Know how fast money moves - and where time leaks.Cycle time, by stage and by source, lag-corrected.
Velocity & Lag measures the speed of the business: how long deals take by stage and source, where time leaks, and what will actually land once in-flight pipe is corrected for your real cycle. The honest version of the forecast.
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.
Median lead→won
58d
▼ 4d
Enquiry→quote
12d
▼ 2d
On-time conv.
74%
▲ 3pp
Stuck $ at risk
$5.2M
past median
Fastest source
Repeat
38d median
Longest tail
Google
68d median
Service analytics from the team behind $150M+ in revenue influenced
What it answers
The questions about speed and certainty.
Not a single cycle number. Where time leaks, which sources drag, and what is genuinely bankable.
01
How long does money actually take to move?
Median time from enquiry to won, end to end and stage by stage, so the real speed of the business is a number, not a guess.
02
Which sources convert fast, and which drag?
Time-to-won by source, so a channel that quotes big but closes slowly is visible against a fast one.
03
Where in the funnel does time leak?
Time-in-stage at every step, so the stage quietly adding weeks to the cycle is exposed.
04
What is bankable, in-flight, and projected?
A lag-corrected forecast that separates won, near-certain and projected, so the number you plan against is honest.
05
Where is at-risk pipe concentrated?
Open value dwelling past its stage median, by stage and owner, so the deals about to become losses get worked.
06
Is the cycle getting faster or slower?
Cycle time over time, with significance, so a creeping slowdown is caught before it costs a quarter.
Stage velocity
See exactly where time leaks.
A 58-day cycle can hide one stage doing all the damage. Median and tail time at every step shows where deals sit, so you shorten the cycle at its real bottleneck rather than pushing everywhere.
Median and tail - P50, P75 and P90 per stage
The real bottleneck - the step adding the most days
Time-in-stage · P10-P90 days, by step (funnel order)
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
Plan against an honest number.
In-flight deals are right-censored: counting them at face value overstates, ignoring them understates. Lag-correction projects maturing pipe from your own history, so the forecast separates the bankable from the hopeful.
Bankable vs projected - won, near-certain and modelled, split
From your own lag - not a straight-line extrapolation
Coverage vs plan - how much of target is in the pipe
In-flight pipe is lag-corrected from your own cycle, so the $18.2M projection reflects how deals really mature, not a straight line.
Stuck-deal heatmap
Work the pipe before it becomes a loss.
Every loss was once a live deal that sat too long. The stuck heatmap maps open value by stage and dwell, so the pools about to age out are visible and workable while there is still time.
Stage by dwell - at-risk value where it concentrates
In-flight deals have not finished maturing. We project them from your own historical time-to-won distribution, with confidence bands, so the forecast neither overstates open pipe nor undercounts it.
With medians and tails (P75, P90), not averages, so a few stuck whales do not distort the picture of how long a stage really takes.
Yes. Survival curves and time-to-won are shown per source, so a fast channel and a long-tail one are compared honestly rather than blended.
Stage timestamps and close dates from your CRM, joined to finance for the won figures, so every duration is reproducible.
It carries a confidence band and is built from your own lag, separating bankable from projected - a range with a track record, not a single optimistic line.
See the real speed of your pipeline.
Connect your CRM. We measure time at every stage, correct in-flight pipe for your cycle, and hand you an honest forecast.
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
Customer
Value
Churn risk
Signal
Get ahead of it
Atlas Build Co
$142K
High
No job in 9mo, 2 quotes unanswered
Owner call + retention offer this week
Marrickville Group
$98K
High
Spend down 41% QoQ, slower replies
Account review, find the blocker
Coastal Facilities
$76K
Med
Smaller jobs, longer gaps
Check-in + maintenance upsell
Northgate Pty
$64K
Med
Single job, no repeat in 6mo
Nurture sequence + case study
Vertex Services
$51K
Low
Steady, on cycle
Monitor
$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
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
RepeatReferralWebsiteGoogleMetaPartnerWin rate
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
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
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
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)
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
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.