Migration guide
Move from FreshBooks to Invoice Crowd with preserved exports, deliberate customer and invoice mapping, a test import, and reconciled totals.
Safe cutover
Invoice Crowd may fit teams that want purchases, vendors, accounting reports and multi-business context beside client billing. FreshBooks can remain the better fit where its polished client-service workflow, support or established integrations are central.
The source remains the evidence for history the target does not recreate.
Export clients, items or services, invoices and estimates plus any available expense, payment, time and report archives. Preserve PDFs and the original account for material history that is not represented by the target import types.
Decide which records must operate in Invoice Crowd and which remain in the source archive. Record the cutover date, owners and retention requirements.
Invoice Crowd analyzes CSV, TXT, XLS and XLSX files before supported imports.
Current analyzers cover items, customers, vendors, invoices and estimates. Auto-detection suggests columns, but required fields and warnings must be reviewed before import.
Test duplicate names, foreign currencies, taxes, discounts, long descriptions and open documents. Review the preview and skipped-row output instead of assuming a successful request means every row was accepted.
Activation follows totals, document meaning and ownership, not a raw row count.
FreshBooks projects, time, expenses, retainers, payments, credits, late fees, recurring profiles, attachments and custom fields need an explicit keep, rebuild or archive decision. Do not treat a row count as proof that balances or document meaning survived. Invoice Crowd has its own recurring invoices, retainers and late fees, so set up the ones you still need instead of importing them; recurring invoices and retainers need a paid plan.
Pause or sequence writes, take final exports, import approved deltas, reconcile opening and open-document totals, and keep a documented fallback path before inviting the wider team.
Migration checklist
Use this checklist with the people responsible for bookkeeping, operations, retention and customer communication.
Keep dated, immutable source exports and access.
Use CSV, TXT, XLS or XLSX within the configured upload limit.
Map required identity and contact fields.
Map supplier identity and contact fields.
Map product and service fields deliberately.
Preserve document number, dates, customer, currency, lines, tax, discounts and totals.
Preserve quote identity, dates, customer and line details.
Review detected headers, suggested mapping, required fields and sample rows.
Resolve missing required fields before committing the job.
Download and review rejected records instead of hiding them.
Match open documents, customer balances and approved opening totals.
Record what remains in FreshBooks and why.
Questions
No. Invoice Crowd currently analyzes and imports supported CSV or Excel data for items, customers, vendors, invoices and estimates. Historical records and provider-specific structures need an explicit archive, rebuild or reconciliation decision.
Invoice Crowd imports CSV, TXT, XLS and XLSX files within the upload size limit. Item imports are checked in batches of up to 1,000 rows or 2 MiB.
Items, customers, vendors, invoices and estimates. Item imports show a full preview first, and one invalid row stops the whole batch until you fix it. Bank reconciliation has a separate import workflow and is not a substitute for migrating a complete accounting ledger.
Not immediately. Keep source access and immutable exports until financial, tax, contractual and audit retention needs are covered and every material balance has been reconciled.
Check field mapping, warnings, row outcomes, representative document rendering, open balances, currencies, taxes and approved opening totals. A successful upload or matching row count is not enough.
Document it in the migration register and either preserve it in the source archive, attach it through a supported operational process, or rebuild it deliberately. Never silently discard it.
Create the archive, normalize a representative set, inspect warnings and skipped rows, and reconcile the result before the production cutover.
