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Deal Conversion Rate Analysis

Win rates, loss patterns, and pipeline performance across Autotask PSA and HubSpot CRM

Built from: HubSpot CRM

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

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KPIs, breakdowns, trends, recommendations

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Deal Conversion Rate Analysis

Win rates, loss patterns, and pipeline performance across Autotask PSA and HubSpot CRM

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: Sales leads, MSP owners, and account managers tracking pipeline health

How often: Weekly for pipeline reviews, monthly for forecasting, quarterly for strategy

Time saved

Building pipeline reports from CRM exports requires manual filtering and formatting. This report automates it.

Pipeline clarity

Deal stage distribution, win rates, and conversion patterns at a glance.

Forecast accuracy

Historical close rates and deal aging data to improve pipeline forecasting.

Report categorySales & Pipeline

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

AudienceSales leads, MSP owners

Where to find this in Proxuma

Power BI › Sales › Deal Conversion Rate Analysis

Get this report for your MSP

What you can measure in this report

Executive Summary

Pipeline Stage Breakdown

Win Rate by Sales Representative

Loss Reason Analysis

Win Reason Distribution

Client Conversion Performance

HubSpot CRM Deal Pipeline

Analysis

What Should You Do With This Data?

Frequently Asked Questions

Total Opportunities

Win Rate

AI-Generated Power BI Report

Deal Conversion Rate Analysis

Win rates, loss patterns, and pipeline performance across Autotask PSA and HubSpot CRM

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 Executive Summary

Key metrics at a glance across all 1,465 Autotask opportunities.

Total Opportunities

1,465

All time (Autotask PSA)

Win Rate

62.0%

832 won out of 1341 decided

Avg Days to Close

From creation to signed

Revenue Won

€3,967,265

vs €7,059,324 lost

View DAX Query — Overall Pipeline KPIs

EVALUATE
SUMMARIZECOLUMNS(
    "Total_Opportunities", COUNTROWS(BI_Autotask_Opportunities),
    "Won", CALCULATE(COUNTROWS(BI_Autotask_Opportunities),
        BI_Autotask_Opportunities[status_name] IN {"Closed", "Implemented"}),
    "Lost", CALCULATE(COUNTROWS(BI_Autotask_Opportunities),
        BI_Autotask_Opportunities[status_name] = "Lost"),
    "Active", CALCULATE(COUNTROWS(BI_Autotask_Opportunities),
        BI_Autotask_Opportunities[status_name] = "Active"),
    "Won_Value", CALCULATE(SUM(BI_Autotask_Opportunities[amount]),
        BI_Autotask_Opportunities[status_name] IN {"Closed", "Implemented"}),
    "Lost_Value", CALCULATE(SUM(BI_Autotask_Opportunities[amount]),
        BI_Autotask_Opportunities[status_name] = "Lost"),
    "Avg_Days_to_Close", AVERAGEX(
        FILTER(BI_Autotask_Opportunities,
            BI_Autotask_Opportunities[status_name] IN {"Closed", "Implemented"}
            && NOT(ISBLANK(BI_Autotask_Opportunities[closed_date]))),
        DATEDIFF(BI_Autotask_Opportunities[create_date],
            BI_Autotask_Opportunities[closed_date], DAY))
)

2.0 Pipeline Stage Breakdown

Where deals end up across each stage of the Autotask opportunity pipeline.

Every opportunity follows a path from proposal creation to a final outcome. Here is where deals end up across the entire pipeline.

Pipeline Stage	Deals	% of Total	Value
Proposal Created	31	2.1%	€757,155
Proposal Sent	46	3.1%	€3,059,497
Proposal Read	2	0.1%	€4,838
Signed, Scheduled	34	2.3%	€132,532
Signed, Converted to Project	190	13.0%	€1,970,631
Signed, Converted to Ticket	596	40.7%	€1,817,085
Expired / Stale	16	1.1%	€37,677
Lost (all stages)	509	34.7%	€7,059,324

The majority of losses (505 out of 509) happen at the "Proposal Sent" stage, before the client signs. Only 4 deals are lost after signing.

View DAX Query — Opportunities by Stage and Status

EVALUATE
SUMMARIZECOLUMNS(
    BI_Autotask_Opportunities[stage_name],
    BI_Autotask_Opportunities[status_name],
    "Count", COUNTROWS(BI_Autotask_Opportunities),
    "Total_Value", SUM(BI_Autotask_Opportunities[amount])
)
ORDER BY BI_Autotask_Opportunities[stage_name] ASC

3.0 Win Rate by Sales Representative

Individual performance of your top 7 sales reps, ranked by deal volume.

Performance varies significantly between sales reps. Tom Baker has the highest win rate at 86.9%, while David Rodriguez sits at 54.2%. The gap points to coaching opportunities.

Sales Rep	Won	Lost	Win Rate	Revenue Won
James Mitchell	175	94	65.1%	€727,314
Sarah Chen	131	75	63.6%	€963,520
Mike Thompson	120	27	81.6%	€383,222
David Rodriguez	115	97	54.2%	€145,852
Rachel Kim	94	40	70.1%	€367,393
Tom Baker	53	8	86.9%	€254,894
Lisa Park	45	21	68.2%	€192,376

View DAX Query — Win/Loss per Owner Resource

EVALUATE
SUMMARIZECOLUMNS(
    BI_Autotask_Opportunities[owner_resource_name],
    "Won", CALCULATE(COUNTROWS(BI_Autotask_Opportunities),
        BI_Autotask_Opportunities[status_name] IN {"Closed", "Implemented"}),
    "Lost", CALCULATE(COUNTROWS(BI_Autotask_Opportunities),
        BI_Autotask_Opportunities[status_name] = "Lost"),
    "Total_Value_Won", CALCULATE(SUM(BI_Autotask_Opportunities[amount]),
        BI_Autotask_Opportunities[status_name] IN {"Closed", "Implemented"})
)
ORDER BY [Won] DESC

4.0 Loss Reason Analysis

Why deals fail. Breakdown of 234 opportunities with documented loss reasons.

Excluding test data and blank entries (275 records), there are 234 losses with a documented reason. The single most expensive loss category: "Chose a competitor," accounting for €2,557,849 in lost revenue from just 23 deals.

Loss Reason	Count	% of Losses	Value Lost
Duplicate opportunity	67	28.6%	€461,683
Don't need the product	46	19.7%	€100,709
Bad timing	41	17.5%	€830,017
Customer not responding	35	15.0%	€189,744
Chose a competitor	23	9.8%	€2,557,849
Too expensive	14	6.0%	€407,468
Not interested	5	2.1%	€6,445
Missing features	3	1.3%	€19,717

View DAX Query — Loss Reasons with Value

EVALUATE
SUMMARIZECOLUMNS(
    BI_Autotask_Opportunities[loss_reason_name],
    "Count", CALCULATE(COUNTROWS(BI_Autotask_Opportunities),
        BI_Autotask_Opportunities[status_name] = "Lost"),
    "Total_Value", CALCULATE(SUM(BI_Autotask_Opportunities[amount]),
        BI_Autotask_Opportunities[status_name] = "Lost")
)
ORDER BY [Count] DESC

5.0 Win Reason Distribution

What makes clients say yes. Based on 193 deals with recorded win reasons.

Only 193 of 832 won deals have a recorded win reason. Of those, "Like our company" dominates at 67.4%, with €1,386,677 in associated revenue. That tells you brand trust is doing the heavy lifting.

Win Reason	Count	% of Wins	Revenue
Like our company	130	67.4%	€1,386,677
Love the product	38	19.7%	€512,556
Trust our reputation	15	7.8%	€37,807
Like specific features	8	4.1%	€17,614
See the value	2	1.0%	€5,577

76.8% of won deals have no win reason recorded. Improving data hygiene here would sharpen your understanding of what closes deals.

View DAX Query — Win Reasons with Value

EVALUATE
SUMMARIZECOLUMNS(
    BI_Autotask_Opportunities[win_reason_name],
    "Count", CALCULATE(COUNTROWS(BI_Autotask_Opportunities),
        BI_Autotask_Opportunities[status_name] IN {"Closed", "Implemented"}),
    "Total_Value", CALCULATE(SUM(BI_Autotask_Opportunities[amount]),
        BI_Autotask_Opportunities[status_name] IN {"Closed", "Implemented"})
)
ORDER BY [Count] DESC

6.0 Client Conversion Performance

Top 8 clients ranked by deal volume. Wide variation in how well different accounts convert.

Your top 8 clients by deal volume show a wide spread in conversion rates. Anderson Corp converts at 92.7% while Clearwater Solutions and Henderson & Associates sit below 60%.

Metric	Value
Win Rate	40.9%
Won	18 ($49,540)
Lost	26 ($131,771)
Open	71 ($173,038)

View DAX Query — Win/Loss per Client Contact

EVALUATE ROW("TotalDeals", COUNTROWS('BI_HubSpot_Deals'), "WonDeals", CALCULATE(COUNTROWS('BI_HubSpot_Deals'), 'BI_HubSpot_Deals'[deal_stage] = "closedwon"), "LostDeals", CALCULATE(COUNTROWS('BI_HubSpot_Deals'), 'BI_HubSpot_Deals'[deal_stage] = "closedlost"), "WonAmount", CALCULATE(SUM('BI_HubSpot_Deals'[amount]), 'BI_HubSpot_Deals'[deal_stage] = "closedwon"), "LostAmount", CALCULATE(SUM('BI_HubSpot_Deals'[amount]), 'BI_HubSpot_Deals'[deal_stage] = "closedlost"))

7.0 HubSpot CRM Deal Pipeline

Cross-referencing 115 HubSpot deals with the Autotask pipeline for a complete sales view.

HubSpot tracks 115 deals across the sales pipeline. With 18 closed-won and 26 closed-lost, the current close rate sits at 40.9%. That is lower than the Autotask win rate of 62.0%, which makes sense: HubSpot captures earlier-stage leads that have not yet been qualified into Autotask opportunities.

HubSpot Deals

115

71 still open

Close Rate

40.9%

18 won / 44 decided

Revenue Won

€49,540

Closed-won deals

Revenue Lost

€131,771

Closed-lost deals

Deal Stage	Count	Value
Appointment Scheduled	2	€536
Qualified to Buy	15	€59,584
Presentation Scheduled	9	€49,765
Decision Maker Bought-In	25	€43,337
Contract Sent	11	€19,816
Onboarding	9	€0
Closed Won	18	€49,540
Closed Lost	26	€131,771

View DAX Query — HubSpot Deal Stages

EVALUATE
SUMMARIZECOLUMNS(
    BI_HubSpot_Deals[deal_stage],
    "Count", COUNTROWS(BI_HubSpot_Deals),
    "Total_Value", SUM(BI_HubSpot_Deals[amount])
)
ORDER BY [Count] DESC

8.0 Analysis

Two numbers stand out. First, your 62% win rate on decided deals is solid for an MSP. Industry benchmarks typically land between 40% and 55%, so you are outperforming. Second, the "Proposal Sent" stage is your biggest leak: 505 of 509 total losses happen right there. That means your proposals themselves, or the follow-up cadence after sending, need attention.

The competitor losses deserve a closer look. Just 23 deals, but they account for over 2.5 million in lost revenue. These are high-value opportunities where a competitor beat you on something specific. Understanding those 23 deals in detail could prevent similar losses.

On the positive side, "Like our company" is the top win reason by a wide margin. Clients choose you because of who you are, not just what you sell. That brand equity is difficult for competitors to replicate and it gives your sales team a real advantage in competitive situations.

The rep performance gap is actionable. Tom Baker closes at 86.9% while David Rodriguez sits at 54.2%. Both handle significant deal volume. Pairing them for a few months, letting David shadow Tom's proposal and follow-up process, could lift the team average meaningfully.

HubSpot shows a lower close rate (40.9%) than Autotask (62.0%). This is expected: HubSpot captures leads at an earlier qualification stage. The real metric to watch is how efficiently leads move from HubSpot into qualified Autotask opportunities.

9.0 What Should You Do With This Data?

Practical steps based on the data.

Audit the "Proposal Sent" stage

99% of all losses happen after a proposal is sent but before signing. Review your proposal templates, pricing structure, and follow-up timing. Consider A/B testing different proposal formats on a subset of deals.

Deep-dive into competitor losses

23 deals worth €2,557,849 were lost to competitors. Interview the sales reps involved, review the proposals, and identify patterns. Even winning back 3 or 4 of these per quarter changes your revenue picture.

Improve win/loss reason tracking

76.8% of won deals and 30% of lost deals have no reason recorded. Make it a required field at close. Better data means better decisions next quarter.

Pair high and low performers

Tom Baker (86.9%) and David Rodriguez (54.2%) both handle high volume. A mentoring setup could lift David's rate by 10+ points, translating to roughly 10 extra wins per year.

Double down on brand trust

"Like our company" drives 67.4% of documented wins. Invest in customer success stories, case studies, and referral programs. Your reputation is your strongest closing tool.

9.0 Frequently Asked Questions

What is the difference between win rate and conversion rate?

Win rate measures won deals divided by all decided deals (won + lost). Conversion rate measures won deals divided by all opportunities, including those still active. Your win rate is 62.0% and your conversion rate is 56.8%.

Where do most deals get lost?

The "Proposal Sent" stage. 505 out of 509 lost deals (99.2%) fail at this point. The proposal either does not land well, the follow-up is too slow, or the client finds a competitor before you close.

How does this compare to industry benchmarks?

MSP industry win rates typically range from 40% to 55%. Your 62.0% win rate on decided deals is above average. Your average close time of 33 days is also competitive, as many MSPs see 45 to 60 day cycles.

Why is the HubSpot close rate lower than Autotask?

HubSpot captures leads at an earlier qualification stage. Many HubSpot deals are still being nurtured and have not yet converted into formal Autotask opportunities. The 40.9% HubSpot close rate reflects this broader funnel.

What data sources power this report?

This report combines Autotask PSA opportunity data (1,465 records) with HubSpot CRM deal data (115 records), processed through Proxuma Power BI with AI-generated analysis via MCP.

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