How 1,465 opportunities worth $14.97M distribute across 9 deal stages, and what that tells you about pipeline health. Generated by AI via Proxuma Power BI MCP server.
How 1,465 opportunities worth $14.97M distribute across 9 deal stages, and what that tells you about pipeline health. Generated by AI via Proxuma Power BI MCP server.
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
How 1,465 opportunities worth $14.97M distribute across 9 deal stages, and what that tells you about pipeline health. Generated by AI via Proxuma Power BI MCP server.
EVALUATE
ROW(
"TotalPipeline", SUM(BI_Autotask_Opportunities[amount]),
"TotalDeals", COUNT(BI_Autotask_Opportunities[opportunity_id]),
"ActivePipeline", CALCULATE(
SUM(BI_Autotask_Opportunities[amount]),
BI_Autotask_Opportunities[status_name] = "Active"),
"ActiveDeals", CALCULATE(
COUNT(BI_Autotask_Opportunities[opportunity_id]),
BI_Autotask_Opportunities[status_name] = "Active"),
"WonDeals", CALCULATE(
COUNT(BI_Autotask_Opportunities[opportunity_id]),
BI_Autotask_Opportunities[status_name] = "Closed (Won)"),
"LostDeals", CALCULATE(
COUNT(BI_Autotask_Opportunities[opportunity_id]),
BI_Autotask_Opportunities[status_name] = "Lost"),
"AvgDealSize", AVERAGE(BI_Autotask_Opportunities[amount])
)Total deal amount per stage, ordered by value. The "Quote" stage alone holds 47.8% of all pipeline value.
EVALUATE SUMMARIZECOLUMNS('BI_HubSpot_Deals'[deal_stage], "DealCount", COUNTROWS('BI_HubSpot_Deals'), "Amount", SUM('BI_HubSpot_Deals'[amount]))Every stage with deal count, total amount, monthly recurring revenue, one-time revenue, and average close probability
| Stage | Translation | Deals | Amount | MRR | One-Time | Avg Prob. |
|---|---|---|---|---|---|---|
| Offerte | Quote | 530 | $7,157,995 | $318,688 | $2,141,668 | 46.0% |
| Offerte verstuurd | Quote Sent | 46 | $3,059,497 | $103,587 | $126,416 | 50.7% |
| Getekend, verwerkt naar project | Signed → Project | 191 | $1,970,631 | $89,759 | $751,569 | 48.8% |
| Getekend, verwerkt naar ticket | Signed → Ticket | 606 | $1,838,843 | $14,656 | $1,625,211 | 46.1% |
| Offerte maken | Creating Quote | 38 | $762,183 | $30,578 | $331,594 | 51.8% |
| Getekend, te verwerken | Signed, To Process | 35 | $132,532 | $14,321 | $49,434 | 47.9% |
| Verlopen | Expired | 16 | $37,677 | $16,140 | $21,537 | 43.8% |
| Offerte gelezen | Quote Read | 2 | $4,838 | $768 | $4,070 | 25.0% |
| CSAL | CSAL | 1 | $1,200 | $0 | $1,200 | 0.0% |
EVALUATE
SUMMARIZE(
BI_Autotask_Opportunities,
BI_Autotask_Opportunities[stage_name],
"Deals", COUNT(BI_Autotask_Opportunities[opportunity_id]),
"TotalAmount", SUM(BI_Autotask_Opportunities[amount]),
"MonthlyRevenue", SUM(BI_Autotask_Opportunities[monthly_cost]),
"OnetimeRevenue", SUM(BI_Autotask_Opportunities[onetime_cost]),
"AvgProbability", AVERAGE(BI_Autotask_Opportunities[probability])
)
ORDER BY [TotalAmount] DESCHow deals distribute across Active, Won, Lost, and Implemented. The win rate of 58.6% means more than half of resolved deals close successfully.
| Status | Deals | Amount | Share of Pipeline |
|---|---|---|---|
| Closed (Won) | 720 | $3,443,385 | |
| Lost | 509 | $7,059,325 | |
| Active | 124 | $3,938,803 | |
| Implemented | 112 | $523,880 |
EVALUATE
SUMMARIZE(
BI_Autotask_Opportunities,
BI_Autotask_Opportunities[status_name],
"Deals", COUNT(BI_Autotask_Opportunities[opportunity_id]),
"TotalAmount", SUM(BI_Autotask_Opportunities[amount]),
"AvgProbability", AVERAGE(BI_Autotask_Opportunities[probability])
)
ORDER BY [Deals] DESCHow each stage splits between monthly recurring revenue and one-time project revenue. Stages dominated by one-time revenue carry more volatility.
EVALUATE
SUMMARIZE(
BI_Autotask_Opportunities,
BI_Autotask_Opportunities[stage_name],
"MonthlyRevenue", SUM(BI_Autotask_Opportunities[monthly_cost]),
"OnetimeRevenue", SUM(BI_Autotask_Opportunities[onetime_cost])
)
ORDER BY SUM(BI_Autotask_Opportunities[amount]) DESCThe pipeline is heavily front-loaded. 530 deals worth $7.16M sit in the "Offerte" (Quote) stage, which accounts for 47.8% of total pipeline value. That is the single largest concentration of revenue in any stage, and it tells you something specific: deals are being created and quoted, but many of them are not moving forward. Whether they stall because of pricing, timing, or follow-up gaps, this is where sales effort should focus.
The "Offerte verstuurd" (Quote Sent) stage holds only 46 deals but $3.06M in value. That means the average deal size here is $66,510, roughly six times the overall average of $10,215. These are your large, high-value deals that have been sent to the prospect but have not yet closed. Each one of these deserves individual attention.
Lost deals represent the largest dollar amount at $7.06M across 509 opportunities. That number is more than double the amount that was actually won ($3.44M). On a deal-count basis, you win more than you lose (720 won vs 509 lost, a 58.6% win rate). But on a dollar basis, the deals you lose are worth more than the ones you win. This suggests your larger opportunities have a lower close rate than smaller ones.
The "Signed to Ticket" stage has the highest deal count at 606 deals, but only $1.84M in total value. The average deal here is around $3,034, which makes sense: these are smaller, transactional deals that convert to service tickets once signed. They move fast and close at volume, but they do not drive large revenue jumps.
On the recurring revenue side, the "Quote" stage holds $318K in monthly recurring revenue. The "Quote Sent" stage adds another $104K. Combined, that is over $420K/month in MRR sitting in pre-close stages. Converting even 30% of that would add $126K to monthly revenue.
5 priorities based on the findings above
$7.16M in pipeline value sitting in "Offerte" means deals are being created but not sent or followed up on. Filter by age and sort by value. Any quote older than 30 days without customer engagement should be flagged for follow-up or marked as lost. Keeping stale quotes inflates your pipeline and hides the real number.
With an average deal size of $66,510, these 46 opportunities are your highest-leverage follow-ups. Each one that closes moves the needle. Build a weekly review cadence for this stage specifically, and make sure every deal has a clear next step and owner.
509 lost deals totaling $7.06M versus 720 won deals at $3.44M means you close more deals by count, but lose the bigger ones. Pull the lost deals over $50K and look for patterns: was it pricing, competitor, timing, or scope? Fixing the close rate on large deals has a disproportionate impact on revenue.
Expired deals ($37.7K) and deals waiting to be processed ($132.5K) are operational friction. The expired ones should be closed or re-engaged. The "Signed, To Process" deals are already won revenue that has not been implemented. Speed up the handoff from sales to delivery for these 35 deals.
$420K in monthly recurring revenue sits in the Quote and Quote Sent stages combined. If your sales team can convert 30% of this MRR, that adds $126K/month to the top line. Make sure proposals with recurring components are prioritized over one-time project work when allocating follow-up effort.
All pipeline data comes from the BI_Autotask_Opportunities table in Proxuma Power BI. This table syncs with your Autotask PSA and contains every opportunity with its stage, status, amount, monthly cost, one-time cost, and probability fields. The AI queries this table using DAX and groups the results by stage and status.
Autotask stores opportunity stages in the language configured by the MSP. In this dataset, stages are in Dutch: "Offerte" means Quote, "Offerte verstuurd" means Quote Sent, "Offerte maken" means Creating Quote, "Getekend" means Signed, "Verlopen" means Expired, and "Offerte gelezen" means Quote Read. The report includes English translations in every table.
Win rate is calculated as Won deals divided by (Won + Lost) deals. Active and Implemented deals are excluded from the calculation because they have not reached a final outcome. In this dataset: 720 won / (720 won + 509 lost) = 58.6%.
The average lost deal is worth roughly $13,870 while the average won deal is $4,782. This means larger deals are harder to close. Common reasons include: longer sales cycles that give prospects more time to reconsider, more stakeholders involved in the decision, and stronger competition on bigger contracts. Tracking lost deal reasons in your PSA would give you more specific answers.
Yes. Connect Proxuma Power BI to your Autotask PSA, add an AI tool (Claude, ChatGPT, or Copilot) via MCP, and ask the same question. The AI writes the DAX queries, runs them against your real opportunity data, and produces a report like this in under fifteen minutes.
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