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Qbr Quarterly Business Review

Built from: Autotask PSA

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Multiple data sources combined

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Qbr Quarterly Business Review

This report provides a detailed breakdown of qbr quarterly business review for managed service providers.

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: Account managers, MSP owners, and vCTOs preparing executive reviews

How often: Quarterly for scheduled QBRs, on-demand for executive briefings

Time saved

Building QBR decks from scratch takes days of data gathering. This report provides the foundation in minutes.

Executive summary

High-level KPIs and trends formatted for non-technical stakeholders.

Client value

Demonstrates the measurable impact of your MSP services with hard numbers.

Report categoryQBR & Executive

Data sourceAutotask PSA · SmileBack

RefreshReal-time via Power BI

Generation timeUnder 15 minutes

AI requiredClaude, ChatGPT or Copilot

AudienceAccount managers, MSP owners

Where to find this in Proxuma

Power BI › QBR › Qbr Quarterly Business Review

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QBR Report

Can we automate our quarterly business review?

Quarterly Business Review (QBR) 2024

A full-year overview of your MSP operations, revenue, expenses, sales, and business health. Generated automatically from your PSA data in seconds.

Built from: Autotask PSA Datto RMM

THE QUESTION WE ASKED

"Can we generate our quarterly peer group business review from our PSA data, automatically?"

One question. The AI connected to Power BI, cross-referenced PSA ticket data, revenue records, employee data, and sales pipeline. It generated this full QBR report in under two minutes.

Every quarter, MSP owners spend hours pulling numbers from their PSA, accounting software, and CRM to fill in a spreadsheet for their peer group. The data is scattered, the formulas break, and by the time it's done, the quarter is already over.

With Proxuma's Power BI integration, this same report is generated in under two minutes. All numbers flow from your live PSA data. No copy-pasting. No broken formulas. Just ask the question and get the answer.

Total Revenue 2024

$1.98M

+14.8% vs Q1 run rate

MRR (Dec)

$94,000

Up from $82,000 in Jan

Net Profit Margin

11.2%

Full-year average

Seats Managed

645

+11.2% growth YoY

General Overview

Headcount, endpoints, and agreement count across 2024. The company grew steadily from 42 to 47 managed services agreements while maintaining a stable team of 18 FTE.

Metric	Q1	Q2	Q3	Q4	Trend
Endpoints Managed	630	648	660	680	+7.9%
Seats Managed	590	608	625	645	+9.3%
Managed Services Agreements	42	44	45	47	+11.9%
Total Employees (FTE)	18	18	18	18	0%
Support Desk Employees	5	5	5	5	0%
Professional Services	3	3	3	3	0%
Alignment Engineers	2	2	2	2	0%
vCIO Employees	1	1	1	1	0%
Technical Employees	14	14	14	14	0%

View DAX Query — General company metrics per quarter

EVALUATE
SUMMARIZECOLUMNS(
    'BI_Common_Dim_Date'[quarter_name],
    "ActiveCompanies", DISTINCTCOUNT(BI_Autotask_Billing_Items[company_id]),
    "TotalTickets", COUNTROWS(BI_Autotask_Tickets),
    "TotalHoursWorked", SUM(BI_Autotask_Time_Entries[hours_worked])
)
ORDER BY 'BI_Common_Dim_Date'[quarter_name]

Revenue Breakdown

Total revenue grew from $462K in Q1 to $533K in Q4. MRR was the dominant driver at 60-65% of all services revenue, growing consistently each month.

Revenue Line	Q1	Q2	Q3	Q4	Full Year
Monthly Recurring Revenue (MRR)	$249,000	$258,500	$267,500	$277,000	$1,052,000
Non-recurring Revenue (NRR)	$145,000	$155,000	$150,000	$185,000	$635,000
Other Recurring Revenue (ORR)	$25,500	$27,000	$28,500	$30,000	$111,000
All Services Revenue	$419,500	$440,500	$446,000	$492,000	$1,798,000
Product Sales	$55,000	$72,000	$60,000	$92,000	$279,000
Miscellaneous Revenue	$9,000	$10,500	$9,300	$12,500	$41,300
Total Revenue	$483,500	$523,000	$515,300	$596,500	$2,118,300

$483K

$483,500

$523K

$523,000

$515K

$515,300

$597K

$596,500

View DAX Query — Revenue breakdown per quarter

EVALUATE
SUMMARIZECOLUMNS(
    'BI_Common_Dim_Date'[quarter_name],
    "Revenue", SUM(BI_Autotask_Billing_Items[total_amount]),
    "Cost", SUM(BI_Autotask_Billing_Items[our_cost]),
    "Profit", SUM(BI_Autotask_Billing_Items[total_amount]) - SUM(BI_Autotask_Billing_Items[our_cost])
)
ORDER BY 'BI_Common_Dim_Date'[quarter_name]

Expenses

Total expenses grew modestly at 5.6% across the year, driven primarily by payroll and tools COGS. Owner compensation stayed flat in H1 and increased by $1,000/mo in H2.

Expense Category	Q1	Q2	Q3	Q4	Full Year
Employee Expense	$216,000	$219,000	$222,000	$225,000	$882,000
Owner Compensation	$45,000	$45,000	$48,000	$48,000	$186,000
Product COGS	$36,500	$47,500	$39,500	$60,700	$184,200
MRR Tools COGS	$54,600	$56,400	$58,200	$60,000	$229,200
ORR COGS	$10,200	$10,800	$11,400	$12,000	$44,400
All Other Expenses	$66,000	$69,000	$70,500	$72,000	$277,500
Total Expenses	$428,300	$447,700	$449,600	$477,700	$1,803,300

View DAX Query — Expense categories per quarter

EVALUATE
SUMMARIZECOLUMNS(
    'BI_Common_Dim_Date'[quarter_name],
    "TotalCost", SUM(BI_Autotask_Billing_Items[our_cost]),
    "BillingItems", COUNTROWS(BI_Autotask_Billing_Items),
    "AvgCostPerItem", DIVIDE(SUM(BI_Autotask_Billing_Items[our_cost]), COUNTROWS(BI_Autotask_Billing_Items))
)
ORDER BY 'BI_Common_Dim_Date'[quarter_name]

Service Desk Operations

Ticket volume grew 8% across the year while the close rate stayed above 100% in every quarter, meaning the team consistently closed their backlog. Average resolution time held steady at ~1.5 hours per ticket.

Metric	Q1	Q2	Q3	Q4
Reactive Tickets Created	1,190	1,215	1,195	1,270
Reactive Tickets Closed	1,195	1,220	1,200	1,285
Total Close %	100.4%	100.4%	100.4%	101.2%
Reactive Hours (total)	1,785	1,823	1,792	1,906
Tickets / SD Tech / Month	79.7	81.3	80.0	85.7
Tickets / Seat / Month	0.67	0.67	0.64	0.66
RHEM (Hours / Seat / Mo)	1.01	1.00	0.96	0.98
Avg Resolution Time (hrs)	1.49	1.49	1.49	1.48
Reactive Service %	23.5%	24.0%	23.6%	25.1%

View DAX Query — Service desk operations metrics

EVALUATE
SUMMARIZECOLUMNS(
    'BI_Common_Dim_Date'[quarter_name],
    "TicketsCreated", COUNTROWS(BI_Autotask_Tickets),
    "TicketsClosed", CALCULATE(COUNTROWS(BI_Autotask_Tickets), BI_Autotask_Tickets[status_name] = "Complete"),
    "AvgResolutionDays", AVERAGE(BI_Autotask_Tickets[resolved_due_age_days]),
    "TotalHoursWorked", SUM(BI_Autotask_Time_Entries[hours_worked])
)
ORDER BY 'BI_Common_Dim_Date'[quarter_name]

Profitability

Net profit margin improved from 11.4% in Q1 to 19.9% in Q4, driven by MRR growth outpacing expense increases. Full-year net profit was $315K on $2.1M revenue.

Q1 Net Profit

$55,200

11.4% margin

Q2 Net Profit

$75,300

14.4% margin

Q3 Net Profit

$65,700

12.7% margin

Q4 Net Profit

$118,800

19.9% margin

Metric	Q1	Q2	Q3	Q4
Total Revenue	$483,500	$523,000	$515,300	$596,500
Total Expenses	$428,300	$447,700	$449,600	$477,700
Net Profit $	$55,200	$75,300	$65,700	$118,800
Net Profit %	11.4%	14.4%	12.7%	19.9%
% Revenue from Services	86.8%	84.2%	86.5%	82.5%
% Services from MRR	59.4%	58.7%	60.0%	56.3%

View DAX Query — Profitability per quarter

EVALUATE
ADDCOLUMNS(
    SUMMARIZECOLUMNS(
        'BI_Common_Dim_Date'[quarter_name],
        "Revenue", SUM(BI_Autotask_Billing_Items[total_amount]),
        "Cost", SUM(BI_Autotask_Billing_Items[our_cost])
    ),
    "NetProfit", [Revenue] - [Cost],
    "Margin", DIVIDE([Revenue] - [Cost], [Revenue])
)
ORDER BY 'BI_Common_Dim_Date'[quarter_name]

Sales Pipeline

The sales team delivered 17 new agreements with $37,800 in new monthly recurring revenue across 2024. The close ratio averaged 28%, well within the peer group target of 15-30%.

Sales Activity	Q1	Q2	Q3	Q4
Telemarketing Dials	980	990	975	1,090
First Time Appts	12	15	12	18
Prospects to PBR	9	12	9	14
New Agreements	4	5	4	7
New Logo MRR $	$7,500	$10,000	$7,900	$13,500

Sales KPIs	Q1	Q2	Q3	Q4
Dials / Appointment	82	66	81	61
Sales Close %	33%	33%	33%	39%

View DAX Query — Sales pipeline per quarter

EVALUATE
ROW(
    "TotalOpportunities", COUNTROWS(BI_Autotask_Opportunities),
    "WonDeals", CALCULATE(COUNTROWS(BI_Autotask_Opportunities), BI_Autotask_Opportunities[status_name] IN {"Closed", "Implemented"}),
    "TotalPipelineValue", SUM(BI_Autotask_Opportunities[amount]),
    "WonValue", CALCULATE(SUM(BI_Autotask_Opportunities[amount]), BI_Autotask_Opportunities[status_name] IN {"Closed", "Implemented"}),
    "CloseRate", DIVIDE(
        CALCULATE(COUNTROWS(BI_Autotask_Opportunities), BI_Autotask_Opportunities[status_name] IN {"Closed", "Implemented"}),
        COUNTROWS(BI_Autotask_Opportunities))
)

MRR Movement

Net MRR grew every quarter. Churn cost $9,100 across the year (4 lost agreements), but new logo acquisition and existing account growth more than compensated.

MRR Movement	Q1	Q2	Q3	Q4	Full Year
New Logo MRR	+$7,500	+$10,000	+$7,900	+$13,500	+$38,900
Existing MRR Growth	+$3,500	+$3,300	+$3,900	+$5,100	+$15,800
Existing MRR Decrease	-$1,200	-$1,000	-$850	-$750	-$3,800
Lost MRR (Churn)	-$3,700	-$1,800	-$2,100	-$1,500	-$9,100
Lost Agreements (#)	2	1	2	1	6
Net MRR Gain $	+$6,100	+$10,500	+$8,850	+$16,350	+$41,800

View DAX Query — MRR movement analysis

EVALUATE
SUMMARIZECOLUMNS(
    'BI_Common_Dim_Date'[quarter_name],
    "Revenue", SUM(BI_Autotask_Billing_Items[total_amount]),
    "NewCompanies", DISTINCTCOUNT(BI_Autotask_Billing_Items[company_id]),
    "BillingItems", COUNTROWS(BI_Autotask_Billing_Items)
)
ORDER BY 'BI_Common_Dim_Date'[quarter_name]

Leverage Ratios

Key efficiency metrics compared against peer group benchmarks. Average AISP at $141-146 sits comfortably in the $100-$150 target range. Service revenue per employee is tracking toward the $150K annual benchmark.

Leverage Metric	Q1	Q2	Q3	Q4	Target
Ann. Svc Revenue / Employee	$139,778	$146,833	$148,667	$164,000	$150,000
Ann. Svc Revenue / Tech Employee	$179,571	$188,786	$191,143	$210,857	$250,000
Seats / SD Employee	118	122	125	129
Tools COGS % of Svc Rev	13.0%	12.8%	13.0%	12.2%
Tools COGS / Seat (monthly)	$30.85	$30.92	$31.20	$31.01
Payroll % of Svc Revenue	62.2%	60.0%	60.9%	55.5%
MRR / SD Employee	$16,600	$17,167	$17,833	$18,467
MRR / Alignment Engineer	$41,500	$42,917	$44,583	$46,167
MRR / vCIO	$83,000	$85,833	$89,167	$92,333
NRR / PS Employee	$48,333	$51,667	$50,000	$61,667
NRR to MRR Ratio	0.58	0.60	0.56	0.67	0.32
Average AISP	$141	$142	$143	$146	$100-$150
Average MRR / Agreement	$1,976	$1,955	$1,978	$1,979	$1,800-$3,000
Product Margin	33.6%	34.0%	34.2%	34.0%

View DAX Query — Leverage and efficiency ratios

EVALUATE
ADDCOLUMNS(
    SUMMARIZECOLUMNS(
        'BI_Common_Dim_Date'[quarter_name],
        "Revenue", SUM(BI_Autotask_Billing_Items[total_amount]),
        "Cost", SUM(BI_Autotask_Billing_Items[our_cost]),
        "HoursWorked", SUM(BI_Autotask_Time_Entries[hours_worked]),
        "ActiveCompanies", DISTINCTCOUNT(BI_Autotask_Billing_Items[company_id])
    ),
    "RevenuePerCompany", DIVIDE([Revenue], [ActiveCompanies]),
    "ProfitMargin", DIVIDE([Revenue] - [Cost], [Revenue]),
    "EffectiveRate", DIVIDE([Revenue], [HoursWorked])
)
ORDER BY 'BI_Common_Dim_Date'[quarter_name]

Business Health

The Turning Point (revenue minus expenses plus owner compensation) shows how much the business produces before the owner is paid. All quarters show positive and growing health.

Health Metric	Q1	Q2	Q3	Q4
Turning Point (quarterly)	$100,200	$120,300	$113,700	$166,800
Existing MRR Performance	+0.9%	+0.9%	+1.1%	+1.6%
Net MRR Gain $	+$6,100	+$10,500	+$8,850	+$16,350
Net MRR Gain %	+2.4%	+4.1%	+3.3%	+5.9%

View DAX Query — Business health indicators

EVALUATE
ADDCOLUMNS(
    SUMMARIZECOLUMNS(
        'BI_Common_Dim_Date'[quarter_name],
        "Revenue", SUM(BI_Autotask_Billing_Items[total_amount]),
        "Cost", SUM(BI_Autotask_Billing_Items[our_cost])
    ),
    "NetProfit", [Revenue] - [Cost],
    "ProfitMargin", DIVIDE([Revenue] - [Cost], [Revenue]),
    "CostRatio", DIVIDE([Cost], [Revenue])
)
ORDER BY 'BI_Common_Dim_Date'[quarter_name]

The numbers paint a clear picture. This MSP is growing at a healthy pace, with MRR up 14.6% and a service team that's keeping up with rising ticket volumes without adding headcount. Here's what stands out from the data.

Key Insights

Automatically generated observations from the data patterns.

MRR growth is outpacing expenses

Monthly recurring revenue grew from $82K to $94K (+14.6%) while total expenses only grew 11.5%. Revenue is scaling faster than cost.

Close rate is above peer group benchmark

The sales close ratio of 33-39% exceeds the peer group target of 15-30%. The sales team is efficient at converting appointments into agreements.

NRR-to-MRR ratio is above target

At 0.56-0.67, the NRR-to-MRR ratio is above the 0.32 benchmark. A high share of revenue comes from project work. While profitable now, more MRR would provide more predictable cash flow.

Technical revenue per employee is below target

Annualized service revenue per technical employee ($179K-$211K) is below the $250K peer group target. Adding seats without hiring more technical staff would close this gap.

Average AISP is in the target range

AISP of $141-146 per seat is in the $100-$150 target range, indicating competitive and sustainable pricing.

Ticket backlog is under control

Close percentage above 100% in all four quarters means the team is consistently clearing more tickets than are coming in. No growing backlog.

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Qbr Quarterly Business Review

Qbr Quarterly Business Review

Quarterly Business Review (QBR) 2024

Full-Year QBR Dashboard

General Overview

Revenue Breakdown

Expenses

Service Desk Operations

Profitability

Sales Pipeline

MRR Movement

Leverage Ratios

Business Health

Key Insights

MRR growth is outpacing expenses

Close rate is above peer group benchmark

NRR-to-MRR ratio is above target

Technical revenue per employee is below target

Average AISP is in the target range

Ticket backlog is under control

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