Reading a Feature Request Ticket

The User Story clearly identifies the persona and the "so that" — the real business motivation:

The User Story format: "As a [persona], I want to [action], so that [business value]."

Breaking it down:

• "As a merchant managing my ShopStream store" → persona: merchant (not customer, not admin, not developer)
• "I want to export my order history to a CSV file" → the feature requested
• "so that I can import the data into my accounting software (QuickBooks, Xero, or Excel) without manual data entry" → the business problem: without this feature, merchants must manually type their orders into accounting software — tedious, error-prone, and time-consuming

Why the "so that" clause matters:
It prevents solutions that satisfy the literal request but miss the real need. If a developer only read "I want a CSV export," they might build an export that downloads in a format accounting software cannot import. The "so that" clarifies the actual requirement: the CSV must be importable by QuickBooks, Xero, or Excel.

User story vocabulary:

• persona → the type of user the story is written for
• user story → a feature description from the user's perspective, not a technical specification
• merchant → a business customer who sells products via the platform (distinct from end-consumer "customers")

Large exports trigger an async job — user gets an email with a link rather than waiting:

AC4 states: "For large exports (>1,000 orders), the file is generated asynchronously. The user receives an email with a download link within 5 minutes."

Why the two different behaviours?

• Small export (<1,000 rows): Can be generated in milliseconds. The browser can wait for the response and immediately start downloading. Synchronous works fine.
• Large export (>1,000 rows): Generating a 50,000-row CSV might take 10–30 seconds. If the HTTP request waits that long, the browser may time out, the connection may drop, and the user doesn't know if their export is coming or not.

The async pattern solves this:

1. User clicks "Export" → system queues a background job → immediately responds to the user: "Your export is being prepared, you'll get an email soon."
2. Background job generates the CSV (takes as long as it needs)
3. System emails the download link when ready

This is why the ticket lists FEAT-1101 (async job queue infrastructure) as a dependency — the async path requires background job infrastructure to already exist.

AC5 adds security: The download link expires after 24 hours, so a leaked email cannot give permanent access to order data.

The Priority Rationale translates user demand into business language — evidence + cost of inaction:

Three distinct types of evidence in this section:

• Quantified demand: "Requested by 34% of merchant accounts in the Q1 survey" — not "many merchants asked for this," but a concrete percentage from a formal survey
• Trend data: "Top-requested feature for 3 consecutive quarters" — this isn't a new request; it's persistent and growing
• Cost of inaction: "6 merchants churned in Q1 citing lack of export functionality" — churned means they cancelled their subscription. This is lost recurring revenue, quantifiable and real.

Why this kind of rationale matters:
A product backlog contains hundreds of feature requests. Without rationale, prioritisation is subjective: "I think this is important." With rationale, it's objective: "This costs us 6 merchants per quarter in churn and is requested by a third of our user base."

A P2 priority is justified here. If the churn number were 60 merchants, it might be P1. If only 3% requested it and no churn was linked to it, it might be P3.

Ticket vocabulary:

• churn → customers who cancel their subscription or stop using the service
• retention → keeping existing customers subscribed
• priority rationale → the justification for the priority level, using data

Dependencies define what must exist before this feature can work — and which parts are already unblocked:

Reading the three dependencies carefully:

• FEAT-1101: Async job queue infrastructure (must be completed first) — this is a hard blocker for AC4 (large export async path). Without the async job infrastructure, the feature cannot be fully built. A developer would need to check FEAT-1101's status before starting.
• FEAT-1155: Role-based UI visibility component (completed ✓) — AC1 requires showing the button only to "merchant" role users. The component for this already exists. No blocker here.
• No database schema changes required — the export reads existing data. No migrations needed. This reduces delivery risk and coordination with DBAs.

What a developer does with this information:

• If FEAT-1101 is done → full implementation possible
• If FEAT-1101 is still in progress → developer can build everything except the async path (AC4/AC5), and add the async path when FEAT-1101 ships
• The "no DB schema changes" note means: no risk of migration failures, no need to coordinate database downtime windows

Ticket vocabulary:

• dependency → work that must exist before this ticket can be completed
• blocker → a dependency whose absence prevents progress entirely
• schema change → a modification to the database structure (add column, create table, etc.)

AC = what the feature must do (user-visible); DoD = how the delivery must be done (quality gates):

Acceptance Criteria (AC1–AC5):
These are testable statements describing user-facing behaviour:

• "An Export to CSV button appears for merchant role" → UI test
• "CSV contains these specific columns" → data test
• "Large exports trigger async + email" → integration test
• "Download link expires after 24h" → security test

If all 5 ACs pass, the feature does what users need.

Definition of Done (DoD):
These are engineering quality standards that must also be met:

• Unit tests written for CSV mapping
• E2E test covering the full flow
• Manual test with 5,000 rows (stress test)
• Security review confirming link expiry and role visibility
• Documentation updated for merchants

A feature can pass all ACs (correct behaviour) but fail DoD (no tests, no documentation). Both must be complete before the ticket is closed.

Why the distinction matters:
Without a DoD, teams might ship features that "work today" but break later because there are no regression tests. The DoD enforces engineering discipline alongside functional completeness.

Ticket vocabulary:

• Definition of Done (DoD) → the team's agreed-upon quality checklist; a ticket isn't "done" until every DoD item is checked
• E2E test → end-to-end test: simulates a real user action from browser to database
• regression test → a test that ensures previously working behaviour stays working