Helpdesk migration
Field-level mapping, validation, and rollback between HelpCrunch and Intercom. We move data and schema; workflows are rebuilt natively in Intercom.
HelpCrunch
Source
Intercom
Destination
Compatibility
8 of 11
objects map 1:1 between HelpCrunch and Intercom.
Complexity
BStandard
Timeline
2-4 weeks
Overview
Moving from HelpCrunch to Intercom is a schema reorganization, not a simple record copy. HelpCrunch stores customer data in a flat Customer object with custom properties, while Intercom separates Contacts from Companies and uses a conversation-first data model with separate Conversation Parts. We handle that structural split during migration by mapping HelpCrunch Customers to Intercom Contacts with their custom properties preserved, exporting chat transcripts to Intercom Conversation records with message parts intact, and transferring knowledge base articles into Intercom's Help Center with their internal links rewritten to match Intercom URLs. Chatbot flows, auto message triggers, and popup configurations do not migrate as automation code because their behavioral conditions are not portable; we deliver a written inventory of every chatbot node and auto message rule for the customer's admin to rebuild in Intercom's Builder. Intercom's API rate limit of 1,000 requests per minute is substantially higher than HelpCrunch's 120 requests per minute, which we use to accelerate bulk imports through batched sequential calls, but we monitor the X-RateLimit-Remaining header and throttle proactively to avoid HTTP 429 responses.
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 HelpCrunch object lands in Intercom, including any object-level transformations, lookup resolution, or schema-design dependencies.
Typical mapping — final map is confirmed during the sample migration step.
HelpCrunch
Customer
Intercom
Contact
1:1HelpCrunch Customer records map directly to Intercom Contact. Standard fields (name, email, userId, phone) transfer as native Intercom Contact fields. Custom properties on HelpCrunch Customers migrate to Intercom custom attributes, but Intercom requires field type matching: text properties map to text attributes, numeric to number, date to date, and checkbox to boolean. We flag any HelpCrunch custom properties that do not have a matching Intercom type and discuss the appropriate transformation during scoping. The Contact's created_at and updated_at timestamps preserve from HelpCrunch where accessible via API.
HelpCrunch
Customer (with company association)
Intercom
Contact + Company
1:manyHelpCrunch does not have a separate Company object; company data lives as a custom property or nested within Customer. We split these at migration time: if a HelpCrunch Customer record has a company name property, we create a corresponding Intercom Company first and link the Contact to it via the company_id attribute. This requires a two-phase import (Companies then Contacts) to satisfy Intercom's foreign-key resolution. We preserve any company-level custom properties as attributes on the Intercom Company.
HelpCrunch
Chat (Conversations)
Intercom
Conversation + Conversation Parts
1:1HelpCrunch Chat records map to Intercom Conversation objects, with each individual message becoming a Conversation Part. The chat metadata (timestamp, status, assignee, channel) transfers to Intercom's conversation attributes. Message content, author type (agent vs customer), and internal notes map to Conversation Part records with appropriate part_type values. Active chat widget session state does not transfer because it is runtime context. Chat attachments migrate as file URLs where the source platform's storage is accessible.
HelpCrunch
Article (Knowledge Base)
Intercom
Article (Help Center)
1:1HelpCrunch knowledge base articles migrate to Intercom Help Center articles. We export article title, body HTML, author, publication status, and SEO metadata (meta title, meta description, slug). Intercom Help Center requires articles to be organized into Collections; we create a default Collection during migration and note the customer may want to create topic-specific Collections post-migration. Internal links between HelpCrunch articles are rewritten to match the new Intercom Help Center URL structure automatically. Embedding context (standalone page vs in-widget) does not transfer and must be reconfigured in Intercom's widget settings.
HelpCrunch
Saved Reply
Intercom
Snippet
1:1HelpCrunch Saved Replies are key-value pairs scoped to the team. We export them as structured text objects with the shortcut abbreviation and the full response body. These import into Intercom as Snippets in the Outbound section, preserving the shortcut abbreviation as the Snippet key for agent efficiency. HTML formatting in saved replies maps to Intercom's Snippet content formatting.
HelpCrunch
Email Template
Intercom
Template
1:1HelpCrunch Email Templates include subject, body HTML, and variable placeholders. We extract the template content and variable names, then import into Intercom's Templates section under Outbound. Variable placeholders are preserved as liquid-style tokens and will resolve in Intercom's template rendering if the customer configures the matching attribute mappings in Outbound. Subject line and sender name transfer directly.
HelpCrunch
Auto Message
Intercom
Outbound Message (manual rebuild required)
lossyHelpCrunch Auto Messages include popup triggers, proactive chat invitations, and behavioral targeting rules. We export the message content and trigger logic (behavioral conditions, timing, page targeting) as structured data. The trigger conditions are not transferable as code because Intercom's Outbound campaign model uses different behavioral operators and event definitions. We deliver a written inventory of every Auto Message with its content, trigger conditions, targeting rules, and the recommended Intercom Outbound Campaign or Workflow equivalent for the customer's admin to rebuild.
HelpCrunch
Chatbot
Intercom
Custom Bot (manual rebuild required)
lossyHelpCrunch Chatbot flows are node-based automation trees with branching logic. We export the flow content and structure including node types, conditions, and branching paths. Node-by-node rebuilding in Intercom's Custom Bot Builder is required because HelpCrunch's rule-based flow nodes and condition syntax do not map to Intercom's Step and Condition blocks. We provide a node-by-node mapping document that lists each HelpCrunch chatbot node and its recommended Intercom Custom Bot Step equivalent so the customer's team or an Intercom partner can reconstruct the logic post-migration.
HelpCrunch
Tag
Intercom
Tag
1:1HelpCrunch Tags are flat string labels applied to Customers and Chats. We export the full tag taxonomy and reapply tag associations during import. Tags on Customers transfer to Intercom Contact tags; tags on Chats transfer to Intercom Conversation tags. The tag string values are preserved exactly as they appear in HelpCrunch.
HelpCrunch
Custom Properties (Fields)
Intercom
Custom Attributes
1:1Custom properties on HelpCrunch Customers include types (text, number, date, checkbox, dropdown). We map these to Intercom custom attributes by type: text properties become text attributes, numeric become number attributes, date properties become date attributes, and checkbox become boolean attributes. Intercom requires field types to match during import mapping; we flag any mismatched types during discovery and apply type coercion or truncation where necessary before loading.
HelpCrunch
Agent (Team Member)
Intercom
User
1:1HelpCrunch Agent records include name, email, and role. We transfer agent profiles to Intercom as Admin or Agent users based on the HelpCrunch role. The customer's admin must assign the appropriate Intercom permission set (Admin, Agent, or Viewer) at the destination because HelpCrunch role semantics do not map directly to Intercom's three-tier permission model. We include the email-to-Intercom-user mapping in the migration manifest.
| HelpCrunch | Intercom | Compatibility | |
|---|---|---|---|
| Customer | Contact1:1 | Fully supported | |
| Customer (with company association) | Contact + Company1:many | Fully supported | |
| Chat (Conversations) | Conversation + Conversation Parts1:1 | Fully supported | |
| Article (Knowledge Base) | Article (Help Center)1:1 | Fully supported | |
| Saved Reply | Snippet1:1 | Fully supported | |
| Email Template | Template1:1 | Fully supported | |
| Auto Message | Outbound Message (manual rebuild required)lossy | Fully supported | |
| Chatbot | Custom Bot (manual rebuild required)lossy | Fully supported | |
| Tag | Tag1:1 | Fully supported | |
| Custom Properties (Fields) | Custom Attributes1:1 | Mapping required | |
| Agent (Team Member) | User1:1 | 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.
HelpCrunch gotchas
API rate limit of 120 req/min blocks bulk migrations
AI conversation caps throttle history migration
Legacy API key deprecation requires key rotation
Knowledge base articles require manual re-embedding
HelpCrunch branding on chat widget in Basic plan
Intercom gotchas
S3 JSON export omits conversation transcripts
Workspace isolation prevents workflow migration
Fin AI resolution fees compound with automation success
Two-year conversation history limit on historical export
Private app rate limits share workspace quota
Pair-specific challenges
Migration approach
Discovery and data audit
We audit the HelpCrunch account across plan tier, object counts (Customers, Chats, Articles, Saved Replies, Email Templates, Tags, custom properties), and conversation volume. We extract a representative sample of custom properties to verify field types, check for missing or null values, and identify any company data encoded as custom properties versus a separate object. We document every active chatbot flow and auto message for the automation rebuild inventory. The discovery output is a written scope with record counts, a field type matrix for all custom properties, and the chatbot and auto message inventory.
Schema mapping and Intercom workspace preparation
We map HelpCrunch objects to Intercom objects and create the corresponding Intercom schema: custom attributes defined with matching types, Help Center collections created, snippet shortcuts imported, and users provisioned from the HelpCrunch agent list. We coordinate with the customer's Intercom admin to confirm attribute names, verify workspace settings (particularly phone validation and default inbox assignment), and ensure the migration user has the appropriate API access. If HelpCrunch data includes company associations as custom properties, we create Intercom Companies first so that the Contact-to-Company link can be resolved during the contact import phase.
HelpCrunch data extraction with rate-limit handling
We extract all HelpCrunch data via the REST API using the Public API key from Settings, Developers, Public API. We respect the 120 req/min rate limit with exponential backoff, chunking large record sets into sequential batches. For contacts, we paginate using the API's cursor-based pagination. For conversations, we pull transcript history including all message parts, timestamps, and assignee metadata. For knowledge base articles, we export body HTML, metadata, and SEO fields. Each extraction phase emits a row-count manifest so that the import can be verified against the source.
Transformation and data preparation
We transform extracted data to match Intercom's schema. This includes splitting HelpCrunch Customers with company custom properties into Contact and Company records, applying field type conversions for any mismatched custom properties, rewriting knowledge base internal article links to Intercom Help Center URLs, and building a tag reapplication manifest. We prepare CSV or JSON payloads per object type in the order required by Intercom's dependency rules (Companies before Contacts, Contacts before Conversations) and validate the payload structure against Intercom's API expectations before loading.
Intercom data load in dependency order
We load data into Intercom in dependency order: first Companies (if any exist in the migration scope), then Contacts with their custom attributes and company links, then Conversations with message parts, then knowledge base articles into Help Center collections. We batch requests to stay within Intercom's 1,000 req/min rate limit, monitor the X-RateLimit-Remaining header, and apply brief pauses when the remaining budget drops below 50 requests. Each phase produces a reconciliation report comparing imported row count to the extraction manifest. Tag associations are applied last to avoid breaking conversation imports.
Cutover, validation, and automation rebuild handoff
We freeze HelpCrunch writes during the final cutover window, run a delta migration of any records modified since the initial extraction, and switch the customer's system of record to Intercom. We validate by spot-checking 25-50 random contacts, conversations, and articles against the HelpCrunch source. We deliver the chatbot and auto message inventory document to the customer's admin team for rebuild in Intercom's Builder and Outbound Campaigns. We offer a one-week hypercare window to resolve reconciliation issues. We do not rebuild HelpCrunch automations as Intercom workflows inside the migration scope.
Platform deep dives
HelpCrunch
Source
Strengths
Weaknesses
Intercom
Destination
Strengths
Weaknesses
Complexity grading
Standard Helpdesk migration. 2 of 7 objects need a mapping; the rest are 1:1.
Overall complexity
Standard migration
Derived from compatibility, mapping clarity, API constraints, and data volume across HelpCrunch and Intercom.
Object compatibility
2 of 7 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
7-object category — typical timelines run 2–7 days end-to-end.
API constraints
HelpCrunch: 120 requests per minute per organization.
Data volume sensitivity
HelpCrunch 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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