CRM Integration
CRM integration patterns for DMTR.
Overview
CRM integrations connect DMTR position and participant data with customer relationship management systems for deal tracking, investor relations, and compliance workflows. Supported patterns include Salesforce, HubSpot, and custom CRM integrations. Use CRM integrations to surface DMTR data in sales and IR workflows and to sync participant information bidirectionally.
Salesforce
Salesforce integration supports custom objects for positions, participants, and transfer intents. Use the Salesforce Connector or custom Apex/API integration to sync data. Map DMTR entities to Salesforce records; use external IDs for deduplication. Configure triggers and flows for real-time updates. Salesforce integration requires a connected app and OAuth configuration; contact the integrations team for setup.
HubSpot
HubSpot integration maps DMTR participants to contacts and companies, and positions to deals or custom objects. Use the HubSpot API and webhooks for bidirectional sync. Configure property mappings for DMTR-specific fields (registry status, transferability). HubSpot integration supports both server-to-server and user-delegated flows. Set up the integration via the DMTR dashboard or API.
Custom CRM
Custom CRM integrations follow the same patterns as Salesforce and HubSpot: define entity mappings, implement sync logic (batch or real-time), and handle authentication. Use the DMTR REST API and webhooks; implement idempotency for writes. Custom CRMs may require additional development for mapping and transformation. Document your data model and sync strategy for approval.
Data mapping
Data mapping defines how DMTR entities (Position, Participant, Transfer) map to CRM objects and fields. Use standard mappings where available (e.g., participant → contact); extend with custom fields for DMTR-specific data. Handle data type conversions (dates, enums, identifiers). Maintain mapping documentation and version it with integration changes. Validate mappings in sandbox before production.
Sync patterns
Sync patterns include full sync (initial load or periodic reconciliation), incremental sync (delta updates by timestamp or cursor), and event-driven sync (webhook-triggered updates). Choose based on data volume and latency requirements. Implement conflict resolution for bidirectional sync (last-write-wins or custom logic). Monitor sync health and alert on failures or drift.