Migrate from Orderry to HighLevel

Orderry client profiles map directly to HighLevel contacts. Client name, phone, email, address, and custom fields transfer as contact fields. Orderry client notes become HighLevel contact notes. A separate Companies record can be created if the client is a business entity.

Orderry work orders become HighLevel opportunities in a dedicated Service Pipeline. Job status (New, In Progress, Completed, Invoiced) maps to pipeline stage values. Work order number, description, and assigned technician transfer as opportunity fields and custom fields, preserving any internal references and timestamps for downstream reporting.

Each Orderry work order status value maps to a corresponding HighLevel pipeline stage, ensuring that the lifecycle of a job is represented accurately in the CRM. Status transitions are preserved as stage‑change timestamps stored in custom datetime fields, which allows you to build reports on job duration and identify bottlenecks across the pipeline.

Orderry product catalog does not have a native HighLevel equivalent. Products migrate as a custom object with fields for name, SKU, unit price, stock quantity, and reorder level. HighLevel does not support automatic inventory deduction; reorder logic requires Workflow rebuild.

Products and services added to Orderry work orders transfer as line items on the HighLevel opportunity, preserving unit price, quantity, and discount information. Taxes and rounding rules are recorded as notes on the opportunity to ensure financial accuracy and to support any future invoicing or reporting needs.

Orderry employee records with name, email, and role transfer to HighLevel users, allowing technician assignments on opportunities, tasks, and workflow actions. Email matching resolves the correct HighLevel user ID, and any inactive Orderry employees become inactive HighLevel users to reflect current staffing levels.

Orderry estimates map to HighLevel opportunities either in a separate Estimates pipeline or as a custom field flag on the main opportunity, preserving estimate total, line items, and approval status. Accepted estimates can trigger stage progression via a HighLevel Workflow, ensuring that your sales process continues smoothly after conversion.

Orderry invoices transfer as records in a custom Invoices object linked to the opportunity, storing invoice number, date, total, balance due, and payment status as custom fields. Because HighLevel lacks native invoicing, these records serve as reference data for reconciliation, and your team can update the payment status through manual entry or Workflow‑driven triggers.

Orderry multi‑location data requires a migration decision: either create HighLevel sub‑accounts per location to preserve isolation and location‑specific access controls, or add a Location__c custom field on contacts and opportunities for a single‑account view. FlitStack delivers a location‑mapping worksheet during the pre‑migration audit, guiding your team through the choice and detailing how inventory and employee assignments will be distributed.

Orderry file attachments on work orders and client profiles are uploaded to HighLevel as files linked to the corresponding contact or opportunity record, preserving the original file name and metadata. Note that HighLevel imposes file size limits per record; any files exceeding these limits may need to be stored externally and referenced via a URL custom field.

Orderry time entries linked to work orders become custom fields on the HighLevel opportunity, capturing total hours worked, hourly rate, and labor cost. The original time entry timestamps are stored in a custom datetime field, enabling technician performance reporting, payroll integration, and historical analysis of labor allocation across jobs.

Orderry custom fields on work orders—such as service type, priority level, dispatch method, or warranty flag—migrate as custom fields on the HighLevel opportunity object, preserving their data type and pick‑list values. Field type matching is enforced during migration: pick‑list to pick‑list, text to text, date to date, ensuring data integrity and enabling consistent filtering and reporting.