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What is the revenue trajectory for new clients?

New Client Revenue Trajectory

A data-driven analysis of new client revenue trajectory from your Power BI environment, with breakdowns and actionable findings.

Built from: Autotask PSA

How this report was made

Autotask PSA

Multiple data sources combined

Proxuma Power BI

Pre-built MSP semantic model, 50+ measures

AI via MCP

Claude or ChatGPT writes DAX queries, executes them, formats output

4
This Report
KPIs, breakdowns, trends, recommendations

                Ready in < 15 min

New Client Revenue Trajectory

This report analyzes new client revenue trajectory using data from Autotask PSA.

The data covers the full scope of Autotask PSA records relevant to this analysis, broken down by the key dimensions your team needs for day-to-day decisions and client reporting.

Who should use this: MSP owners, finance leads, and operations managers tracking profitability

How often: Monthly for financial reviews, quarterly for strategic planning, on-demand for pricing decisions

Time saved

Building financial reports from PSA exports and spreadsheets is a full day of work. This report delivers it in minutes.

Margin visibility

Revenue numbers alone do not tell the story. This report connects revenue to cost for true profitability.

Pricing intelligence

Data-driven evidence for pricing adjustments, contract negotiations, and resource allocation.

Report categoryFinancial & Revenue

Data sourceAutotask PSA · Datto RMM · Datto Backup · Microsoft 365 · SmileBack · HubSpot · IT Glue

RefreshReal-time via Power BI

Generation timeUnder 15 minutes

AI requiredClaude, ChatGPT or Copilot

AudienceMSP owners, finance leads

Where to find this in Proxuma

Power BI › Financial › New Client Revenue Trajectory

Get this report for your MSP

What you can measure in this report

Summary Metrics

Revenue by Company

Monthly Revenue Trend

Contracts by Type

Analysis

Recommended Actions

Frequently Asked Questions

TOTAL REVENUE

TOTAL CONTRACTS

AI-Generated Power BI Report

New Client Revenue Trajectory

A data-driven analysis of new client revenue trajectory from your Power BI environment, with breakdowns and actionable findings.

Demo Report: This report uses synthetic data to demonstrate AI-generated insights from Proxuma Power BI. The structure, DAX queries, and analysis reflect real MSP data patterns.

1.0 Summary Metrics

TOTAL REVENUE

€10,539,134

15 clients

TOTAL CONTRACTS

1,889

4 contract types

View DAX Query — Summary query

-- Combined summary metrics from Power BI dataset

What are these DAX queries? DAX (Data Analysis Expressions) is the formula language Power BI uses to query data. Each collapsible section below shows the exact query the AI wrote and ran. You can copy any query and run it in Power BI Desktop against your own dataset.

1.0 Revenue by Company

Revenue breakdown by company from billing data

Montgomery-Peck

214,468

Hahn Group

253,148

Wu-Jackson

321,669

Torres-Jones

255,698

Thompson, Contreras and R

320,831

Patterson, Riley and Laws

416,449

Richards, Bell and Christ

328,164

Burke, Armstrong and Morg

469,660

Price-Gomez

286,926

Little Group

1,431,177

Metric	Value
Total Revenue	$17,606,769
Won Deals	18
Won Amount	$49,540

View DAX Query — Revenue by Company query

EVALUATE ROW("Revenue", SUM('BI_Autotask_Billing_Items'[total_amount]), "WonDeals", CALCULATE(COUNTROWS('BI_HubSpot_Deals'), 'BI_HubSpot_Deals'[deal_stage] = "closedwon"), "WonAmount", CALCULATE(SUM('BI_HubSpot_Deals'[amount]), 'BI_HubSpot_Deals'[deal_stage] = "closedwon"))

2.0 Monthly Revenue Trend

Monthly revenue trend over the observed period

Month	Revenue
202502	€1,051,887
202503	€1,106,650
202504	€1,341,613
202505	€1,080,821
202506	€1,033,307
202507	€1,045,558
202508	€1,058,862
202509	€1,002,352
202510	€1,006,188
202511	€927,812
202512	€887,195
202601	€770,865

View DAX Query — Monthly Revenue Trend query

EVALUATE TOPN(12, SUMMARIZECOLUMNS('BI_Common_Dim_Date'[year_month], "Revenue", SUM('BI_Autotask_Billing_Items'[total_amount])), 'BI_Common_Dim_Date'[year_month], DESC)

3.0 Contracts by Type

Distribution of contracts across types

Recurring Service (1,207)

Time & Materials (504)

Block Hours (173)

Fixed Price (5)

Type	Count
Recurring Service	1,207
Time & Materials	504
Block Hours	173
Fixed Price	5

View DAX Query — Contracts by Type query

EVALUATE SUMMARIZECOLUMNS('BI_Autotask_Contracts'[contract_type_name], "Count", COUNTROWS('BI_Autotask_Contracts'))

5.0 Analysis

What the data is telling us

The data above paints a picture of new client revenue trajectory across your MSP operations. Look for patterns, outliers, and trends that warrant attention. Each section includes the DAX query used, so you can drill deeper into any metric that catches your eye.

6.0 Recommended Actions

✓

1. Schedule Recurring Review

Set up a weekly or monthly review of new client revenue trajectory metrics. Trends matter more than snapshots. Use the DAX queries in this report as your starting point.

✓

2. Connect Your Own Data

This report uses demo data. Connect Proxuma Power BI to your own Autotask PSA to generate this analysis from your real numbers.

7.0 Frequently Asked Questions

What data sources does the New Client Revenue Trajectory report use?

This report pulls data from PSA through the Proxuma Power BI integration, using DAX queries against the live data model.

How often is this data refreshed?

The underlying Power BI dataset refreshes daily. Reports can be regenerated at any time for the latest figures.

Can I customize this new client revenue trajectory report?

Yes. Proxuma reports are fully customizable. You can modify the DAX queries, add new sections, or adjust the analysis to match your specific MSP needs.

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