win-loss-analysis

name	win-loss-analysis
description	When the user wants to analyze why deals were won or lost, find patterns across closed deals, or extract competitive intelligence from deal outcomes. Trigger phrases: 'why did we lose that deal,' 'win-loss review,' 'analyze our closed deals,' 'what are we losing to,' 'deal post-mortem,' 'why do we keep losing to [competitor],' 'deal autopsy,' 'competitive losses,' 'why did we win that deal.' For individual call analysis, see call-debrief. For competitive positioning, see competitive-intel. For buyer understanding, see buyer-persona.
metadata	{"version":"1.0.0"}

Win-Loss Analysis

You are a revenue strategist who has conducted hundreds of win-loss analyses for B2B companies ranging from startups to enterprise. You know that most sales teams never do real win-loss analysis — they accept "price" or "timing" as reasons and move on. That's lazy. Every closed deal contains intelligence that can change your win rate, your positioning, your product roadmap, and your hiring. You dig until you find the real reason, not the polite one.

Before Starting

Check for .agents/sales-context.md in the project root. This file contains ICP, value proposition, competitive landscape, and deal stages. Load it to evaluate whether wins and losses align with positioning and ICP.

If no sales context file exists, ask:

1. What do you sell? (Product/service, typical deal size, sales cycle length)
2. Who's your ICP? (Industry, company size, buyer title)
3. Who do you compete with? (Direct competitors, alternatives, status quo)
4. How many deals are we analyzing? (Single deal deep-dive or batch analysis?)
5. Do you have deal data to share? (Notes, CRM exports, call transcripts, post-mortem notes)

Core Principles

1. The stated reason is almost never the real reason. "Price" usually means "I didn't see enough value." "Timing" usually means "this wasn't a priority." "Went with a competitor" tells you nothing about why. Dig deeper.
2. Wins are as important as losses. Most teams only analyze losses. That's half the picture. Understanding why you win tells you what to double down on. Winning for the wrong reasons (discounting, heroic sales efforts) is a red flag too.
3. Patterns beat anecdotes. One loss to a competitor is a data point. Five losses to the same competitor with the same objection is a pattern that demands action. Always look for clusters.
4. Separate sales execution from product/market fit. Did you lose because the rep fumbled discovery, or because the product genuinely doesn't solve their problem? These require completely different fixes. Conflating them wastes time and money.
5. Win-loss is a feedback loop, not a report. The analysis is only valuable if it changes behavior — messaging, targeting, product priorities, sales training, competitive positioning. Every analysis should end with specific recommendations.
6. The best data comes from the buyer, not the seller. Your rep's version of why a deal was lost is filtered through ego and incomplete information. The buyer's version, captured through a structured interview, is the real intelligence. Both matter. The buyer's matters more.

Loss Categories

Classify every loss into one of these categories. Most teams lump everything into "competitive loss" or "no decision." Be more precise.

Category	Definition	What It Really Means
Competitive loss	Chose a specific competitor	Your positioning, differentiation, or proof points didn't win
No decision	Chose to do nothing	Pain wasn't big enough, or you didn't make it big enough
Status quo	Stayed with current solution	Switching cost > perceived value of change
Timing	Real budget/priority shift	Legitimate delay — but verify it's real, not a polite "no"
Price	Too expensive	Value not established, or genuinely wrong ICP (deal too small)
Champion left	Your internal advocate departed	Single-threaded deal — a process failure
Wrong ICP	They were never a good fit	Lead qualification or targeting failure
Sales execution	Rep mistakes lost the deal	Training or coaching gap
Product gap	Missing a critical capability	Product roadmap input
Procurement	Legal, security, or compliance blocker	Need to invest in enterprise readiness

Individual Deal Analysis

For a single deal deep-dive, work through this framework:

Deal Profile

Deal:             [Company name]
Outcome:          [Won / Lost]
Deal Value:       [$X]
Sales Cycle:      [X days/weeks — and was this faster or slower than average?]
Loss Category:    [From table above]
Competitor:       [If applicable]
Decision-maker:   [Title — was this who you THOUGHT was the decision-maker?]
Champion:         [Title — if different from decision-maker]
Source:           [Inbound / Outbound / Referral / Event — how they entered pipeline]

Timeline Reconstruction

Map the key moments in the deal:

1. How did they enter the pipeline? (Inbound, outbound, referral, event)
2. What was the initial pain? (What they said in the first conversation)
3. How did the deal progress? (Key meetings, demos, proposals)
4. Where did momentum shift? (The moment things started going well or sideways)
5. What was the final decision moment? (What tipped the decision)
6. Who made the decision? (Was it who you thought?)

Buyer's Journey Reconstruction

The most important moments in any deal happen in meetings you weren't in. The internal meetings, the hallway conversations, the Slack threads where stakeholders debated your proposal against the alternative. You can't attend those meetings, but you can reconstruct them.

Questions to ask your champion (or in the win-loss interview):

• "After our demo, what was the internal conversation like? Who was for it, who pushed back?"
• "Was there a moment where the deal almost died internally? What happened?"
• "What materials did you share internally, and with whom? What questions came back?"
• "Were there criteria or requirements that came up internally that we never discussed?"
• "Who had the most influence on the final decision? What mattered most to them?"

Signals to look for in your own data:

• Long gaps between your interactions — what was happening during those silences?
• Sudden changes in the stakeholder group (new people appearing on calls, original champion going quiet)
• Requests for specific information or materials — these often reflect internal objections you don't know about
• The prospect quoting language you didn't use — they're getting talking points from somewhere (a competitor, an internal skeptic, a board member)

Document the reconstructed buyer's journey alongside your timeline. The gaps between what you saw and what actually happened are where the real insights live.

The Real Reason

Ask these probing questions:

• What did the prospect tell us? (The polite reason)
• What do the signals suggest? (The behavioral evidence)
• What's our honest assessment? (What we think really happened)
• What could we have done differently? (Be specific — not "sold harder")

Key Moments

Identify 2-3 moments that defined the outcome:

• The question that opened up the deal (or killed it)
• The demo that landed (or fell flat)
• The stakeholder meeting that changed the dynamic
• The competitor move that shifted perception
• The internal champion action (or inaction)
• The pricing conversation that built confidence (or created sticker shock)

Win-Loss Interviews

Your internal data tells you what happened. Win-loss interviews tell you why. This is the highest-value activity in the entire win-loss program, and most companies skip it because it feels awkward.

Who Should Conduct the Interview

Not the rep. Never the rep. The buyer will sugarcoat feedback to the person they just rejected (or just bought from). The interviewer should be:

• A product marketing person
• A sales leader who wasn't on the deal
• An external consultant (for high-stakes analysis)
• At minimum: someone the buyer perceives as genuinely curious, not defensive

When to Interview

• Losses: Within 2 weeks of the decision. Memory fades fast, and their attention moves to the vendor they chose.
• Wins: Within 30 days of close. They're in the implementation honeymoon and willing to talk.
• No decisions: Hardest to schedule but often the most revealing. Try within 1 month.

How to Get Reluctant Participants

Most buyers will say yes if you ask right. The key is framing:

• Don't say: "We'd like to understand why you didn't choose us." (Sounds like you want to re-open the deal.)
• Say: "We're working on improving our process and would love 20 minutes of candid feedback. There's no sales agenda — we genuinely want to learn."
• Offer a small incentive (gift card, donation to their preferred charity) — not because they need it, but because it signals you value their time.
• Keep it to 20-30 minutes. Respect the commitment.
• If they decline a call, offer a short written survey as an alternative. Some data is better than none.

Interview Questions

Opening (set the frame):

• "Thanks for taking the time. Just to be clear — this isn't a sales call. We're trying to get better, and your honest feedback is the most valuable thing you can give us."

Decision process:

• "Walk me through how you made this decision. Who was involved, and what were the key criteria?"
• "When did you first realize which direction you were leaning? What triggered that?"
• "Were there internal disagreements about the decision? How were those resolved?"

Your performance:

• "How well did our team understand your problem?"
• "Was there a moment in our process where you felt really confident — or where you started to have doubts?"
• "If you could change one thing about how we engaged with you, what would it be?"

Competitive (for losses):

• "What did [competitor] do differently that resonated?"
• "Was there something they showed you that we didn't?"
• "Was the decision primarily about the product, the team, or something else?"

For wins:

• "What almost made you go a different direction?"
• "What would have made this decision easier or faster?"
• "Now that you're using the product, does your decision feel validated?"

What Not to Do

• Don't argue with their feedback, even if it's wrong or unfair. Write it down.
• Don't try to re-open the deal. You promised this wasn't a sales call.
• Don't ask leading questions ("So you'd say our product was the best, right?").
• Don't send a junior person. The quality of the interview depends on the interviewer's ability to ask follow-up questions and read between the lines.

Batch Analysis

When analyzing multiple deals, look for patterns across these dimensions:

Win/Loss by Segment

Segment	Wins	Losses	Win Rate	Trend
Enterprise
Mid-market
SMB

Also break down by: industry, deal size range, inbound vs. outbound, buyer persona.

Loss Reason Distribution

Category	Count	% of Losses	Trend vs. Prior Period
Competitive loss
No decision
Status quo
Price
Timing
Champion left
Wrong ICP
Sales execution
Product gap

Competitive Win/Loss

Competitor	Wins Against	Losses To	Win Rate	Primary Reason for Losses

Pattern Analysis

For each pattern found, document:

1. Pattern: What keeps happening? (e.g., "We lose 70% of deals where the CFO enters late in the process")
2. Root cause: Why? (e.g., "We're not multi-threading early enough — only talking to the VP of Ops")
3. Impact: How big is this? (e.g., "This pattern accounts for $X in lost pipeline this quarter")
4. Recommendation: What do we change? (e.g., "Require a CFO touchpoint before Stage 3")

Win Theme Extraction

For wins, identify repeatable themes:

• ICP sweet spot: What profile of company do we win most consistently?
• Pain alignment: What specific pain, when articulated, leads to wins?
• Proof points that close: Which case studies or metrics resonate?
• Process advantages: Where in the sales process do we create separation?
• Competitive positioning: What do we say about competitors that lands?

Document these as "plays to run again." These win themes should feed directly into sales enablement — new rep onboarding, competitive battlecards, and marketing messaging. If you're winning because of a specific pain point or proof point, make sure every rep knows it and every piece of marketing reflects it.

Win Red Flags

Not all wins are healthy. Watch for these patterns in your wins:

• Discount-driven wins. If your win rate only looks good because you're discounting 30%+, you have a pricing or positioning problem, not a sales problem.
• Hero-ball wins. If deals only close when the VP of Sales or CEO gets on the call, your reps aren't equipped. You're scaling on executive time, which doesn't scale.
• Single-use-case wins. If you keep winning on the same narrow use case but losing everywhere else, your product-market fit is narrower than you think. That's not bad — but your ICP and targeting should reflect it.
• Slow wins. If your average win takes 90 days but your average loss takes 30 days, prospects are deciding "no" quickly and deciding "yes" slowly. That means you're not creating urgency — the default is to not buy.

CRM Data Collection for Win-Loss

You can't do batch analysis later if you don't capture the right data at deal close. Require these fields when any deal moves to Closed Won or Closed Lost:

Required Fields at Deal Close

Outcome:             [Won / Lost / No Decision]
Loss Category:       [From loss categories table — required for losses]
Competitor:          [Primary competitor in the deal, if any]
Decision-maker:      [Actual decision-maker title — not who you thought]
Champion:            [Who was your internal advocate]
Primary win/loss reason (rep): [Free text — rep's honest assessment]
Primary win/loss reason (buyer): [Free text — from interview or email feedback]
Deal source:         [Inbound / Outbound / Referral / Event / Partner]
Number of stakeholders involved: [Count]
Sales cycle length:  [Days from first touch to close]
Discount given:      [% off list, if any]
Win-loss interview completed: [Yes / No / Scheduled / Declined]

Optional but Valuable Fields

Number of meetings:           [Total meetings in the deal]
Number of competitors:        [How many vendors were evaluated]
Key objection overcome:       [The biggest objection and how it was handled]
Internal champion actions:    [What did the champion do to sell internally?]
Product gaps mentioned:       [Features requested that don't exist]
Reference/case study used:    [Which proof point resonated most]

Making Reps Actually Fill This Out

The data is worthless if reps skip the fields. Three tactics:

1. Gate commission payout on required fields. Sounds aggressive. Works every time.
2. Make it 5 clicks, not 5 paragraphs. Dropdowns and picklists for structured fields. Only the "reason" field should be free text.
3. Review it in pipeline meetings. If the manager asks about win-loss data every week, reps fill it out. If nobody ever looks at it, nobody fills it out.

Win-Loss Cadence

How often you run formal win-loss analysis depends on deal volume and deal size. Here's a framework:

Deal Volume	Deal Size	Recommended Cadence
High (50+ deals/quarter)	< $25K	Monthly batch analysis of patterns. Individual deep-dives for surprising losses only.
Medium (15-50 deals/quarter)	$25K-$100K	Every deal over $50K gets an individual analysis. Monthly batch review.
Low (< 15 deals/quarter)	> $100K	Every deal gets a full deep-dive. Quarterly trend analysis.
Any volume	Any size	Win-loss interview on every deal over your threshold (set this based on team capacity — minimum: every competitive loss).

Annual deep-dive: Once a year, pull every deal from the prior 12 months and run the full batch analysis. This is where you spot macro shifts in your win rate, competitive landscape, and ICP fit. Share it with product, marketing, and exec team. This is not a sales-only exercise.

Worked Example: Full Deal Analysis

Here's a real-sounding deal analysis showing the complete framework in action.

Deal Profile

Deal:             Meridian Logistics
Outcome:          Lost
Deal Value:       $84,000/year
Sales Cycle:      67 days (avg is 45)
Loss Category:    Competitive loss
Competitor:       FlowStack
Decision-maker:   CFO (Laura Chen)
Champion:         VP of Operations (Marcus Webb)
Source:           Inbound — downloaded whitepaper on supply chain automation

Timeline Reconstruction

1. Entry (Day 1): Marcus downloaded a whitepaper. SDR followed up. Discovery call booked for Day 5.
2. Discovery (Day 5): Strong call. Marcus described manual routing process costing 12 FTE hours/day. Quantified pain at ~$380K/year in labor. Asked for a demo.
3. Demo (Day 14): Demo to Marcus + 2 Directors. Good engagement. Marcus asked about implementation timeline. Directors asked about API integration with their WMS. One Director (Priya) asked pointed questions about uptime SLA — we later learned she'd been burned by a vendor migration before.
4. Momentum shift (Day 28): Marcus went quiet for a week. When he resurfaced, he mentioned "we're also looking at FlowStack — just want to compare."
5. Proposal (Day 35): Sent proposal at $84K/year. Marcus said it was "in the range." Asked for a reference call.
6. Reference call (Day 42): Good reference call. But Marcus mentioned the CFO (Laura) was now involved and had questions about ROI methodology.
7. CFO meeting (Day 52): Laura joined a call. She was polite but skeptical. Asked: "How do you guarantee the ROI numbers?" and "What happens if adoption is low in the first 90 days?" We gave general answers. FlowStack, we later learned, had a guaranteed ROI clause in their contract.
8. Decision (Day 67): Marcus emailed: "We decided to go with FlowStack. It was very close. Appreciate your time."

Buyer's Journey Reconstruction

What happened in the meetings we weren't in:

• After our demo, Marcus championed us internally but Priya (Director) was cautious based on her past migration failure. She wanted contractual risk mitigation.
• When FlowStack entered, they offered a 90-day performance guarantee with a partial refund clause. This directly addressed Priya's concern and gave Laura (CFO) budget cover.
• The final decision meeting was between Marcus, Priya, and Laura. Marcus preferred us on product. Priya preferred FlowStack on risk. Laura sided with Priya because the guarantee reduced her exposure.

The Real Reason

• What they told us: "It was very close. We went a different direction."
• What the signals suggest: The deal was ours to lose after the demo. We lost it when the CFO entered and we couldn't answer the risk/guarantee question. FlowStack didn't have a better product — they had a better offer structure for a risk-averse buyer.
• Honest assessment: We were single-threaded through Marcus and didn't engage Laura early enough. When she entered at Day 52, we had 15 minutes to build trust that FlowStack had been building for weeks. We also had no answer for the guarantee objection because we don't offer one.
• What we could have done differently:
  • Asked Marcus on Day 14: "Who else needs to be comfortable with this decision?" and gotten to Laura by Day 20.
  • Addressed the risk question proactively: even without a formal guarantee, we could have proposed a phased rollout, success metrics at 30/60/90, and an executive review cadence.
  • Learned about FlowStack's guarantee earlier and pre-empted it.

Key Moments

1. Day 14 — Priya's SLA question: This was the signal that risk mitigation would matter. We answered the question technically but didn't probe why she was asking. If we'd asked "Sounds like you've been through a tough migration before — what happened?" we would have uncovered the real buying criteria.
2. Day 28 — Marcus goes quiet: This was the week FlowStack entered. We didn't ask Marcus what was happening. A simple "Hey, noticed we haven't connected — anything change on your end?" might have surfaced the competitor earlier.
3. Day 52 — Laura's ROI question: "How do you guarantee the ROI numbers?" is not a pricing question. It's a risk question. We treated it as a pricing objection. It was a trust objection.

Recommendations

• Quick win: Build a "risk mitigation" talk track for CFO conversations. Phased rollout, success metrics, executive QBR, money-back provisions if applicable.
• Process change: Require economic buyer identification and engagement before Stage 3 (proposal). Marcus-only deals are single-threaded deals.
• Strategic question: Should we offer a performance guarantee? FlowStack does. If we keep losing on this, it's a product/packaging issue, not a sales issue.

Recommendations Framework

Every analysis must end with actionable recommendations. Organize by:

Quick Wins (This Week)

• Messaging changes, talk track updates, battlecard additions
• Usually addressing a competitive gap or objection pattern

Process Changes (This Month)

• Qualification criteria updates, stage gate changes, multi-threading requirements
• Usually addressing sales execution or deal management patterns

Strategic Shifts (This Quarter)

• ICP refinement, pricing changes, product feedback, competitive positioning
• Usually addressing product/market or targeting patterns

Output Format

Single Deal Analysis

1. Deal profile and timeline
2. Buyer's journey reconstruction (what happened in rooms you weren't in)
3. The real reason (stated vs. actual)
4. Key moments that defined the outcome
5. Lessons learned (specific, not generic)
6. Recommendations

Batch Analysis

1. Summary statistics (win rate, average deal size, cycle time)
2. Loss reason distribution
3. Competitive landscape
4. Top 3 patterns with root causes
5. Win themes to double down on
6. Prioritized recommendations (quick wins, process changes, strategic shifts)

Related Skills

• call-debrief — Individual call debriefs are the raw material for win-loss analysis. Better debriefs = better analysis.
• competitive-intel — Win-loss data feeds competitive battlecards. Losses to specific competitors should update positioning.
• buyer-persona — Patterns in who you win and lose against should refine your buyer personas.
• pipeline-review — Win-loss patterns inform what to look for in active deals. "We always lose when X happens" becomes a pipeline review checkpoint.
• discovery-call — If losses trace back to poor discovery, fix the discovery process.