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HELP DESK MIGRATION ALTERNATIVE · 2026 GUIDE

Help Desk Data Migration Checklist

86 actionable items across 7 phases. Built from 1,500+ completed migrations.

A help desk migration is one of the highest-stakes projects an IT team can run. You are moving years of customer history, support tickets, knowledge base articles, and operational data from one system to another. If something goes wrong, you lose customer context, break agent workflows, and damage trust.

This checklist covers every phase in 86 actionable items across 7 phases. Built from 1,500+ completed migrations. No theory, no filler — just the tasks you need to track from first data audit to final system decommission.

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86 items · 7 phases · Free

86 items across 7 phases

Every task from first data audit to final system decommission. Work through it here, or use the downloads above to track progress with your team.

Phase 1 · 11 items

Discovery and Data Audit

Before you touch any migration tooling, you need to understand exactly what you have, what shape it is in, and what needs to come with you to the new system.

01

Evaluate your current help desk and document pain points

Write down what is broken, what is slow, and what your agents complain about most. These pain points become the success criteria for your migration. If the new system does not solve them, the project has failed regardless of data integrity.

02

Define migration goals and measurable success criteria

Set specific targets: "reduce average ticket resolution time by 20%," "support 3x current ticket volume," "enable multi-channel routing." Vague goals like "improve support" give you no way to measure whether the migration was worth it.

03

Identify all stakeholders and assign a single project owner

Someone must own the migration end-to-end. This person is accountable for timeline, communication, and decisions. Without a single owner, decisions stall and accountability diffuses across teams.

04

Complete a full data inventory across all object types

Catalog every data object in your current help desk: tickets, contacts, organizations, knowledge base articles, custom fields, tags, attachments, agent accounts. For each object, record the type, record count, approximate size, and data sensitivity level.

05

Capture exact record counts for every data object

Run exports or API queries to get precise numbers. You need these counts to validate after migration. If you started with 127,403 tickets and end with 127,398, those 5 missing tickets need to be found and accounted for.

06

Map dependencies between data objects

Tickets depend on contacts. Contacts link to organizations. KB articles live inside categories. Automations reference custom fields. Map these dependency chains so you know the order things must be migrated in. Importing tickets before their associated contacts will create orphan records.

07

Run data profiling on your source data

For every critical field, measure: percentage of null values, duplicate key rate, orphan record rate, and encoding anomalies. This tells you how clean your data actually is. If 15% of your contact records have no email address, you need to decide how to handle that before migration, not during.

08

Decide what to migrate, what to archive, and what to discard

Not everything deserves to move. Spam tickets, test data, duplicate contacts, deprecated custom fields, and outdated KB articles marked for deletion should be archived or discarded. Migrating junk data into a clean new system defeats the purpose of the switch.

09

Identify all custom fields, tags, and picklist values that need mapping

Export a complete list of every custom field, dropdown option, tag, and label in your source system. Each one needs a mapping rule: does it map 1-to-1 to the target, does it need a transformation, or is it being retired?

10

Document all active automations, triggers, macros, SLA policies, and routing rules

Automations cannot be migrated as data. They must be manually rebuilt in the new system. Document every active automation with its trigger condition, action, and any dependencies on custom fields or tags. Missing even one critical routing rule can send tickets to the wrong team on day one.

11

List every third-party integration connected to your current help desk

CRM sync, billing system, Slack notifications, analytics dashboards, phone system, chatbot. List every integration. Each one needs to be reconnected and tested in the new system. This is one of the most commonly forgotten tasks in a migration project.

Phase 2 · 9 items

Strategy and Planning

Turn your audit into an actionable plan. Choose how to migrate, set risk thresholds, build a timeline, and get stakeholder buy-in before any work begins.

12

Select your migration strategy: Big Bang, Phased, or Trickle

Big Bang moves everything at once during a maintenance window — simple but requires downtime tolerance. Phased migrates data in batches (by department, date range, or data type) — medium complexity, medium risk. Trickle uses continuous sync with a delta cutover — zero downtime but highest technical complexity. Your choice depends on downtime tolerance, data volume, and dependency complexity.

13

Create a RACI matrix for the migration project

Define who is Responsible, Accountable, Consulted, and Informed for each phase of the project. This prevents the "I thought you were handling that" conversations that derail migration projects during cutover week.

14

Define your rollback criteria and rollback procedure

Before you start, decide what failure looks like and how you will reverse it. Example: "If more than 0.5% of records fail validation after cutover, we roll back to the source system within 4 hours." Without pre-defined criteria, teams waste critical hours debating whether to continue or abort during a crisis.

15

Set acceptable data variance and error rate thresholds

Define pass/fail numbers before migration, not after. Industry standard targets: row parity >= 99.9%, transformation error rate <= 0.5%, zero orphan records. If you set these after seeing results, you will rationalize problems instead of fixing them.

16

Build a detailed project timeline with milestones for each phase

Assign specific calendar dates to each phase. Include buffer time between phases for issue remediation. A typical mid-market help desk migration takes 4-8 weeks end-to-end. Complex enterprise migrations may take 8-12 weeks.

17

Add a 15-20% contingency buffer to the timeline

Every migration surfaces surprises. Rate limits you did not expect, custom fields that do not map cleanly, an API that behaves differently in production than in sandbox. The contingency buffer is not pessimism — it is standard project management best practice.

18

Create a migration budget covering all cost categories

Account for: new platform subscription fees, migration service or internal engineering labor, agent training time, potential productivity dip during the transition period, and a contingency fund (15-20% of total). The most commonly underestimated line item is internal engineering labor.

19

Build a communication plan for every stage of the project

Who gets notified when planning starts? When cutover is scheduled? When go-live happens? When hypercare ends? Include escalation paths for issues discovered during migration. Surprises during cutover are inevitable. Surprise communication failures are not.

20

Get formal stakeholder sign-off on strategy, timeline, and budget

Do not proceed without written approval from project sponsors, IT leadership, and support management. This protects you when scope changes arise later and creates shared accountability for the plan.

Phase 3 · 11 items

Data Preparation and Mapping

This is where migrations quietly succeed or fail. The quality of your data preparation directly determines the quality of your results.

21

Clean your source data: remove spam, test records, duplicates, and deprecated entries

Run deduplication on contacts and organizations. Delete or archive spam tickets, test tickets created during sandbox experiments, and any records that exist only because of a past import error. Migrating dirty data into a clean system is a waste of effort.

22

Merge duplicate contacts and organizations

Identify contacts with multiple records (same email, different names) and merge them before migration. If you migrate duplicates, you will have duplicate records in the new system with split ticket histories. That is a nightmare for agents trying to see a customer's full context.

23

Archive tickets older than your retention policy

If your company only needs active access to the last 2 years of tickets, archive older records rather than migrating them. This reduces migration volume, speeds up the process, and keeps the new system clean. Archived data can be stored separately for compliance.

24

Perform a full backup of your source system

Export everything: database, file attachments, knowledge base content, configuration. This is your safety net. If anything goes catastrophically wrong during migration, this backup is how you restore operations.

25

Verify your backup by restoring it to an isolated test environment

A backup you have not tested is not a backup. It is a hope. Attempt a partial restore to confirm the export is complete, not corrupted, and actually usable. This step catches problems that would otherwise surface during a crisis.

26

Store the backup in a secure, separate location

Do not store the backup inside either the source or target platform. Use S3, Google Cloud Storage, Azure Blob, or an encrypted local drive. The backup must survive even if both platforms have issues simultaneously.

27

Create a versioned field mapping document

For every field in the source system, define: the target field it maps to, the transformation rule (if any), and any default values for fields that do not exist in the target. Format: source_field -> target_field -> transform_rule.

28

Document all data transformation logic in detail

Field concatenation, picklist value conversion, date format changes, timezone normalization, nested JSON flattening — document every transformation rule. Undocumented transformations become mystery bugs post-migration.

29

Get the field mapping reviewed and approved by a business owner

Engineers understand the technical mapping. Business owners understand whether the mapped result makes sense for daily operations. A field that is technically correct but operationally confusing will frustrate agents and erode trust in the new system.

30

Create a test dataset for pilot migration runs

Pull a representative sample that includes your most complex records: tickets with the longest threads, contacts with the most custom fields, organizations with nested relationships, KB articles with embedded images. Test on hard data first, not easy data.

31

Commit the mapping specification to version control

Every change to field mappings must be tracked. If a mapping is changed between pilot run 2 and pilot run 3, you need to know exactly what changed, who approved it, and why. Use Git or equivalent.

Phase 4 · 11 items

Platform Setup and Configuration

Set up the target system so it is ready to receive data. This phase typically runs in parallel with data preparation.

32

Set up the new help desk platform instance

Create the account, configure the subdomain, and apply branding (logo, colors, email templates). The platform should be fully set up before any data migration begins.

33

Configure user roles and permissions in the new system

Recreate your permission structure: admin roles, agent roles, supervisor roles, read-only roles. Map every user from the source system to the correct role in the target. Permission mismatches are a common post-migration security issue.

34

Recreate all custom fields, tags, ticket statuses, and picklist values

These must exist in the target system before data is imported. If a ticket references a custom field that does not exist in the target, the import will either fail or silently drop that data. Build the container before you pour data into it.

35

Rebuild automation rules, triggers, workflows, and macros

Automations cannot be migrated as data. They must be manually rebuilt using your documentation from Phase 1 as the blueprint. Test each automation individually before go-live.

36

Rebuild SLA policies and escalation rules

SLA timers, response time targets, escalation paths, and business hours must be configured in the new system before go-live. If these are not set, your first day on the new platform will have zero SLA enforcement.

37

Configure email channels with proper DNS records

Set up email forwarding rules, and verify SPF, DKIM, and DMARC records for your support email addresses. Incorrect email configuration is one of the top causes of tickets not being created in the new system on day one.

38

Configure chat, messaging, and social media channels

If you use live chat, Facebook Messenger, WhatsApp, Twitter DMs, or other messaging channels, configure and test each one in the new system. Channel-specific routing rules may need separate configuration.

39

Set up all third-party integrations

Reconnect your CRM, billing system, analytics tools, Slack workspace, phone system, and any other connected services. Each integration needs API keys or OAuth tokens regenerated for the new platform.

40

Create all agent accounts and verify login access

Every agent should be able to log into the new system before go-live. Do not discover login issues on cutover day. Have each agent confirm access at least 48 hours in advance.

41

Distribute training materials and quick-reference guides

Create one-page cheat sheets covering the most common agent tasks in the new system: how to reply to a ticket, how to assign, how to escalate, how to use macros. Agents should not need to figure out the new UI under pressure on day one.

42

Hold training sessions or office hours for agents

Run at least one hands-on training session where agents practice common workflows in the new system. Follow up with an open office hours session for remaining questions. Untrained agents on a new system will slow down your entire support operation.

Phase 5 · 11 items

Sample Migration and Pilot Testing

Run the migration on test data before you run it on production. Start with your most complex records, not the easiest ones.

43

Run a sample migration on your test dataset

Execute the migration pipeline against your test dataset. Start with the most complex records: longest ticket threads, contacts with the most custom fields, orgs with the deepest nesting. If the hard data works, the easy data will too.

44

Validate ticket threading and conversation integrity

Open migrated tickets in the target system and verify that conversation threads display in the correct order. Customer messages, agent replies, and internal notes should appear exactly as they did in the source.

45

Validate custom field values and tag mappings

Spot-check that custom fields contain the correct transformed values. A picklist value of "Enterprise" in the source should map to the target equivalent — not show up blank or as "Unknown."

46

Verify all attachments transferred and are openable

Check that file attachments (screenshots, PDFs, documents) are present on migrated tickets AND can be opened. Silent attachment failures are common: the attachment link exists but the file is missing or corrupted.

47

Verify historical timestamps are preserved

Check that Created On and Modified By dates on migrated records show the original historical dates, not the migration date. If every ticket shows today's date as Created On, your reporting and SLA history is destroyed.

48

Verify relational integrity between objects

Tickets should be linked to the correct contacts. Contacts should be linked to the correct organizations. No orphan records: no tickets without a contact, no contacts without an org where one should exist.

49

Check encoding for special characters, emoji, and multi-byte strings

Search for tickets containing emoji, accented characters, or non-Latin scripts. Verify they display correctly in the target system. Encoding mismatches between platforms can silently corrupt customer communications.

50

Measure row parity: source count vs target count for every object type

Compare exact record counts between source and target for tickets, contacts, organizations, KB articles, and attachments. Any discrepancy must be investigated and explained before proceeding to production.

51

Test the rollback procedure on sample data

Practice your rollback: purge the test data from the target system and verify the source is completely unaffected. If you cannot cleanly roll back a sample migration, you cannot safely roll back a production migration.

52

Run additional sample migrations until all issues are resolved

Do not proceed to production until every known issue from pilot testing has been fixed and re-validated. Each iteration should produce fewer issues. If new issues keep appearing, your mapping or transformation logic needs more work.

53

Document all issues found and fixes applied during pilot testing

Maintain a log of every issue discovered during sample runs: what went wrong, what the root cause was, and how it was fixed. This document becomes critical if similar issues appear during production migration.

Phase 6 · 15 items

Go-Live Cutover Execution

This is cutover day. Follow the plan. Communicate constantly. Do not improvise.

54

Announce a system-wide code and configuration freeze

At least 48 hours before cutover, freeze all changes to both the source and target systems. No code deployments, no workflow changes, no permission edits, no app installations. A last-minute change can break migration logic that was tested against a specific configuration.

55

Temporarily revoke write access on both systems

If possible, restrict admin and developer roles to read-only during the freeze window. This prevents well-meaning but migration-breaking changes from someone who forgot about the freeze.

56

Hold the final Go/No-Go meeting and get unanimous stakeholder approval

Gather project sponsors, IT leads, support managers, and the migration team. Review the readiness checklist item by item. Any unresolved concern is a "No-Go." Do not proceed with lingering doubts. It is always cheaper to delay a cutover than to recover from a failed one.

57

Perform a final full backup of the source system

This is your last safety net before cutover. Back up the complete source database and all file attachments. This backup represents your last known-good state and is the foundation of any rollback.

58

Verify the final backup with a partial restore test

Confirm the backup is not corrupted and can be restored. Run this in an isolated environment, never in production.

59

Execute the bulk data migration

Run the production migration pipeline. Monitor progress in real time: rows processed, rows failed, error logs, and throughput rate. If error rates exceed your pre-defined thresholds, pause and assess before continuing.

60

Monitor migration progress and error logs in real time

Watch for HTTP 429 (rate limit exceeded) errors, 413 (payload too large) errors, and 422 (validation failure) errors. Track rows processed versus rows expected. Any anomaly should be flagged immediately, not investigated after the run completes.

61

Place the old help desk in read-only mode

Disable all incoming email forwarding, API endpoints, chat widgets, and customer portal access on the source system. Change all user roles to read-only. Any new data entering the source system after this point will not be captured.

62

Post a read-only banner in the old system UI

Inform any agent who opens the old system that it is now read-only and the new system is live. Include a direct link to the new system.

63

Execute the final delta migration

Run the delta catch-up script to capture all data created or modified since the bulk migration started. This is what prevents data loss during the transition window and enables zero-downtime cutover. Without delta migration, you lose every ticket created during the migration window.

64

Run post-delta validation checks

Verify row parity, aggregate totals, checksum matches, and referential integrity between source and target. This is the final proof that all data made it across. Do not proceed to DNS switch until validation passes.

65

Re-point DNS and all incoming support channels to the new system

Update email forwarding, MX records, chat widget scripts, API webhook URLs, and customer portal DNS to point to the new platform. Double-check every channel. A single missed channel means tickets disappearing into the old system.

66

Enable notifications and automations in the new system

Only turn on automations, triggers, SLA timers, and email notifications AFTER data validation is complete. Enabling them before validation can fire automated responses on partially migrated or incorrect data.

67

Re-establish and test all third-party integrations

Reconnect every integration and send test data through each one. Verify CRM sync, Slack notifications, billing webhooks, and analytics pipelines are all functioning correctly.

68

Send test messages through every support channel

Send a test email to your support address. Initiate a test chat session. Submit a test portal ticket. Confirm each one creates a ticket in the new system, routes to the correct team, and triggers the expected automation.

Phase 7 · 18 items

Post-Migration QA and Hypercare

The migration is not done at cutover. It is done after stability is confirmed and the team is operating normally on the new system.

69

Spot-check ticket data from different time periods

Randomly select tickets from last week, last month, last year, and 2+ years ago. Verify ticket IDs, subjects, conversation threads, custom fields, and timestamps match the source system.

70

Verify contact and organization records

Check names, email addresses, phone numbers, organization links, and custom fields on a sample of contact and organization records.

71

Verify knowledge base articles

Check content accuracy, formatting, embedded images, category assignments, and URL slugs. Broken images or missing formatting in customer-facing KB articles damage credibility immediately.

72

Verify attachment and file integrity

Open a sample of attachments from migrated tickets. Confirm they are the correct files, not corrupted, and display properly in the target system.

73

Test automation and trigger execution end-to-end

Create a real test ticket and verify that assignment rules, auto-responses, SLA timers, and escalation triggers all fire as expected in the new system.

74

Test SLA policies and escalation rules

Verify that SLA countdown timers start correctly, business hours are applied properly, and escalation rules trigger at the right thresholds.

75

Test all support channels end-to-end

Send a real email to your support address. Start a real chat session. Submit a real portal ticket. Follow each one through the full lifecycle: creation, assignment, agent response, and resolution.

76

Have 2-3 agents complete a full workflow walkthrough

Ask agents to perform their most common daily tasks in the new system: pick up a ticket, read the customer history, write a reply, add an internal note, assign to a teammate, resolve, and close. Note any friction points.

77

Test the customer portal

Log in as a customer. Submit a new ticket, view existing ticket history, and search the knowledge base. Confirm everything works from the customer's perspective.

78

Validate reporting dashboards and historical analytics

Check that dashboards display data correctly and that historical reports (response time trends, CSAT scores, ticket volume by month) show accurate numbers. If your historical reporting is broken, leadership loses trust in the new system on day one.

79

Benchmark performance against pre-migration baseline

Compare page load times, API response times, and search speed to your pre-migration measurements. Performance within +/-20% of baseline is the standard acceptance threshold.

80

Audit user roles, permissions, and security settings

Verify that every agent has the correct role, every admin has the correct access level, and no user has more permissions than intended. Security misconfigurations after migration are a common and serious oversight.

81

Set up a dedicated war room or Slack channel for hypercare issues

Create a single place where agents can report issues in real time during the first 48-168 hours after go-live. Staff it with someone who can triage and escalate quickly.

82

Send a company-wide go-live communication

Notify the entire company that the help desk migration is complete, the new system is live, and how to report any issues. Include links to the new system and any relevant quick-reference guides.

83

Monitor error rates, latency, and missing-record alerts for the full hypercare window

Minimum hypercare window is 48 hours. For complex migrations, 7 days (168 hours) is recommended. Track: error rate (target <0.5%), query latency (target +/-20% baseline), missing record alerts (target: zero), job retry rate (target <2%).

84

Gather real-time feedback from agents daily

Run a quick pulse survey or daily standup with agents during hypercare. Ask: "What is not working? What is confusing? What is slower than the old system?" Fix high-impact issues immediately.

85

Hold a post-mortem review meeting and document lessons learned

After hypercare ends, gather the full project team. Review what went well, what went wrong, and what you would do differently. Document everything for the next time your organization runs a migration.

86

Begin decommissioning the old system

Archive all remaining data from the source platform. Perform a secure wipe if required by your data retention policies. Terminate the old platform's subscription. Update your CMDB and internal documentation to reflect the new system as the system of record.

COMMON QUESTIONS

Help desk data migration checklist FAQ

How long does a help desk migration take?

The timeline depends on data volume, complexity of custom fields, number of integrations, and whether you need zero-downtime cutover. A small migration under 50,000 records with standard fields can finish in a day or two. Mid-market migrations with custom fields and moderate volume typically take 1-2 weeks of active migration work. Large enterprise migrations with hundreds of thousands of records, multi-brand setups, and complex relational data can take 2-4 weeks. The most common reason migrations take longer than expected is underestimating the time needed for data preparation, field mapping, and post-migration validation.

ClonePartner completes most migrations within a week. Small standard migrations often finish in under 1-5 days, and even the largest enterprise projects take a maximum of about one month. You receive a detailed timeline with specific milestones after the initial assessment call.

How much does a help desk migration cost?

Migration costs vary widely depending on the method you choose. Self-service automated tools charge per-record fees that range from a few hundred dollars for small datasets to $10,000+ for large ones, but that sticker price does not include internal engineering labor for mapping, testing, and validation, which can add $2,000-$47,000 in hidden costs. Managed migration services charge fixed project fees that typically start around $5,000 and scale with complexity. The total cost of a migration should include the tool or service fee, internal labor, potential downtime cost, and a contingency buffer.

ClonePartner migrations start as low as $500. Every quote is all-inclusive and fixed-price — no add-ons, no per-feature tier upgrades, no hidden fees. The price covers discovery, custom scripting, unlimited sample migrations, validation, delta cutover, and post-migration support. One number after your scoping call, and it does not change.

What data should I migrate to my new help desk?

At minimum, migrate all tickets with full conversation threads (public replies and internal notes), attachments, custom fields, and tags. Also migrate knowledge base articles with their formatting, images, and category structure, plus all agent and customer user profiles. For a fully operational system, bring contacts, organizations, and their relational links to tickets. Automations, macros, SLA rules, and routing logic cannot be migrated as data and must be manually rebuilt in the new platform. Leave behind spam tickets, test records, duplicate contacts, deprecated custom fields, and outdated KB articles. A good rule: if nobody has touched it in 2 years and compliance does not require it, archive it instead of migrating it.

ClonePartner's engineers help you make these decisions during the discovery call. They walk through your data objects, flag what is critical, recommend what to archive, and ensure nothing important gets left behind while no junk comes along.

What is a delta migration and why does it matter for zero downtime?

A delta migration is a final catch-up migration run just before go-live that captures all data created or modified since the bulk migration started. During any migration, your team continues working — new tickets come in, agents reply, contacts get updated. Without a delta migration, all of that data is permanently lost when you switch systems. Delta migration is the single feature that enables zero-downtime cutover. Without it, you must either freeze your entire support operation during the transition or accept data loss. It is non-negotiable for any business that cannot afford hours of downtime or missing customer interactions.

ClonePartner includes delta migration as standard in every project at every price point. It is not an add-on or a premium feature. The catch-up script runs right before go-live, captures every ticket, reply, and contact update created during the bulk migration window, and ensures zero data loss.

Can I preview how my data will look before committing to a full migration?

The industry standard for pre-migration testing varies. Some automated tools offer a free demo that moves a small random batch of roughly 20 records so you can check basic field mapping. Managed services typically run a larger-scale test migration in a sandbox environment. The purpose of a preview is to catch mapping errors, custom field issues, timestamp overwrites, and relational integrity problems before they affect your production data. A 20-record sample is useful for checking basic connectivity but too small to surface complex data issues. The more records you test, the more confident you can be.

ClonePartner offers unlimited sample migrations. You can see exactly how your tickets, contacts, custom fields, and attachments look in the new system — not 20 random records but a substantial portion of your real data in a sandbox. Run as many samples as you need, request mapping adjustments between runs, and only give the green light when you are fully satisfied.

What happens if something goes wrong during a help desk migration?

If a migration fails mid-run, the correct response is: stop immediately, do not re-run the failed job, disable incoming channels on the target system, re-route traffic back to the source, export backups from both systems, preserve all migration logs and error details, and diagnose the root cause before attempting anything else. Common failure causes include API rate limits (HTTP 429 errors), structural mismatches between platforms, missing contact dependencies that create orphan records, and payload size limits. The biggest mistake teams make is re-running a failed migration without understanding why it failed, which compounds the problem.

With ClonePartner, failures are caught during internal sample migrations and fixed by engineers before you see them. If an issue surfaces during production, engineers diagnose and resolve it in real time. You do not troubleshoot anything yourself. Re-migration is included at no additional cost, and ClonePartner absorbs the project risk through a formal SLA and Statement of Work.

Do I need a technical team to manage a help desk migration?

It depends on your migration method. If you use a self-service tool, you need at least one technical person who can dedicate significant time to managing the project: connecting APIs, mapping fields, running tests, validating results, troubleshooting errors, and coordinating the cutover. Industry experience shows this typically requires 40-200+ hours of engineering time depending on complexity. If you use a managed migration service, your team's involvement is minimal since the service handles the technical work. The question is whether diverting your engineering team from product work for weeks is worth the savings on a migration service fee.

ClonePartner is a fully managed service. A dedicated migration engineer handles every phase: data audit, custom scripting, field mapping, sample migrations, validation, delta cutover, and post-migration QA. Your involvement is a 30-minute discovery call and a final sign-off on the validation report. Your engineering team stays on product work throughout.

How do I know if my help desk migration was successful?

A successful migration passes five validation checks. Row parity: exact record counts between source and target match for every object type (tickets, contacts, organizations, KB articles, attachments) with at least 99.9% match rate. Relational integrity: tickets are linked to the correct contacts and contacts to the correct organizations, with zero orphan records. Timestamp preservation: Created On and Modified By dates show original historical values, not the migration date. Attachment integrity: a sample of file attachments can be opened and are not corrupted. Functional testing: automations fire correctly, SLA timers count down, integrations sync, and agents can complete daily workflows without friction.

ClonePartner provides a detailed validation report after every migration covering all five checks. This includes exact record counts, relational integrity verification, timestamp audits, attachment spot-checks, and hand-reviewed examples of the most complex records with direct links in the new system for your own review.

Will my historical ticket dates be preserved or overwritten during migration?

By default, most help desk platforms overwrite the Created On and Modified By fields with the migration date and the API user account when records are imported. This means five years of ticket history can appear as if it was all created on a single day. The impact is severe: historical reporting breaks, SLA compliance records become meaningless, and audit trails are destroyed. Preserving historical timestamps requires platform-specific workarounds. Salesforce requires enabling the "Set Audit Fields Upon Record Creation" permission. Dynamics 365 uses the overriddencreatedon field. HubSpot needs specific property override settings. Zendesk has its own timestamp rules for ticket imports. If your migration method does not explicitly address this, assume all dates will be lost.

ClonePartner's engineers handle platform-specific timestamp preservation as a standard part of every project. Whether it is Salesforce audit field permissions, Dynamics 365 workarounds, HubSpot overrides, or Zendesk rules, your historical data stays historical. No extra charge, no add-on required.

What platforms are supported for help desk migration?

The major help desk platforms that support data migration via API include Zendesk, Freshdesk, Intercom, Front, Help Scout, HappyFox, Gorgias, Gladly, Dixa, Kayako, LiveAgent, Jira Service Management, ServiceNow, and Freshservice. Most platforms provide REST APIs that allow extraction and import of tickets, contacts, organizations, and knowledge base articles. The key technical challenges in cross-platform migration are structural differences in how each platform handles ticket threading, custom fields, attachment storage, user identity, and API rate limits. Each platform pair has its own set of edge cases and constraints.

ClonePartner supports migrations across 500+ platforms, covering not just help desk but also CRM (Salesforce, HubSpot, Pipedrive, Close), HRIS (BambooHR, Rippling), ATS (Greenhouse, Lever, Teamtailor), ERP (Dynamics GP, NetSuite, QuickBooks), and knowledge base (Confluence, Notion, SharePoint). If you are migrating across categories simultaneously, ClonePartner coordinates it as a single project with one fixed price.

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