Multi-Platform Sync Guide

When your business uses three or more platforms, syncing data across all of them requires careful planning. This guide walks you through setting up a hub-and-spoke model to keep data consistent everywhere.

Overview

Goal: Sync contacts, deals, or other records across multiple platforms (e.g., HubSpot + Jobber + QuickBooks) using one system as the central source of truth.

What You'll Achieve:

• A single "hub" system that owns the master record
• Spoke systems that stay in sync with the hub
• Consistent field formats across all platforms
• Clear conflict resolution rules

Time Required: 30-45 minutes per spoke connection

The Hub-and-Spoke Model

Instead of creating mappings between every pair of systems (which grows exponentially), designate one platform as the hub:

                 ┌─────────┐
                 │  Jobber  │
                 └────▲─────┘
                      │
┌───────────┐    ┌────┴─────┐    ┌──────────────┐
│ Pipedrive │◄──►│  HubSpot │◄──►│  QuickBooks   │
└───────────┘    │  (Hub)   │    └──────────────┘
                 └────┬─────┘
                      │
                 ┌────▼─────┐
                 │Salesforce│
                 └──────────┘

Why not connect everything to everything?

With 4 platforms, direct connections require 6 mappings. With 5 platforms, you need 10. The hub-and-spoke model keeps it linear: each spoke only maps to the hub.

Step 1: Choose Your Hub

Pick the platform that best fits as your central system:

General rule: Choose the platform where data is created first or updated most frequently.

Step 2: Plan Your Mappings

For each spoke, decide what data flows and in which direction:

Example: HubSpot (Hub) with Jobber + QuickBooks

HubSpot ↔ Jobber:

• Contacts ↔ Clients (bidirectional)
• Deals → Jobs (one-way)
• See the HubSpot + Jobber guide for details

HubSpot → QuickBooks:

• Contacts → Customers (one-way)
• Deals → Invoices (one-way, on "Closed Won")

Jobber → HubSpot:

• Job status updates → Deal stage updates

Step 3: Standardize Field Formats

With multiple systems, format consistency is critical. Apply the same transformations across all spoke mappings:

Phone Numbers

Use the phone_e164 transform on every mapping that includes phone fields. This guarantees all systems store phones in the same format regardless of how they were entered.

Hub (HubSpot):    +15551234567  (E.164)
Spoke 1 (Jobber): +15551234567  (same)
Spoke 2 (QB):     +15551234567  (same)

Email Addresses

Apply lowercase and trim transforms to email fields across all mappings so matching works reliably.

Addresses

Pick a consistent approach (field-by-field or single-line) and use it for every spoke. See the Address Mapping guide for details.

Step 4: Configure Matching

Records must be matched reliably across all systems. Use the same matching field everywhere:

Recommended: Email address (with lowercase transform)

1. Set email as the Matching Field in every mapping
2. Enable Case Insensitive Matching
3. Consider storing hub record IDs in custom fields on each spoke for fallback matching

Cross-Reference IDs

For reliable matching, store the hub's record ID in each spoke system:

HubSpot Contact ID → Jobber custom field "hubspot_id"
HubSpot Contact ID → QuickBooks custom field "hubspot_id"

This prevents duplicates when email addresses change.

Step 5: Set Up Conflict Resolution

With multiple systems writing data, conflicts are inevitable. Establish clear ownership:

Field-Level Ownership

See Conflict Resolution for configuration details.

Step 6: Sequence Your Syncs

Order matters when multiple mappings depend on each other:

1. First: Sync contacts/clients between hub and all spokes
2. Second: Sync deals/jobs (these need existing contacts)
3. Third: Sync financial records (these need existing contacts and deals)

Scheduling Recommendations

• Hub ↔ Primary spoke: Every 15 minutes or real-time (webhooks)
• Hub → Secondary spokes: Hourly
• Status updates back to hub: Every 15 minutes

Stagger schedules to avoid overlapping syncs that could cause race conditions.

Step 7: Test the Full Chain

Before going live with all spokes:

1. Test each spoke independently — Verify hub ↔ spoke sync works in isolation
2. Test the chain — Create a record in the hub and verify it appears in all spokes
3. Test updates — Modify a record in one spoke and verify it flows through the hub to other spokes
4. Test conflicts — Update the same record in two spokes simultaneously and verify resolution

Common Pitfalls

Circular Updates

Problem: Hub updates Spoke A → Spoke A triggers webhook → Hub syncs again → infinite loop

Solution: FluxCascade tracks record versions and skips records that haven't actually changed since the last sync. Enable Change Detection in your mapping settings.

Stale Data Overwriting Fresh Data

Problem: A slow-running hourly sync overwrites a change made minutes ago by a faster sync.

Solution:

• Use consistent sync frequencies across related mappings
• Enable timestamp-based conflict resolution
• Consider webhook-triggered syncs for time-sensitive data

Duplicate Records

Problem: The same contact gets created in a spoke before the hub sync runs.

Solution:

• Always create records in the hub first
• Use matching fields that exist across all systems (email)
• Run an initial deduplication before enabling multi-platform sync

Scaling Beyond 5 Platforms

For large multi-platform setups:

1. Group by data domain — Customer data hub vs. financial data hub
2. Use connection groups — Organize related connections in FluxCascade
3. Monitor sync health — Check the Syncs page regularly for error trends
4. Document your architecture — Keep a diagram of which systems connect and who owns what

Next Steps

• HubSpot + Jobber Guide — Set up your first hub-spoke connection
• Conflict Resolution — Configure field ownership rules
• Scheduling — Fine-tune sync timing
• Webhooks — Enable real-time sync for critical data