Sage 300 and Mailchimp integration

What moves between them

ARCustomers and contact details flow from Sage 300 into Mailchimp lists as members. OEOrders and their line items flow from Sage 300's order entry system into Mailchimp's e-commerce store, tracked with order status and total amount to enable revenue attribution on email campaigns. The sync is unidirectional from Sage 300 into Mailchimp. Mailchimp can push list member events (subscribe, unsubscribe, profile update) back via webhook if registered, allowing you to capture list changes for external audit or logging. Polling runs on a schedule you define, typically daily or after each order cycle.

How ml-connector handles it

ml-connector manages separate credential sets for each system: Sage 300 credentials (username and password, both required uppercase) and Mailchimp API key or OAuth token. On the Sage 300 side it builds HTTP Basic Auth headers on each request, polls ARCustomers and OEOrders using OData $filter on DocumentDate to retrieve only new and changed records, and handles pagination with $skip and $top. Mailchimp's data center is resolved from the API key suffix to build the correct endpoint URL. Customer records map to Mailchimp list members with email as the key field; order records map to e-commerce orders with order totals and line items as products. Because Sage 300 has no webhooks, polling is pull-based on a schedule; Mailchimp webhooks are optional and can push events to ml-connector if enabled. Every record carries a job ID for retry deduplication and a full audit trail.

A real-world example

A regional distributor runs Sage 300 for order entry and accounting across multiple sales territories. They use Mailchimp for customer newsletters and campaign analytics. Before the integration, the marketing team manually exported customer lists from Sage 300 every quarter and uploaded them to Mailchimp, and order revenue was tracked manually in spreadsheets. With Sage 300 and Mailchimp connected, the customer audience updates automatically on a nightly poll, new customers appear in lists within hours, and each order flows into Mailchimp's e-commerce tracking so campaign revenue is attributed back to the email that drove it. Marketing can now see exactly which campaigns converted for which customer segments without re-keying any data.

What you can do

• •Sync ARCustomers from Sage 300 into Mailchimp list members, keeping audience data current with nightly polls.
• •Flow OEOrders and line items into Mailchimp e-commerce orders for revenue attribution on campaigns.
• •Handle Sage 300's uppercase HTTP Basic Auth and Mailchimp's API key or OAuth 2 with automatic credential encryption.
• •Poll Sage 300 on a schedule using OData date filters to capture only new and changed records since the last run.
• •Track every sync with a full audit trail and replay capability if a downstream write to Mailchimp fails.

Questions

Which direction does data flow between Sage 300 and Mailchimp?

The main flow is from Sage 300 into Mailchimp. Customer records (ARCustomers) sync into Mailchimp list members, and order records (OEOrders) sync into e-commerce orders for campaign revenue tracking. Mailchimp list member events (subscribe, unsubscribe, profile change) can push back via webhook if enabled for audit logging.

Why does Sage 300 require uppercase usernames and passwords in the API?

Sage 300's HTTP Basic Auth is case-sensitive and expects both username and password in uppercase as a security design. ml-connector automatically uppercases credentials before building the auth header, so you can store them in any case and the integration handles the transformation.

How does ml-connector capture new orders from Sage 300 without webhooks?

Sage 300 has no webhooks, so ml-connector polls OEOrders on a schedule you define, using OData $filter on DocumentDate to retrieve only records created or changed since the last poll. This keeps the customer experience consistent even on a system that is pull-only.