AI changed the cost of maintaining in-house software?

AI-accelerated development has drastically reduced the maintenance burden. Modern AI agents can handle refactors and upgrades in minutes, making the Total Cost of Ownership (TCO) for in-house tools much more competitive than in the pre-AI era.

Why is opportunity cost included in a Build vs Buy analysis?

Opportunity cost represents the lost revenue or growth from not having those same engineers work on core product features that directly drive business value.

Total Cost of Ownership

Should you build your own experimentation platform or buy a commercial solution? Compare the 3-year TCO including engineering effort and data privacy impact.

Staffing & Opportunity

Avg. Engineer Cost ($)

Alternative Return (%)

Include Opportunity Cost

Opportunity cost is currently excluded. Enable to see the impact on product roadmap velocity.

The "Build" Path (In-House)

Initial Build Effort (Hours - Year 1)

Maint. Year 2 (Hours)

Maint. Year 3 (Hours)

Annual Infrastructure Cost ($)

The "Buy" Path (Commercial)

Annual License Fee ($)

Implementation Fee ($)

Strategic Advantages

Data Privacy: Building in-house ensures sensitive revenue data and PII stay within your own infrastructure. No third-party cookie dependencies.
Security: Meet strict data residency and compliance (GDPR/CCPA) without relying on a vendor's security posture.
Hyper-Specialization: Off-the-shelf tools often struggle with non-standard interaction patterns (3D, hardware, or complex SPAs).
IP Value: If experimentation logic is your core differentiator, the code itself is a company asset.

3-Year Financial TCO

Favoring In-House Build

$26,502

Projected 3-year savings by building in-house.

Total Cost to Build

$118,498

Y1: $73,999Y2: $22,250Y3: $22,250

Total Cost to Buy

$145,000

Y1: $55,000Y2: $45,000Y3: $45,000

Need help deciding?

TCO is more than just licensing vs. salary. It's about opportunity cost, scalability, and long-term maintenance. I can help you conduct a formal Requirements Gap Analysis to see which path fits your specific tech stack and business goals.

Consult with Murat

Build vs Buy FAQ

Is it safer to build in-house for data privacy?

Yes. In-house solutions ensure that sensitive revenue data and customer PII stay within your own infrastructure. You avoid the risk of third-party cookie dependencies and vendor data breaches.

What is the biggest hidden cost of building?

Maintenance and "Technical Debt." While Year 1 build costs are obvious, the engineering hours required to keep the system running, update for new browsers, and add new features in Years 2 and 3 are often underestimated.

Has AI changed the 'Build vs Buy' calculation?

Fundamentally. The traditional "Buy" argument was built on the fear of a massive long-term maintenance burden. With AI-accelerated development, the cost of refactoring, upgrading dependencies, and debugging in-house tools has plummeted. Small teams can now maintain sophisticated internal platforms that previously required entire departments.

When should I definitely buy instead of build?

If you need to reach a high testing velocity tomorrow and your team has zero experience with statistical engine design. While AI makes building easier, commercial tools still provide the fastest possible "Time to Value" for teams that don't want to manage infrastructure at all.