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Know what your pipeline is really worth.Every dollar of spend, traced to closed revenue.

Pipeline Money is the single view of where revenue is won, contracted and in-flight. Spend traced through every stage to the deals it actually closes, lag-corrected for your real sales cycle, and reconcilable to the dollar. No vanity pipeline, no double-counting. The number your board can trust.

Book a consult
Pipeline MoneyDemonstrative data
Click139,760
Enquiry3,898
Qualified2,350
Quote806
Negotiation544
Won465
Spend
$452K
▲ 4.1%
Enquiries
3,898
▲ 9.2%
Quotes
806
▼ 1.4%
Negotiations
544
▲ 6.0%
Closed
$12.4M
▲ 18%
Blended ROAS
27.4×
▲ 0.9×
Pipeline analytics from the team behind $150M+ in revenue influenced
PanasonicRainCoCheapest LiquorKing CoolingAuto ComfortiHeat & CoolAACAEInsider Experience SportsInterosPeter JacksonLa TrobeToy WorldForesightOncoreMindshopSurface SpectrumNAWTeafyEZI TagPanasonicRainCoCheapest LiquorKing CoolingAuto ComfortiHeat & CoolAACAEInsider Experience SportsInterosPeter JacksonLa TrobeToy WorldForesightOncoreMindshopSurface SpectrumNAWTeafyEZI Tag
Purest SolutionsCuratedVoir VodkaSwing & ServeNewLeafNavigataFirst EnergyHaldatecSirius GreenElite ElectricalMobile SkipsBrowedAsenoMGIDCRebateM8TMJ TutoringAcademic TutorsUCSPurest SolutionsCuratedVoir VodkaSwing & ServeNewLeafNavigataFirst EnergyHaldatecSirius GreenElite ElectricalMobile SkipsBrowedAsenoMGIDCRebateM8TMJ TutoringAcademic TutorsUCS
What it answers

The questions your leadership actually asks.

Not "how many leads." The board-level questions about where revenue truly is, what is going to close, and which dollars created it.

01
What is our pipeline genuinely worth right now?
Every open deal weighted by its stage probability and corrected for reporting lag, so in-flight revenue is neither overstated nor undercounted mid-cycle.
02
How much of the number is closed, contracted, or still in-flight?
One reconciled split of the quarter: realised, contracted and projected revenue, each tied out to its source records.
03
Where, in dollars, is revenue leaking?
The largest leak ranked by value at stake, not just conversion rate, so you fix the stage that costs the most, not the one that looks worst.
04
What will actually settle in the next 90 days?
A settlement-propensity forecast with a confidence band, built from your own historical lag distribution, not a straight-line extrapolation.
05
Which marketing dollars created the pipeline that closes?
Spend attributed to realised revenue, traced to source and campaign, separating the channels that fill the funnel from the ones that fill the bank.
06
Where is revenue stuck, and which deals are overdue?
Open value flagged where deals sit beyond their normal time-in-stage, so your team works the pipe that is quietly ageing out.
Stage funnel & leakage

See exactly where revenue leaks - in dollars.

A conversion rate tells you a stage is weak. It does not tell you what it costs. The leakage waterfall prices every drop-off in pipeline value lost, then ranks them, so the stage you fix first is the one bleeding the most money.

  • Ranked by value at stake - the worst leak in dollars, not just the worst rate.
  • Significance on every comparison - real movement is flagged; noise is not.
  • Time-in-stage & loss reasons - why deals die at each stage, and how long they sat.
Find your biggest leak
Pipeline Money · by stageLive
Stage funnel · leakage waterfall
Enquiry
3,898 · $48.7M
entered
Qualified
2,350 · $34.1M
60.3%−$6.1M
Quote
806 · $24.9M
34.3%−$9.2M
Negotiation
544 · $18.2M
67.5%−$3.4M
Won
465 · $12.4M
85.5%−$1.6M
Largest leak: Qualified → Quote. $9.2M of qualified pipeline never reaches a quote (34.3% conversion vs 41% prior, significant).
Cohort quality

Know which enquiries actually become revenue.

Two months can bring the same number of enquiries and a completely different amount of money. The cohort view tracks each month's enquiries through to won revenue over time, so you can see quality drift before it shows up in the quarter.

  • Lag-corrected maturity - young cohorts are projected from your real cycle, not written off.
  • Source-quality drift - spot a channel whose leads stop converting, early.
  • Like-for-like - every cohort on the same scale, so comparison is fair.
See your cohort quality
Pipeline Money · by cohortLive
Enquiry cohort · % reached won, by weeks since
Cohort
W0
W2
W4
W6
W8
W10
W12
Jun '26
0.4
1.1
2.0
·
·
·
·
May '26
0.5
1.4
2.8
3.9
4.6
·
·
Apr '26
0.6
1.6
3.0
4.4
5.5
6.1
·
Mar '26
0.5
1.5
3.1
4.7
5.9
6.7
7.0
Feb '26
0.7
1.8
3.4
5.0
6.2
6.9
7.3
Jan '26
0.6
1.6
3.2
4.8
6.0
6.8
7.1
% of enquiries won still maturing (lag-corrected on hover)
Forecast & in-flight

Know what is going to close - with confidence.

A settlement-propensity forecast built from your own lag distribution, not a trend line. The fan shows the range; the intelligence layer reads it for you: what to watch, what it means, and the hypothesis behind the number.

  • Confidence bands - 50% and 90% intervals, so a forecast is a range, not false precision.
  • Pipe coverage vs plan - how much of the target is already in the pipe.
  • Backtested - the model is scored against its own last twelve forecasts.
Forecast your pipeline
Pipeline Money · forecastLive
Forecast intelligence90% confidence

Watch90-day settlement forecast totals $18.2M (90% CI $15.1M–$21.6M). Bottom-up tracks 4.2% below the P50 in early weeks, consistent with current sales-cycle lag.

HypothesisA seasonal Q3 enquiry lift (+12%) offsets the quote-stage slowdown; pipe coverage holds at 1.8× the quarter's plan.

Cumulative settled $ · next 90 days
+30d+60d+90d
Where the numbers come from

Built on your systems, reconciled to your records.

Pipeline Money is not a parallel set of figures. It joins the systems you already run into one number that ties out, then keeps it current.

Your CRM

Every deal, stage, owner and close date. We map your real pipeline stages with you, so the funnel matches how your business actually sells.

HubSpotSalesforcePipedrive

Your marketing channels

Spend, clicks and campaigns from every paid source, joined to the deals they created with server-side tracking, lag-corrected to your sales cycle.

GoogleMetaLinkedInMicrosoft

Your operations software

Quoting, job management and finance, so contracted and settled revenue is grounded in delivery, not just CRM optimism.

Job softwareQuotingXero / MYOBCustom
Proof

What operators get when the pipeline is honest.

When every dollar of spend is tied to the revenue it closes, budget moves to what pays back and the pipeline stops lying. A sample of the outcomes.

Field services
30:1return
Australian Air Conditioning & Electrical
Heating & cooling
$3M in closed revenue from $100K of spend - 2,600 qualified enquiries traced to the jobs they became over twelve months.
Read case study
Field services
$5Mnew revenue
I Heat & Cool
Heating & cooling
A full year of new revenue with cost-per-deal cut from $90 to $41.95 once spend was judged on closed jobs, not leads.
Read case study
Field services
$840Kpipeline
King Cooling
Heating & cooling
1,500 enquiries at a $27 cost per enquiry, with 28% converting to booked jobs - visible, stage by stage, in one view.
Read case study
Questions

The things buyers ask.

Your CRM sums open deals at face value. Pipeline Money weights each by its stage probability, corrects for reporting lag, and reconciles closed and contracted revenue against your operations and finance systems - so the number ties out instead of flattering the forecast.
That is exactly what lag-correction is for. In-flight deals are right-censored, so we project maturing cohorts from your own historical lag distribution, with confidence bands, instead of letting you undercount mid-cycle.
No. We map your real stages with you in a short onboarding, so the flow and the leakage waterfall match how you actually sell rather than a generic three-stage template.
The forecast carries a confidence band and is backtested against its own last twelve forecasts, with the reliability shown. You plan against a range and its track record, not a single optimistic line.
It syncs continuously, and every figure is reproducible to its source: the query, the commit and the data snapshot that produced it. A dedicated database per customer, SOC 2 certified, hosted in Australia.
Read access to your CRM and ad platforms, and a short session to map your stages. No data team and no spreadsheets - we handle the joins and the reconciliation.

See your real pipeline in your first weeks.

Connect your CRM, channels and operations software. We map your funnel, reconcile every stage, and hand you a pipeline number you can take to the board.

01

Connect your stack

CRM, ad platforms and ops software. No data team required.

02

Map your funnel

Your real stages, mapped with us in a short onboarding.

03

Reconcile the pipeline

Closed, contracted and in-flight, tied out to source.

04

See where it leaks

Every stage priced in the revenue at stake.

05

Forecast with confidence

What will settle next quarter, with a confidence band.

Book a consult Talk to an analyst
BlufireLIVE DEMO
Diagnostics
Demonstrative data. A sample of the top-level views - the full drill-downs live in the product.
Pipeline MoneyDemonstrative data · click between views
Pipeline Money · spend traced to closed revenue
Click139,760
Enquiry3,898
Qualified2,350
Quote806
Negotiation544
Won465
Stage funnel · leakage waterfall
Enquiry
3,898 · $48.7M
entered
Qualified
2,350 · $34.1M
60.3%−$6.1M
Quote
806 · $24.9M
34.3%−$9.2M
Negotiation
544 · $18.2M
67.5%−$3.4M
Won
465 · $12.4M
85.5%−$1.6M
Largest leak: Qualified → Quote. $9.2M of qualified pipeline never reaches a quote (34.3% conversion vs 41% prior, significant).
Enquiry cohort · % reached won, by weeks since
Cohort
W0
W2
W4
W6
W8
W10
W12
Jun '26
0.4
1.1
2.0
·
·
·
·
May '26
0.5
1.4
2.8
3.9
4.6
·
·
Apr '26
0.6
1.6
3.0
4.4
5.5
6.1
·
Mar '26
0.5
1.5
3.1
4.7
5.9
6.7
7.0
Feb '26
0.7
1.8
3.4
5.0
6.2
6.9
7.3
Jan '26
0.6
1.6
3.2
4.8
6.0
6.8
7.1
% of enquiries won  still maturing (lag-corrected on hover)
Customers · churn & expansion risk
Customers by stage · last 13 weeks, churn & expansion risk scored
EnquiryQualifiedQuoteNegotiationWon
Churn-risk model · at-risk customers, scored
CustomerValueChurn riskSignalGet ahead of it
Atlas Build Co$142KHighNo job in 9mo, 2 quotes unansweredOwner call + retention offer this week
Marrickville Group$98KHighSpend down 41% QoQ, slower repliesAccount review, find the blocker
Coastal Facilities$76KMedSmaller jobs, longer gapsCheck-in + maintenance upsell
Northgate Pty$64KMedSingle job, no repeat in 6moNurture sequence + case study
Vertex Services$51KLowSteady, on cycleMonitor
$1.9M of revenue sits in 21 accounts scored high or medium churn risk. Each carries the signal that flagged it and the move to get ahead of it - the model drives the save, not just the dashboard.
Retention · % of customers and revenue kept over time
0%50%100%Logo retentionRevenue retentionDAYS SINCE ENQUIRY (still open)
You keep 76% of customers and 84% of their revenue at 12 months. The gap between the lines is where small accounts churn but big ones stay - and where a retention play pays back fastest.
Channels · where the work comes from, and which we win
Enquiry share by source · blended win-rate overlay
Repeat Referral Website Google Meta PartnerWin rate
0%50%100%26%32%38%w-12w-9w-6w-3w-0
Stacked share is where enquiries come from; the white line is blended win rate (right axis). Repeat +4pp and Referral +2pp over 13 weeks.
Win rate by source · enquiry to won, last 90 days
Repeat
46% win
312 enq · avg $54k+3pp
Referral
38% win
264 enq · avg $48k+1pp
Partner
30% win
48 enq · avg $65k+4pp
Meta
30% win
120 enq · avg $32k+0pp
Website
26% win
184 enq · avg $42k-1pp
Google
21% win
64 enq · avg $24k-1pp
Repeat and Referral close at nearly double the rate of paid search - but paid brings volume Repeat never will.
Enq→Qual
Qual→Quote
Quote→Neg
Neg→Won
Repeat
92%
88%
78%
72%
Referral
86%
82%
70%
65%
Meta
82%
76%
64%
55%
Website
78%
73%
58%
48%
Partner
74%
68%
52%
43%
Google
68%
60%
51%
40%
Each row is a source, each column a pipeline transition. Repeat stays tight through every stage; paid sources leak hardest at Negotiation → Won, the price-pressure stage.
People & Performance · rep, team and region
13-week attainment ranking · teams
#1#2#3#4#5#6Metro West98%Metro North94%Eastern91%Northern88%Southern84%Regional79%w1w4w7w10w13
Each line is a team; y-axis is rank (1 = top). Crossings reveal real shifts. Southern slid from #2 to #5 over the quarter.
Repeat
Google
Meta
Referral
Outbound
S. Tran
-10
+22
+118
+5
-20
R. Okafor
+30
-15
+12
+44
-30
J. Mehta
+15
+40
-25
+30
+10
L. Cheng
-20
+33
+28
-10
+25
D. Ross
+45
-18
+9
+20
-24
A. Pulu
+12
+25
-30
+40
+15
N. Haddad
-40
+18
+35
-12
+28
M. Anderson
+20
-22
+8
+15
-54
Cell = a rep's conversion on that source vs their team median. S. Tran converts +118% on Meta; M. Anderson is -54% on Outbound. A routing signal, surfaced for your judgement.
Activity per rep · weighted touches / week
median 73/wk30507090110ACTIVITIES / WEEK · dot size = attainment
Each dot is a rep; size is attainment. Spread runs 45 to 112 a week, but activity and conversion correlate only 0.42 - three light-activity reps still close above median (large dots left of the line).
Won / Lost · why deals die
Price
Timing
Competitor
Scope / fit
No budget
Stage $
Enquiry
$0.2M
2%
$0.9M
7%
$0.1M
1%
$0.2M
2%
$0.7M
6%
$2.1M
Qualified
$0.4M
3%
$0.8M
7%
$0.4M
3%
$0.3M
2%
$0.5M
4%
$2.4M
Quote
$1.1M
9%
$0.6M
5%
$0.9M
7%
$0.5M
4%
$0.3M
2%
$3.4M
Negotiation
$2.3M
19%
$0.5M
4%
$1.1M
9%
$0.4M
3%
$0.1M
1%
$4.4M
Reason $
$4.0M
$2.8M
$2.5M
$1.4M
$1.6M
$12.3M
Darker = more revenue lost there. Price dominates and concentrates late, at Negotiation ($2.3M); Timing losses cluster early. Click any cell in-product for the lost-deal cohort.
Reason trend · $M lost per week, last 12 weeks
Price+74%
$5.4M last wkP50 $4.3M
Timing-33%
$2.4M last wkP50 $3.0M
Competitor+71%
$2.4M last wkP50 $2.1M
Scope / fit+25%
$1.5M last wkP50 $1.4M
No budget-44%
$1.0M last wkP50 $1.3M
Unresponsive-44%
$0.5M last wkP50 $0.6M
Price is accelerating (+74%) while Timing and No budget decay - the loss mix is shifting toward a fixable reason.
Negotiation → Won leak · sub-reasons
Lower bidder won
38%
of stage loss
Margin-floor breach
24%
of stage loss
Spec / scope change
18%
of stage loss
Slow response
12%
of stage loss
Other
8%
of stage loss
41% of proposals at negotiation never close. Lower-bidder wins (38%) and margin-floor breaches (24%) lead - both are recoverable with the right pricing move, median dwell 42 days before lost.
Velocity & Lag · how fast money moves
Survival curves · enquiry to won, by source
0%50%100%RepeatReferralWebsiteGoogleDAYS SINCE ENQUIRY (still open)
Each line is the share of enquiries still open over time. Repeat converts fast - half are won by day 30; Google carries a long tail.
Time-in-stage · P10-P90 days, by step (funnel order)
0d10d20d30d40d50dEnquiryQualifiedQuoteNegotiation
Box = P25-P75, the line is the median, whiskers are P10-P90. Quote is the slowest and most variable stage - median 18 days, with a P90 tail stretching to 44.
Lag-corrected forecast · next 90 days
Bankable
$8.1M
won + near-certain
In-flight
$15.0M
open, weighted
Projected
$18.2M
90% CI $15.1-21.6M
Coverage
1.8×
vs plan
In-flight pipe is lag-corrected from your own cycle, so the $18.2M projection reflects how deals really mature, not a straight line.
Geography · zone by zone
Pipeline by delivery zone · $ won, sized by colour
Metro North
$4.8M
42% win
Metro West
$3.9M
38% win
Inner East
$2.7M
36% win
Northern
$2.1M
34% win
Southern
$1.6M
30% win
Western
$1.4M
28% win
Regional A
$1.1M
26% win
Regional B
$0.8M
24% win
Coastal
$0.6M
22% win
Metro North and Metro West are 38% of won work this quarter. Coastal and Regional B see thin flow and lower win rates.
Top zones · won $, enquiries, win rate
Metro North
$4.8M
132 enq · 42% win
Metro West
$3.9M
118 enq · 38% win
Inner East
$2.7M
84 enq · 36% win
Northern
$2.1M
72 enq · 34% win
Southern
$1.6M
58 enq · 30% win
Coastal
$0.6M
26 enq · 22% win
Bars are won revenue; the north carries the quarter. Coastal brings enquiries but converts at half the rate of Metro North.
Win rate · source × zone
M.North
M.West
East
North
South
Repeat
46%
42%
40%
34%
30%
Referral
38%
40%
36%
30%
28%
Website
26%
24%
30%
28%
22%
Google
21%
20%
24%
26%
20%
Meta
30%
28%
26%
22%
24%
Referral wins hardest in Metro West; Repeat dominates the north. Route effort to the source that wins each zone.
Pipeline Economics · CAC, payback, LTV:CAC
Cost per enquiry · as it escalates through the funnel
Per enquiry
$116
raw acquisition
Per qualified
$198
after qualification
Per quote
$305
after quoting effort
Per won (CAC)
$584
fully loaded
Acquisition looks cheap at $116 an enquiry; loaded through to a won deal the true CAC is $584. The gap is where efficiency is won or lost.
Pipe coverage · region × quarter (× plan)
Q1
Q2
Q3
This Q
Metro
1.4×
1.6×
1.7×
1.9×
Northern
1.2×
1.3×
1.5×
1.6×
Southern
1.0×
1.1×
1.2×
1.4×
Regional
0.8×
0.9×
1.0×
1.1×
Metro is well covered at 1.9× plan; Regional trails at 1.1× - where the next bit of pipeline-building should aim.
Lifetime value vs loaded CAC · by source
RepeatReferralPartnerMetaWebsiteGoogle$0k$20k$40k$60k$0$60$120$180LOADED CAC · up-left is best
Up and to the left is best - high lifetime value at low cost. Repeat sits top-left ($54k LTV, $66 CAC, 8.2:1); Google is bottom-right, barely clearing its loaded cost at 1.7:1.