Win-Loss Analyst
Tests whether you really lost on price
You win 60% of closed deals, but only 18.2% against Rivalco.
30 closed deals: 18 won ($801K) and 12 lost ($605K); 57% by value.
Rivalco, outbound win rate is at or below half the overall rate.
Won deals took 43 days on average and lost deals 91: the deals you lose also drag on.
Why a deal was lost is not in the data; segments need at least 4 deals to be called weak or strong.
Win rate by competitor (%)
- Rivalco (11)18.2%
- Northgate (8)62.5%
- No competitor (11)100%
Win rate by lead source (%)
- outbound (12)16.7%
- inbound (9)77.8%
- referral (9)100%
Average sales cycle (days)
Segments, most lost value first
| Segment | Deals | Won | Win rate | Lost value |
|---|---|---|---|---|
| Competitor: Rivalco | 11 | 2 | 18.2% | $502K |
| Source: outbound | 12 | 2 | 16.7% | $499K |
| Source: inbound | 9 | 7 | 77.8% | $106K |
| Competitor: Northgate | 8 | 5 | 62.5% | $103K |
| Competitor: No competitor | 11 | 11 | 100% | $0 |
| Source: referral | 9 | 9 | 100% | $0 |
What to do this week
- Build a plan against Rivalco: $502K of lost value and a 18.2% win rate.
- Rethink outbound as a source: 16.7% of its deals are won. Qualify harder or shift effort to referral.
- Set a cycle limit: lost deals ran 91 days against 43 for won ones, so a deal still open past about 65 days is a warning.
Do
- Interview a sample of lost deals against your weakest competitor before changing price or product.
Don't
- Don't judge sources on win rate alone: check deal size and cycle too.
How to improve
- Add the loss reason chosen by the rep so the next report can test it against the pattern.
- Add stage reached so the next report can show where each segment drops out.
Demo
Overview
Every CRM has a closed-lost reason field and the data in it is close to worthless. It is chosen by the person who lost the deal, at the moment they lose it, from a list written by someone else — and "price" is always on that list and never wrong enough to argue with. So price dominates every closed-lost report in every company, and the conclusion drawn from it, discount more, is expensive and usually mistaken.
The evidence that contradicts it is in the same records. If price were the reason, losses would concentrate where the price gap is largest. Usually they concentrate somewhere else: in deals where one specific competitor was present, in deals that never reached a second meeting, in deals where the buyer needed something the product does not do, in deals where the champion was too junior to sign. All of that is visible in stage history, call notes, participants and stage durations.
And nobody analyses the wins. A loss analysis without them cannot say what is different about the deals you close, which is the more useful half.
This agent tests the stated reason against the evidence, reports what actually separates wins from losses, and never assesses an individual rep. A per-person win-rate table gets managed rather than acted on, and it corrupts the reason field further.
Benefits
You stop discounting for the wrong reason
Which is the most expensive mistake this data causes.
Product and positioning get real input
From evidence, not from a field chosen under pressure.
Qualification improves
Because you know which deals were never winnable.
What it does
Tests the stated reason against the evidence
If price were the reason, losses would cluster where the gap is largest. Usually they cluster somewhere else entirely.
Analyses the wins too
A loss report alone cannot tell you what is different about the deals you close.
Finds where deals actually die
The stage they stop at, and how long they sat there. Far more honest than a dropdown.
Reads competitor presence
Losses concentrated against one competitor is a positioning problem, not a pricing one.
Checks buyer seniority
A champion who could never sign is a qualification finding that gets recorded as price.
Never ranks reps
A per-person win-rate table gets managed rather than acted on, and it corrupts the reason field further.
What this changes
What this changes about your week
- It takes over
- Testing why deals were actually lost, against what was typed in the CRM.
- Done today by
- A closed-lost report that everyone reads and nobody trusts.
- How often
- Quarterly, from the same unreliable field.
- Typical manual effort
- Stage history, competitors, seniority and requirements all read across won and lost deals together.
Why Sales in particular. 'Price' is chosen by the person who lost, at the moment they lost, from a list someone else wrote — it is always available and never wrong enough to argue with, so it swamps everything and the fix it implies is expensive.
Runs unattended
Started by you or by an event, and it finishes on its own. Nothing waits for someone to be at a desk.
The same standard every time
The two-hundredth item is held to the bar the first one was. Consistency is the part people cannot sustain.
It cannot act on its own
Win-Loss Analyst has no path to sending, spending or committing. That limit is why its output is safe to act on.
How it runs
This agent runs server-side through the PROMIVO runtime. Each run is logged step by step and every tool call is permission-checked before it executes.
- 1InputValidated against the agent input schema
- 2Modelclaude-opus-5 with automatic fallback
- 3Toolsextract_structured_data
- 4PermissionsRuns READ actions automatically; anything higher waits for approval
- 5OutputStructured result matching the output schema
- 6LoggingTokens, duration and every step recorded
Requirements
Integrations
No integrations required.
Before you start
- Closed won and closed lost deals with value, stage history and dates
- Stated close reasons
- Competitors present, where recorded
- Contact roles and seniority, and notes or requirements captured
- Requires the All-Access plan or higher
Use cases
Quarterly win-loss review
What actually separates the two.
Before a pricing change
Whether price is really the constraint.
Competitive strategy
Which competitor you lose to, and at which stage.
Product roadmap input
Requirements raised in deals you lost.
Pricing
All-Access
Billed monthly through your PROMIVO subscription. Cancel at any time.
Runs consume your plan allowance for agent executions and tokens. See plan limits
FAQ
Does it rank salespeople?
No, deliberately. A per-person win-rate table gets managed rather than acted on, and the first thing to change is what people type into the reason field. Findings are about deals and patterns.
Why not just use our closed-lost reasons?
Because they are chosen by the person who lost, at the moment they lost, from a list someone else wrote. Price is always available and never wrong enough to argue with, so it swamps everything.
Does it interview customers?
No. It contacts nobody. It works from your own records — and where those cannot answer a question, it says which question a real win-loss interview would need to answer.
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