CRM migration
Field-level mapping, validation, and rollback between MaxCredible and Freshsales. We move data and schema; workflows are rebuilt natively in Freshsales.
MaxCredible
Source
Freshsales
Destination
Compatibility
4 of 8
objects map 1:1 between MaxCredible and Freshsales.
Complexity
BStandard
Timeline
1-2 weeks
Overview
Moving from MaxCredible to Freshsales is a migration from an accounts-receivable automation platform into a general-purpose sales CRM. MaxCredible's debtor-centric data model organizes records around the payment relationship, while Freshsales uses the standard Contact-Account-Deal hierarchy. We resolve the structural difference during scoping: individual debtors map to Freshsales Contacts, business debtors map to Accounts with the contact linked as a primary relationship, and invoice aging data is preserved as custom fields on the corresponding Deal. MaxCredible's XML integration format is proprietary and not publicly documented; we request sample XML files during discovery to reconstruct the schema before any data extraction runs. Tone-of-voice templates, workflow automations, and Tableau report definitions do not migrate as code. We deliver a written inventory of every automation and report definition for the customer's admin to rebuild in Freshsales.
Every standard and custom field arrives verified.
AI proposes the map; you confirm before any record moves.
Parent–child, lookups, and ownership stay linked.
Calls, emails, meetings — with original timestamps.
Documents, uploads, and inline notes move with the record.
Why teams make this switch
Leaving
What's pushing teams away
Choosing
What's pulling them in
Object mapping
Each row shows how a MaxCredible object lands in Freshsales, including any object-level transformations, lookup resolution, or schema-design dependencies.
Typical mapping — final map is confirmed during the sample migration step.
MaxCredible
Debtor
Freshsales
Contact and Account (split required)
1:manyMaxCredible debtors split into Freshsales Contact and Account based on debtor type. Individual persons map to Contact records with first name, last name, email, and phone preserved from MaxCredible fields. Business entities map to Account records with the business name as Account Name, and the primary contact within that business is created as a Contact linked via AccountId lookup. We preserve MaxCredible's debtor_id as custom field max_debtor_id__c and the credit risk score as custom field credit_risk_score__c on both Contact and Account for collections reference. The debtor status field maps to a custom picklist.
MaxCredible
Invoice
Freshsales
Deal
1:1MaxCredible invoices map to Freshsales Deal records using invoice number as an external dedupe key. The invoice amount becomes the Deal value. Due date migrates to Close Date. Invoice aging status (current, overdue, disputed) is stored as a custom field invoice_aging_status__c on the Deal. The debtor relationship resolves to the target Contact or Account, which provides the Deal's primary relation. We flag any invoice with a disputed flag for manual review before insert to prevent validation rejections.
MaxCredible
Credit Note
Freshsales
Deal (adjustment) + custom object
1:manyCredit notes require a two-part migration since Freshsales has no native credit note object. We create a Deal adjustment by reducing the original invoice Deal value by the credit note amount and link it via a custom field credit_note_reference__c pointing to the parent invoice. For audit purposes, we also populate a Credit_Note__c custom object with the credit note number, original invoice external ID, adjustment amount, issue date, and reason code. Net receivable balance is recalculated in Freshsales as the Deal value minus all linked credit note adjustments.
MaxCredible
Reminder
Freshsales
Task
1:1MaxCredible reminders migrate to Freshsales Task records. The reminder due date becomes Task Due Date. The priority and urgency from MaxCredible's aging rules map to Freshsales Task Priority (High for overdue, Normal for upcoming). The reminder body copy migrates as the Task description. The debtor and invoice references migrate as custom fields reminder_debtor_id__c and reminder_invoice_id__c so the customer's collections team can trace the origin in MaxCredible if needed during the transition period.
MaxCredible
User
Freshsales
User
1:1MaxCredible user accounts map directly to Freshsales User records by email match. Role assignments from MaxCredible (collections handler, credit manager, admin) migrate as a custom picklist field max_role__c. Active users get Active status in Freshsales; inactive users are provisioned as Inactive Users so historical assignment on migrated tasks and deals is preserved without exposing the former employee to live data.
MaxCredible
Communication Log (email, SMS, WhatsApp)
Freshsales
Task (activity)
1:1MaxCredible communication logs across email, SMS, and WhatsApp channels normalize into Freshsales Task records. Each Task stores the communication body, timestamp, and channel type in a custom field communication_channel__c. WhatsApp thread context, SMS carrier metadata, and email template references from MaxCredible are preserved as a JSON blob in a custom long-text field original_metadata__c to prevent data loss even though they do not render natively in Freshsales. This keeps the audit trail intact for compliance review.
MaxCredible
Receivables Ledger
Freshsales
Custom fields on Contact and Account
lossyThe MaxCredible receivables ledger aggregates open items per debtor and is not a single record but a financial view. We extract the per-debtor open invoice total, credit balance, and DSO snapshot and map these to Freshsales custom fields on Contact (open_receivable_total__c, credit_balance__c) and Account (open_receivable_total__c, dso_snapshot__c). Since Freshsales is not an accounting system, these fields serve as a collections reference view rather than a ledger. The customer configures list views and reports against these custom fields in Freshsales.
MaxCredible
Risk Score
Freshsales
Custom field on Contact and Account
lossyMaxCredible AI credit risk scores are snapshot values stored as a number field per debtor. We migrate the current score and the scoring date to custom fields credit_risk_score__c and credit_risk_score_date__c on both Contact and Account. The underlying behavioral data (payment timing history, dispute frequency) is not separately exposed in MaxCredible's export, so the destination cannot reproduce the identical score. We document this limitation in the migration handoff and recommend the customer's credit team recalibrate scoring rules in Freshsales using Freshsales' built-in Freddy AI lead scoring as the replacement model.
| MaxCredible | Freshsales | Compatibility | |
|---|---|---|---|
| Debtor | Contact and Account (split required)1:many | Fully supported | |
| Invoice | Deal1:1 | Fully supported | |
| Credit Note | Deal (adjustment) + custom object1:many | Fully supported | |
| Reminder | Task1:1 | Fully supported | |
| User | User1:1 | Fully supported | |
| Communication Log (email, SMS, WhatsApp) | Task (activity)1:1 | Fully supported | |
| Receivables Ledger | Custom fields on Contact and Accountlossy | Mapping required | |
| Risk Score | Custom field on Contact and Accountlossy | Fully supported |
Gotchas + challenges
Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.
MaxCredible gotchas
ERP XML integration format is proprietary to MaxCredible
Communication logs use channel-specific formatting
Tone-of-voice templates are not machine-readable for direct migration
Credit risk scores are snapshot values, not raw behavioral data
Freshsales gotchas
Freddy AI is Pro-tier only despite heavy marketing
Post-migration emails and sequences are disabled
Bot session credits are a one-time 500-session allocation
Phone credits charged per minute with no cap
File storage limits scale with plan tier
Pair-specific challenges
Migration approach
Discovery and XML schema reconstruction
We request sample XML export files from the customer's MaxCredible instance covering debtors, invoices, credit notes, reminders, and communication logs. We parse the sample to document element names, nested relationships, date formats, and encoding conventions. This reconstruction step is required before we can write a reliable extraction script. We also extract user records, role assignments, and debtor status enumerations during this phase. The discovery output is a written data dictionary and migration scope confirming which MaxCredible objects are in scope and which will be documented for rebuild.
Freshsales schema design and custom field provisioning
We design the destination Freshsales schema based on the object mapping. This includes creating all custom fields on Contact and Account (credit_risk_score__c, credit_risk_score_date__c, max_debtor_id__c, open_receivable_total__c, dso_snapshot__c), pre-creating Deal custom fields for invoice reference (invoice_number__c, invoice_due_date__c, invoice_aging_status__c, invoice_disputed__c, credit_note_reference__c), and setting up the communication channel and metadata fields. We define the debtor-to-Contact-and-Account split rule based on the debtor type enumeration observed in the XML samples. Schema is deployed to the customer's Freshsales environment for validation before any data loads.
Sandbox migration and reconciliation
We run a full migration into the customer's Freshsales sandbox using production-like data volumes. The customer's collections lead and admin reconcile record counts (debtors in, Contacts and Accounts in, Deals in, Tasks in), spot-check ten to twenty debtor records field by field against MaxCredible, and validate that invoice aging status matches the source. Any schema corrections or mapping adjustments happen in this phase. We do not proceed to production migration until the sandbox sign-off is received.
User provisioning and role reconciliation
We extract every distinct MaxCredible user and match by email against the Freshsales User table. Active collectors and credit managers get Active Freshsales user accounts provisioned by the customer's admin. Inactive or departed users are provisioned as Inactive Users in Freshsales to preserve task assignment and ownership history without giving them live access. Role mappings (collections handler, credit manager, admin) are stored in the custom max_role__c field on the User record.
Production migration in dependency order
We run production migration in record-dependency order: Account records (from business debtors), Contact records (from individual debtors linked to Account), Deal records (invoices with custom invoice fields populated), Task records (reminders and communication logs). Each phase emits a row-count reconciliation report. Communication logs are the last standard object to migrate because they depend on both Contact and Account lookups being resolved first. Credit note adjustments post-process the parent Deals to reflect net receivable amounts.
Cutover, validation, and automation handoff
We freeze MaxCredible writes during final cutover, run a delta migration for any records modified during the migration window, then enable Freshsales as the system of record. We validate total debtor count against total Contact plus Account count, total invoice count against total Deal count, and total open receivable value against the sum of Deal values in Freshsales. We deliver the automation inventory document listing every MaxCredible reminder rule and escalation condition with a recommended Freshsales workflow equivalent. We do not rebuild automations in Freshsales as part of the migration scope.
Platform deep dives
MaxCredible
Source
Strengths
Weaknesses
Freshsales
Destination
Strengths
Weaknesses
Complexity grading
Standard CRM migration. 2 of 8 objects need a mapping; the rest are 1:1.
Overall complexity
Standard migration
Derived from compatibility, mapping clarity, API constraints, and data volume across MaxCredible and Freshsales.
Object compatibility
2 of 8 objects need a mapping; the rest are 1:1.
Field mapping clarity
Field mapping is derived from defaults — final spec confirmed during the sample migration.
Timeline complexity
8-object category — typical timelines run 2–7 days end-to-end.
API constraints
MaxCredible: Not publicly documented.
Data volume sensitivity
MaxCredible doesn't expose a bulk API — REST + parallelization used for high-volume runs.
Estimator
Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.
Step 1
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FAQ
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