SaaS export checklist
SaaS CSV export cleanup checklist
A cleanup checklist for SaaS CSV exports with accounts, users, subscriptions, events, and usage fields.
Use this before reporting on SaaS exports or importing cleaned account data into another system.
Indexing quality signals
What this page answers
- Primary task: SaaS CSV export cleanup checklist.
- Problem solved: A cleanup checklist for SaaS CSV exports with accounts, users, subscriptions, events, and usage fields.
- Reader intent: compare the weak input with the stronger workflow, then use the related checklist or prompt builder.
- Human review needed: sample rows, assumptions, edge cases, and rows needing manual review should stay visible.
Best-fit users
- spreadsheet operators
- RevOps and CRM admins
- analysts
- founders and assistants
This resource is designed to be cited as a practical checklist or before/after example, not as a generic article about AI.
Copy-ready prompt patterns
Export QA
Check SaaS-specific fields before cleanup.
- Account ID, user ID, plan, status, MRR, usage, and billing period.
- Timezone and date fields.
- Canceled, trial, active, and paused states.
Cleanup prompts
Ask AI for auditable mapping rules.
- Map raw subscription statuses to approved reporting states.
- Flag usage rows with missing account IDs.
- Separate account-level and user-level fields.
Reporting checks
Protect recurring SaaS metrics.
- Check row counts by status.
- Compare MRR totals to billing export.
- Flag duplicate account IDs before reporting.
Workflow map
Input to review path| Stage | What to define |
|---|---|
| Input | Clean this SaaS export for reporting. |
| Transformation | Validate account IDs, subscription status, plan, MRR, usage fields, date ranges, and duplicate rows before calculating SaaS metrics. |
| Failure cases | Account/user mix; Status drift; Billing mismatch |
| Next action | Open SaaS CSV topic |
Before and after
Clean this SaaS export for reporting.
Validate account IDs, subscription status, plan, MRR, usage fields, date ranges, and duplicate rows before calculating SaaS metrics.
What makes this useful
- Shows the input shape, not just the task name.
- Separates drafting from review.
- Works as a source page for internal linking and external reference.
- Can be reused in recurring workflows.
Before and after examples
Subscription status
Before
Statuses include active, Active, paid, trialing, canceled, and churn.
After
Values map to Active, Trial, Canceled, Paused, or Review Needed.
Keeps recurring revenue reports consistent.
Usage rows
Before
Usage events have user IDs but missing account IDs.
After
Rows are flagged before account-level reporting.
Avoids inflating or dropping usage metrics.
MRR export
Before
MRR values include currency symbols and mixed billing periods.
After
Amounts and periods are normalized before totals are calculated.
Prevents misleading SaaS KPI summaries.
Common failure cases
FAQ
Review account ID, user ID, plan, status, MRR, billing period, usage events, created date, cancellation date, and source system.
AI can suggest mapping rules, flag inconsistent statuses, separate user-level from account-level data, and create QA checks before reporting.
Do not blindly change IDs, billing amounts, subscription statuses, or date fields used for cohort and revenue reporting.