Bookings to CRM Customer Record Sync

Overview

When a Microsoft Bookings appointment is created, this flow builds and maintains a customer record in Dataverse: it matches or creates the customer, tags them New vs Returning, increments their visit count, and logs the appointment as a visit activity capturing service, staff, and times. An Outlook notification summarizes each sync. Built API-first as a Dataverse workflow record; ships Off.

Why it matters: Bookings holds rich interaction data that's lost if it never reaches the CRM. Syncing it automatically builds a complete, governed customer history for marketing and service - with zero manual data entry.

Status: Built. Solution: FlowLibs - Bookings to CRM Customer Record Sync.

Use Case

A services team (salons, clinics, advisory, repair, etc.) takes bookings through Microsoft Bookings. They want every appointment reflected on the customer's CRM record automatically, so sales and operations always see the full visit history and can tell first-timers from regulars.

Flow Architecture

Environment Variables

Connectors & Connections

Connector	API name	Actions used
Microsoft Bookings	shared_microsoftbookings	CreateAppointment
Microsoft Dataverse	shared_commondataserviceforapps	ListRecords CreateRecord UpdateRecord
Office 365 Outlook	shared_office365	SendEmailV2

Note — All connections are referenced as solution connection references; the flow is portable between environments as long as a connection is mapped at import time.

Customization Guide

Almost every realistic variant of this flow can be implemented by changing environment variable values. A few cases require small edits inside the flow definition — those are called out explicitly below.

Marketing sync

After Create/Update Customer, add the customer to a Mailchimp/Dataverse marketing segment based on Customer Type.

Lifetime value

Add a money column on Booking Customer and accumulate each visit's value.

True relationship

Replace the email-key link with a Dataverse N:1 lookup from Booking Visit to Booking Customer.

Returning logic by visit history

Instead of (or in addition to) the customer row, count prior rows in the visit table for that email to classify Returning.

Service/staff preferences

Track most-frequent service and staff per customer for personalization.

Key Expressions

The flow is intentionally light on Power Fx / WDL gymnastics — the heaviest expressions are the branch-name concatenation and the approval outcome check. They are listed below in the order they appear in the flow.

@variables('varCustomerEmail') <- @{triggerBody()?['CustomerEmail']}

@concat('flowlibs_email eq ''', variables('varCustomerEmail'), '''')

@greater(length(coalesce(outputs('List_Matching_Customers')?['body/value'], json('[]'))), 0)

@add(coalesce(first(outputs('List_Matching_Customers')?['body/value'])?['flowlibs_totalvisits'],0),1)

@{first(outputs('List_Matching_Customers')?['body/value'])?['flowlibs_bookingcustomerid']}

@{string(triggerBody()?['StaffMembers'])}

Customize & download