Where your deals are, how much pipeline value is active, and what your close rate tells you about sales performance. Generated by AI via Proxuma Power BI MCP server.
Where your deals are, how much pipeline value is active, and what your close rate tells you about sales performance. 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: MSP operations teams and service delivery managers
How often: As needed for specific analysis or reporting requirements
Where your deals are, how much pipeline value is active, and what your close rate tells you about sales performance. Generated by AI via Proxuma Power BI MCP server.
EVALUATE ROW(
"OpenCount", [Conversion - Open Opportunities],
"OpenTotal", [Pipeline - Total Value],
"OpenWeighted", [Pipeline - Weighted Value],
"AvgSize", [Pipeline - Avg Deal Size],
"AvgAgeDays", AVERAGEX(FILTER('BI_Autotask_Opportunities', 'BI_Autotask_Opportunities'[status_name] = "Active" && NOT(ISBLANK('BI_Autotask_Opportunities'[create_date]))), DATEDIFF('BI_Autotask_Opportunities'[create_date], TODAY(), DAY)),
"OldestDeal", MAXX(FILTER('BI_Autotask_Opportunities', 'BI_Autotask_Opportunities'[status_name] = "Active" && NOT(ISBLANK('BI_Autotask_Opportunities'[create_date]))), DATEDIFF('BI_Autotask_Opportunities'[create_date], TODAY(), DAY)),
"DealsOver90", CALCULATE(COUNTROWS('BI_Autotask_Opportunities'), 'BI_Autotask_Opportunities'[status_name] = "Active", 'BI_Autotask_Opportunities'[create_date] < TODAY() - 90)
)Total deal value per Autotask opportunity stage, ranked by amount. Stage names are in Dutch with English translations.
| Title | Owner | Stage | Amount | Age (days) | Prob |
|---|---|---|---|---|---|
| Update required | Travis Peterson | Voorstel verstuurd | $2,657,650.00 | 140 | 50% |
| Update required | Travis Peterson | Voorstel verstuurd | $219,979.44 | 145 | 50% |
| Performance issue | Michelle Chapman | Voorstel maken | $149,871.91 | 416 | 50% |
| Backup request | Michelle Chapman | Voorstel maken | $127,869.76 | 158 | 50% |
| Hardware issue | Michelle Chapman | Voorstel maken | $114,071.38 | 87 | 50% |
| Backup request | Michelle Chapman | Voorstel maken | $113,799.76 | 83 | 50% |
| Update required | Travis Peterson | Voorstel maken | $96,175.80 | 263 | 50% |
| Network issue | Michelle Chapman | Voorstel verstuurd | $36,692.55 | 111 | 50% |
| Support request | Kristina Brown | Voorstel maken | $30,935.96 | 326 | 50% |
| Software issue | Michelle Chapman | Voorstel verstuurd | $28,568.24 | 200 | 50% |
EVALUATE TOPN(10,
CALCULATETABLE(
SELECTCOLUMNS('BI_Autotask_Opportunities',
"Title", 'BI_Autotask_Opportunities'[title],
"Owner", 'BI_Autotask_Opportunities'[owner_resource_name],
"Stage", 'BI_Autotask_Opportunities'[stage_name],
"Amount", 'BI_Autotask_Opportunities'[amount],
"AgeDays", DATEDIFF('BI_Autotask_Opportunities'[create_date], TODAY(), DAY),
"Probability", 'BI_Autotask_Opportunities'[probability]
),
'BI_Autotask_Opportunities'[status_name] = "Active"
),
[Amount], DESC
)
ORDER BY [Amount] DESCHow all 1,465 opportunities break down by current status, with total deal value and revenue split
| Age Bucket | Deals | Amount | Avg Age |
|---|---|---|---|
| 0–30 days | 0 | $0.00 | — |
| 31–90 days | 19 | $290,268.98 | 86.0 |
| 91–180 days | 45 | $3,134,092.94 | 128.6 |
| 181–365 days | 33 | $261,754.00 | 266.4 |
| 365+ days | 27 | $252,687.33 | 500.8 |
EVALUATE
GROUPBY(
ADDCOLUMNS(
FILTER('BI_Autotask_Opportunities',
'BI_Autotask_Opportunities'[status_name] = "Active"
&& NOT(ISBLANK('BI_Autotask_Opportunities'[create_date]))),
"Age", DATEDIFF('BI_Autotask_Opportunities'[create_date], TODAY(), DAY),
"Bucket",
SWITCH(TRUE(),
DATEDIFF('BI_Autotask_Opportunities'[create_date], TODAY(), DAY) <= 30, "1. 0-30 days",
DATEDIFF('BI_Autotask_Opportunities'[create_date], TODAY(), DAY) <= 90, "2. 31-90 days",
DATEDIFF('BI_Autotask_Opportunities'[create_date], TODAY(), DAY) <= 180, "3. 91-180 days",
DATEDIFF('BI_Autotask_Opportunities'[create_date], TODAY(), DAY) <= 365, "4. 181-365 days",
"5. 365+ days"
)
),
[Bucket],
"Deals", COUNTX(CURRENTGROUP(), 'BI_Autotask_Opportunities'[opportunity_id]),
"Amount", SUMX(CURRENTGROUP(), 'BI_Autotask_Opportunities'[amount]),
"AvgAge", AVERAGEX(CURRENTGROUP(), [Age])
)
ORDER BY [Bucket]The active pipeline holds $3.94M across 124 deals, which represents a healthy funnel for an MSP. The average deal size of $10,215 is consistent with managed services engagements that include both recurring and project-based revenue.
The win rate of 58.6% is solid. That means for roughly every 10 deals that reach a resolution, about 6 close successfully. The lost deals (509) account for $7.06M in total value. That is more than double the value of closed-won deals ($3.44M). The higher dollar value in lost deals suggests that larger opportunities are harder to close, or that pricing is a factor on bigger engagements.
The "Offerte" (Quote) stage holds the most value at $7.16M across 530 deals. This is the stage where deals sit the longest before they either convert or get lost. If there is a bottleneck in your sales process, this is likely it. The "Offerte verstuurd" (Quote Sent) stage has only 46 deals but carries $3.06M in value, meaning the average deal size at that stage is $66,500. These are your high-value prospects that need the most attention.
One area to watch: 16 deals are in "Verlopen" (Expired) status with $37,677 in value. These are opportunities that have gone stale. They should either be closed as lost or re-engaged. Leaving them in the pipeline inflates your active count without contributing to conversion.
The "Getekend" (Signed) stages contain 832 deals across three sub-stages: processed to ticket (606), processed to project (191), and pending processing (35). The 35 deals in "Getekend, te verwerken" represent signed deals that have not yet been converted to tickets or projects. That is a fulfillment gap that should be addressed this week.
5 priorities based on the findings above
These deals have been signed but not yet converted to a ticket or project. That means the client said yes, but nothing is happening on your side. Each day of delay risks the client second-guessing their decision. Get these into your delivery pipeline this week. The total value is $132,532.
These are quotes that have been sent but not yet signed. With an average value of $66,500 per deal, this is where your biggest revenue opportunity sits. Assign follow-up calls for each one. If a quote has been out for more than 14 days without a response, that deal is likely going cold.
Deals in "Verlopen" (Expired) status are dead weight in your pipeline. They create a false sense of pipeline health. Go through each one: if the client is still active, reach out with an updated proposal. If they have moved on, close the deal as lost so your pipeline metrics are accurate.
Lost deals total $7.06M while closed-won deals total $3.44M. That ratio suggests that larger deals are being lost at a disproportionate rate. Pull the top 10 lost deals by value and look for patterns: were they undercut on price, was the sales cycle too long, or did the scope exceed what the client expected?
The 38 deals in "Offerte maken" (Create Quote) are your earliest-stage opportunities. With $762K in potential value and an average probability of 51.8%, these are deals that have not yet received a formal quote. Monitoring this stage weekly tells you whether your top-of-funnel is healthy or drying up.
Opportunity data comes from Autotask PSA. Proxuma Power BI connects to Autotask via its API, pulls all opportunity records including stage, status, amount, monthly cost, and one-time cost. The AI then runs DAX queries against this data to calculate totals, averages, and distributions.
Win rate is calculated as Closed Won deals divided by all resolved deals (Closed Won + Lost). In this dataset: 720 / (720 + 509) = 58.6%. Active and Implemented deals are excluded because they have not reached a final outcome yet.
The stage names reflect the Autotask configuration. Autotask allows custom stage names, and this MSP uses Dutch labels (Offerte = Quote, Getekend = Signed, Verlopen = Expired, Offerte maken = Create Quote, Offerte verstuurd = Quote Sent). English translations are included in the table for clarity.
The "amount" field is the total opportunity value in Autotask. "Monthly cost" is the recurring monthly revenue (MRR) tied to the deal. "One-time cost" covers project fees, setup charges, and hardware. Together they make up the full deal value.
Yes. The DAX queries can be modified to add filters on create date, close date, or owner. Add a FILTER clause on the relevant column. For example, filtering to opportunities created in the last 90 days gives you a view of recent pipeline activity.
Yes. Connect Proxuma Power BI to your Autotask account, 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 data, and produces a report like this in under fifteen minutes.
Connect Proxuma Power BI to your PSA, RMM, and M365 environment, use an MCP-compatible AI to ask questions, and generate custom reports - in minutes, not days.
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