Context

A next-generation sales application supported Pre Journey, In Store, and Post Journey activities across dashboard, synchronization, stock, collection, ordering, rewards, printouts, and reports.

QA Role

I built journey-based coverage for multiple application variants and maintained the supporting test data and UAT scripts. Defects were investigated across connected sales, collection, stock, and reporting functions rather than treated as isolated screen issues.

Testing Scope

• Visit and synchronization flows
• Sales Order and Pre Order
• Payment collection
• Stock load, unload, and van-to-van movement
• Customer management and product returns
• Rewards, agreements, and POSM
• Document printing and reports
• Available credit-limit calculations

Test Approach

Testing followed a representative field-sales day: prepare and sync, visit an outlet, create or collect a transaction, move stock, print documents, and review the resulting reports. This exposed handoff risks that module-level checks could miss.

Tools

Postman, MySQL, Jira, Google Drive, and Visual Studio Code.

Methods & Formats

Gherkin / BDD.

Project Evidence Set

Test Case

End-to-end scenarios for pre-journey preparation, outlet visits, transactions, stock movement, printouts, and reports.

API Testing

API checks for sales, collection, synchronization, stock movement, reporting, and available-credit behavior.

SQL Validation

Database reconciliation for sales, payments, stock, reports, returns, and credit-limit values.

Gherkin / BDD

Behavior scenarios for representative field-sales journeys and cross-module handoffs.

Bug Report

Findings documented with journey stage, affected data handoff, reproduction steps, evidence, and regression scope.

Regression Checklist

Release checks grouped by journey stage to protect sales, collection, stock, return, reward, and reporting flows.

Business Impact

The journey-based coverage helped protect continuity between field activity and back-office records, reducing the risk of mismatched stock, collections, documents, and reports.

Confidentiality

This case study reflects real QA responsibilities. Product rules, identifiers, and selected details have been generalized to protect confidential information.

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