Connect QuickBooks Online and ConnectWise.

Connect QuickBooks Online data ...

... to ConnectWise, seamlessly.

Integration #1: QuickBooks Online

Integration #2: ConnectWise

Invoice Total Amount + Ticket Actual Hours = Revenue per Service Hour

Customer Current Balance + Agreement Monthly Amount = Contract Coverage Ratio

Invoice Balance Due + Time Entry Billable Hours = Unbilled Time Value

Sales Receipt Total Amount + Member Target Utilization % = Technician Revenue Performance

Bill Total Amount + Company Open Ticket Count = Project Cost Variance

Customer Total Sales + Company Open Ticket Count = Revenue per Support Ticket

Invoice Line Item Count + Service Board Total Tickets = Billing Complexity Index

Invoice Transaction Date + Agreement Hours Used = Contract Burn Rate

Item Unit Price + Work Type Default Rate = Service Line Profitability

Invoice Due Date + Activity Activity Type = Client Engagement Score

Extract true business intelligence insights in seconds.

Invoice Total Amount

Ticket Actual Hours

Revenue per Service Hour

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Customer Current Balance

Agreement Monthly Amount

Contract Coverage Ratio

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Invoice Balance Due

Time Entry Billable Hours

Unbilled Time Value

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Sales Receipt Total Amount

Member Target Utilization %

Technician Revenue Performance

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Bill Total Amount

Company Open Ticket Count

Project Cost Variance

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Customer Total Sales

Company Open Ticket Count

Revenue per Support Ticket

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Invoice Line Item Count

Service Board Total Tickets

Billing Complexity Index

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Invoice Transaction Date

Agreement Hours Used

Contract Burn Rate

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Item Unit Price

Work Type Default Rate

Service Line Profitability

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Invoice Due Date

Activity Activity Type

Client Engagement Score

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Choose a data point...

...literally any one you like

Increased efficiency and profits

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Curious? Explore more
or
data integration possibilities.

Combining QuickBooks Online and ConnectWise data has never been so easy...

Break down the silos between finance and operations by integrating QuickBooks Online and ConnectWise through Resplendent Data. This powerful pairing connects the dots between revenue and real-time service metrics giving you visibility into areas like project cost variance, technician revenue performance, and even client engagement scores, all in the context of your financials.

By unifying these platforms, you can transform disconnected data into actionable intelligence to make faster, smarter decisions that drive your business forward.

How it works...

Resplendent Data transforms raw data from the tools and apps you're already using into actionable, visual dashboards in a few short steps.

Integrations

These are your apps and databases that contain data waiting to be visualized.

Datasets

Each dataset represents one category of data, such as clients, tasks, tickets, or invoices.

Invoices

Clients

Time Entries

Tickets

Joined Datasets

Joined datasets are created by combining data from two standard datasets.

All Data Combined

Modified Datasets

Modified datasets clean or modify data before visualization, such as replacing text or performing calculations.

Filter internal tickets

Remove duplicate tickets

Standardize ticket types

Widgets

Widgets turn the data from any dataset into a visual representation.

Revenue MTD
$1.26M
Tickets by Type
Revenue YTD
$7.81M
Hours by Client
Hours by Technician

Simple

A basic example of data flowing directly from the source to dashboard widgets.

Integrations

These are your apps and databases that contain data waiting to be visualized.

Datasets

Each dataset represents one category of data, such as clients, tasks, tickets, or invoices.

Invoices

Widgets

Widgets turn the data from any dataset into a visual representation.

Revenue MTD
$1.26M
Revenue YTD
$7.81M

Advanced

A robust example of preparing data for even more helpful insights and visualization.

Integrations

These are your apps and databases that contain data waiting to be visualized.

Datasets

Each dataset represents one category of data, such as clients, tasks, tickets, or invoices.

Clients

Time Entries

Tickets

Joined Datasets

Joined datasets are created by combining data from two standard datasets.

All Data Combined

Modified Datasets

Modified datasets clean or modify data before visualization, such as replacing text or performing calculations.

Filter internal tickets

Remove duplicate tickets

Standardize ticket types

Widgets

Widgets turn the data from any dataset into a visual representation.

Hours by Client
Tickets by Type

Ready to see it (and believe it)?

Let's dive in. Start a free account or schedule a demo and we'll walk you through it.

P.S. You can do both and we'll use your own data for the demo.