CI regression suite for an e-commerce marketing platform

The client is a US retail technology company whose platform runs product recommendations, email automation, and campaign flows for online stores. Its merchants depend on those journeys staying reliable through frequent releases.

The product shipped fast, but every deploy carried the risk of quietly breaking a revenue-critical flow, and there was no automated safety net to catch it.

Regression was manual and slow, so a full pass took days and rarely finished before the next release was due. Testers could only spot-check the highest-risk journeys and hope the rest still worked.

Because checks ran late and by hand, defects reached production and were found by merchants rather than the team. Confidence in each deploy was low and rollbacks were common.

The platform needed fast, trustworthy regression that ran on every merge, not a manual pass bolted on before release. Speed of feedback was the whole point.

We built an end-to-end Playwright suite in TypeScript, modelling recommendations, email automation, and campaign journeys with a clean page-object design and stable selectors. Disciplined structure is what keeps the suite cheap to extend as the product grows.

Every suite was wired into GitHub Actions to run on each merge, gating the pipeline and posting results straight back to the pull request. Developers got deterministic feedback in minutes instead of days.

We hunted flakiness at the root with explicit waits and isolated test data, and ran the suite in parallel so a red build always meant a real defect. The result was regression the team could trust on every commit.