NewWeather Demand Modelling is live. Forecast demand before it arrivesWeather Demand Modelling is live

How is the team converting what marketing feeds it?Performance by rep, team and region - on closed revenue.

People & Performance is the cockpit on your sales team: attainment, activity, pipeline ownership, win rate and ramp, every number on closed revenue and every rep comparable. Coaching, routing and hiring stop being a gut call.

Book a consult
People & PerformanceDemonstrative data
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.
Network attainment
87%
▲ 4pp
Median cycle
36d
▼ 6d
Activity / wk
73
▲ 11
$ pipe / rep
$1.84M
▲ 8%
Top-quartile share
41%
concentration
Active reps
24
6 teams
Service analytics from the team behind $150M+ in revenue influenced
What it answers

The questions every head of sales asks.

Not activity dashboards. Who performs, who converts where, and where a point of coaching is worth the most revenue.

01
Which reps actually perform?
Ranked on closed revenue and win rate, not calls logged, so effort and outcome are told apart.
02
Who converts better in which channel?
Win rate by rep and lead source, so you route referral leads and paid leads to the people who close them.
03
What is each rep's quote-to-win rate?
From proposal to signed, by rep, so a strong talker with a weak close rate is visible.
04
Who is on track to hit quota?
Attainment against target with the in-flight pipe weighted, so the quarter is a forecast, not a hope.
05
Where is a point of coaching worth the most?
The stage and rep combination where a small lift moves the most revenue, costed for you.
06
How fast do new reps reach productivity?
Ramp curves for new hires against your tenured baseline, so hiring and onboarding pay off on a known timeline.
Rep × source crossover

Match your closers to the leads they win.

The most actionable view in the section. Several reps convert at twice their team median on one channel and below baseline on another. Route each source to who closes it and the same pipeline returns more, with nobody working harder.

  • Routing as revenue - send each source to who actually wins it
  • Above and below the line - green beats team median, red trails it
  • Quantified upside - the redistribution dollars, estimated
See your crossover grid
People & Performance · rep × sourceLive
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 & coverage

See how hard - and how well - each rep works the pipe.

Effort is not outcome. Plotting every rep's weekly activity, sized by attainment, shows the real spread and breaks the myth that more dials always means more deals - some of your best closers run light and convert anyway.

  • The real spread - P10 to P90 activity across the team
  • Effort vs outcome - dot size is attainment, not activity
  • Efficient outliers - light-activity, high-conversion reps surfaced
See your activity spread
People & Performance · activityLive
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).
Ramp & new-hire watchlist

Know if a new hire is on track - by month two.

A rep who is behind at month four is an expensive surprise. The ramp curves track each new hire against your tenured baseline, and the watchlist puts tenure, pipe build and activity in one place, so onboarding pays off on a known timeline or gets fixed early.

  • Against your baseline - measured on your own tenured reps
  • Early warning - a lagging hire flagged at month two
  • Build, not just output - 13-week pipe trajectory per rep
See your ramp watchlist
People & Performance · ramp watchlistLive
Ramp to productivity · new hires vs mature curve
M0 → M12
- - mature baseline · on-curve hire · behind, needs intervention
RepTeamTenurePipeAct/wk13w pipe
L. BrownMetro West4mo$1.2M125
V. BoseMetro North6mo$1.4M110
R. KhouriMetro West8mo$2.0M101
K. RaoEastern12mo$2.6M90
A. KhanNorthern14mo$3.4M82
P. SantosNorthern16mo$2.8M73
T. SinghMetro North18mo$3.7M99
H. KimSouthern18mo$1.8M44
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 performance is honest.

When every rep is measured on closed revenue, coaching lands where it pays and routing follows the close rate. 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.

No. It ranks on closed revenue, win rate and quote-to-win, not calls or emails logged. Activity is an input; this measures outcomes.
Every metric is shown against a like-for-like peer set and the relevant baseline, with sample size built in, so a rep in a thin territory is not punished for volume.
Yes. The same view rolls up to team, branch and region, and drills back down to the rep and the deal.
Your CRM for deals, stages and owners, joined to your quoting and finance systems so closed and contracted revenue is grounded in delivery.
It replaces the manual spreadsheet on top of them. The numbers reconcile to your CRM and finance systems, with every figure traceable to source.

See who really drives revenue, in your first weeks.

Connect your CRM and finance systems. We map your team, reconcile performance to closed revenue, and hand you the coaching and routing moves.

01

Connect your stack

CRM and finance. No data team required.

02

Map your team

Reps, teams, regions and quotas.

03

Reconcile performance

Every rep on closed revenue.

04

See the gaps

Where coaching and routing pay off.

05

Get the moves

Each action priced in revenue.

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.