92%
Know why deals die - where, when, and if it is getting worse.Every loss priced, ranked, and traced to its stage.
Won / Lost turns the softest data in your business into a number. Every lost deal tagged by reason, priced in revenue, and mapped to the stage and source it came from - so the reasons you lose become a ranked, fixable list instead of a pile of anecdotes.
Won / LostDemonstrative data
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.
Win rate 90d
34%
▲ 2pp
Loss $ 90d
$14.2M
1,420 deals
Top reason
Price
28% of $
Worst stage
Negotiation
41% drop
Cancellations
8%
$7.2M post-win
Competitor
22%
4 named rivals
Service analytics from the team behind $150M+ in revenue influenced
What it answers
The questions you ask after every lost deal.
Not a win-rate number on a slide. Why deals die, which losses you can actually fix, and where in the funnel they slip.
01
Why are we really losing deals?
Every lost deal tagged by reason and priced in revenue, so the loss that costs the most is ranked first, not the one shouted loudest.
02
What is our real win rate?
Win rate on deals that reached a decision, by segment, channel and rep, with the stalled-forever deals separated out.
03
Which losses are actually fixable?
Price, timing and fit separated, so you spend effort on the reasons a change in approach can win back.
04
Where in the funnel do we lose?
Loss reason mapped to the stage it struck, so you fix the leak at its source rather than at the end.
05
Who do we lose to, and how often do we win?
Competitive win rate by rival, so you know where you genuinely compete and where you are being used as a quote.
06
Is our win rate holding, by segment?
Win rate over time across segments, with significance, so a quiet decline in one is caught early.
Reason trends
Catch a shifting loss mix before the quarter does.
A flat win rate can hide a loss mix tilting hard toward one reason. Twelve weeks per reason shows which are accelerating and which are decaying, so you act on a trend in week two rather than explain it in month three.
- Per reason - each loss reason on its own twelve-week line
- Direction, flagged - accelerating losses called in red
- Tied to the heatmap - every reason drills to stage and deal
Won / Lost · reason trendLive
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.
The closing leak
Fix the stage where the most revenue dies.
Knowing price is your top reason is half the story; knowing it strikes at negotiation tells you what to change. Breaking the worst stage into sub-reasons separates the losses a pricing or response change can win back from the ones you were never going to take.
- Sub-reason detail - lower-bidder vs margin vs scope, split out
- Recoverable vs not - the winnable losses, isolated
- Dwell before loss - how long deals sat before dying
Won / Lost · closing leakLive
Negotiation → Won leak · sub-reasons
Lower bidder wonof stage loss
38%
Margin-floor breachof stage loss
24%
Spec / scope changeof stage loss
18%
Slow responseof stage loss
12%
Otherof stage loss
8%
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.
Cancellation cohort
See if post-win cancellations are systemic.
A win is not revenue until it is delivered. The cohort grid tracks deals that cancelled after they were won, by when they signed and how long they lasted, so a one-off becomes visible as a pattern - and you can tell a bad quarter from a broken process.
- By cohort and age - when they signed vs when they cancelled
- Systemic vs noise - a spike in one bucket is a pattern
- Exposure, priced - the revenue at risk, not a count
Won / Lost · cancellation cohortLive
0-30d
31-60d
61-90d
90d+
Jan '26
$0.4M
$0.9M
$0.6M
$0.3M
Feb '26
$0.5M
$1.1M
$0.7M
$0.4M
Mar '26
$0.6M
$1.4M
$0.9M
$0.5M
Apr '26
$0.7M
$1.8M
$1.0M
·
May '26
$0.8M
$1.2M
·
·
Jun '26
$0.5M
·
·
·
Post-win cancellations by cohort and age. Recent cohorts spike at the 31-60 day bucket; $7.2M exposure overall, most clustering after a demand slowdown. Empty cells have not matured yet.
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.
↗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.
⚙Your operations software
Quoting, job management and finance, so contracted and settled revenue is grounded in delivery, not just CRM optimism.
Proof
What operators get when losses become data.
When every loss is priced and traced, the winnable ones rise to the top and the rest stop draining the team. A sample of the outcomes.
Field services30:1return
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 →The rest of the picture
One view of nine.
Every dimension of your revenue, at the same depth, reconciled to the same source.
Pipeline Money →
Where revenue is won, contracted and in-flight.
Channels & ROAS →
Where spend pays back, to the campaign.
People & Performance →
Region, team and rep performance.
Won / Lost ◆
Why deals close or die.
Customers →
The full journey and where revenue concentrates.
Geography →
Postcode-level and branch benchmarks.
Velocity & Lag →
How fast deals move and mature.
Pipeline Economics →
CAC by stage, LTV:CAC, payback.
Questions
The things buyers ask.
It is the most common starting point. We help standardise your reason taxonomy in onboarding and reconcile it against the deal record, so the reasons become consistent enough to act on rather than free-text noise.
Stalled and lost are separated explicitly. Win rate is measured on deals that reached a decision, and the perpetually-open deals are tracked in their own view so they do not flatter or distort the number.
Yes. Every reason is sliceable by the stage it struck, the segment, the channel and the rep, and traces back to the underlying lost deals.
From the loss reason and competitor fields on closed-lost deals in your CRM, standardised so head-to-head win rates are consistent across reps.
Every loss is priced in pipeline value, so the reasons are ranked by the revenue at stake, not by how often they are typed.
Turn your losses into a fixable list.
Connect your CRM. We standardise your loss reasons, price them in revenue, and trace each to the stage and rival it came from.
01
Connect your CRM
Deals, stages, reasons and competitors.
02
Standardise reasons
A taxonomy you can actually act on.
03
Price every loss
Each reason in revenue at stake.
04
Map to the stage
See where each reason strikes.
05
Get the fixes
The winnable losses, ranked.