Product launch readiness checklist: QA, performance, UAT and compliance

What launch readiness means

A product is launch-ready when it does what users need, stays fast under real traffic, protects their data and has a team ready to support it. Most launches that go wrong fail on day one because of bugs, slow pages or confused users, not because the idea was poor.

1. Define 'ready' before you test

• List the critical user journeys that must work flawlessly (sign-up, payment, the core task).
• Set measurable thresholds: response times, error rates, crash-free sessions and accuracy targets for AI features.
• Agree who makes the go / no-go call and what evidence they need.

2. Product quality assessment

• Review the build and release process, coding standards and documentation.
• Check test coverage on the critical journeys and the gaps that remain.
• Confirm monitoring, logging and alerting are in place before users arrive.

3. Functional and regression testing

• Test every critical journey end to end, on the browsers and devices your users have.
• Automate regression tests for the core flows so every release is checked the same way.
• Test edge cases: empty states, failed payments, slow networks, expired sessions.

4. Load and performance testing

• Model peak traffic, such as a launch announcement or month-end usage, not the daily average.
• Run load, stress and soak tests, and find the breaking point before customers do.
• Test from the regions and network conditions your users are in.
• Fix the slowest queries and pages, then re-test.

5. User acceptance testing (UAT)

• Recruit real users from the target segment, not only internal staff.
• Give them scripted tasks plus time to explore, and track every issue to closure.
• Measure task completion and confusion, not only bugs.

6. Security and data protection

• Check authentication, permissions and data access for every role.
• Review where personal data goes, including logs, analytics and third-party tools.
• Confirm notice, consent and breach-response steps meet the laws that apply, such as India's DPDP Act and the EU's GDPR.

7. Extra checks for AI features

• Measure accuracy on a set of real, representative inputs, and keep that set for every future release.
• Test prompt injection and jailbreak attempts, especially where the AI reads emails, documents or web pages.
• Make sure the product behaves safely when the model is wrong, slow or unavailable.
• Keep a human review step wherever an AI output affects money, customers or compliance.

8. The go / no-go decision

1. 01Review the evidence. Compare results against the thresholds agreed in step 1, and list open defects by severity.
2. 02Decide and record it. Make the call in writing, with any conditions, owners and dates.
3. 03Prepare the rollback. Have a tested way to roll back or switch off features, and a support rota for launch week.

How Loopd.SI helps

Loopd.SI's launch readiness service covers product quality assessment, business assurance, performance testing, managed testing and user acceptance testing, including UAT with Indian users for products launching in India.