Categorize your losses and name the fix.
Sorts lost deals into no-decision, price, competitor, timing, or fit, pulls competitive intel, and splits preventable from structural.
Inside: The loss taxonomy, the competitive intel pull, and the fix per theme.
Install it in one line, or paste it in.
~/.claude/skills/ and runs automatically when it is relevant.Connect your context. Set it to your motion.
it reads all of the above automatically, across every lost deal in the window you pick, including the raw loss notes.
reads what the buyer actually said before they went dark, so "no decision" gets a real cause.
on lost trials, shows whether they ever reached first value, which separates a product gap from a sales gap.
This was built for a B2B SaaS org running a staged pipeline. Set these to your stack:
Run any loss taxonomy you like. The skill sorts your losses into your buckets and names the fix per bucket, so point it at your fields, not anyone else's.
| Set this | What it is | Default / Example |
|---|---|---|
| LOST filter | how you mark a loss | Stage = Closed Lost |
| WINDOW | the loss-date range to analyze | trailing 4 quarters |
| REASON field | your loss-reason picklist | Closed Lost Reason |
| NOTES field | free-text loss notes | loss descriptionnext-step notes |
| COMPETITOR field | who you lost to | competitor on the deal |
| STAGE_AT_LOSS field | how far it got before dying | stage when marked lost |
| SEGMENT fields | how you group accounts | industryemployee countregion |
| MIN_SAMPLE | fewest losses before a theme counts | 5 (raise if you lose a lot) |
Everything the skill does, in full.
Reads your closed-lost deals and tells you why they died, in buckets you can act on: no decision, price, competitor, timing, or fit. It pulls the competitive intel out of the losses, then splits them into two piles that matter more than the total: the losses you could have prevented, and the ones that were structural and never yours to win. Each theme ends with the fix. The point is not to feel bad about the number. It is to stop losing the same deal twice.
- 1Loss categorization (clean buckets)
Sort every lost deal into one primary reason: NO_DECISION (they picked nothing, status quo won), PRICE (budget or value gap), COMPETITOR (they picked someone else), TIMING (real but not now), or FIT (never a match). When the reason field is blank, read the notes or the transcript to place it. Report the share and the lost deal size behind each bucket, so a common reason and an expensive reason are both visible.
- 2Competitive intel pull
For every COMPETITOR loss, pull who won and, where the notes say so, why. Roll it into a per-competitor view: how often they beat you, at what stage, in which segment, and the reason that keeps repeating. This is the sheet your reps wish they had before the next competitive deal.
- 3Preventable vs structural split
Split every loss into two piles. PREVENTABLE: the deal was winnable and something in the motion lost it (single-threaded, slow follow-up, wrong persona, weak business case, late competitor entry). STRUCTURAL: it was never yours (no budget, no real need, wrong segment, a feature you do not build). This split matters more than the raw count, because only one pile is yours to fix.
- 4The fix per theme
Every theme ends with a specific, do-this-next fix, not a platitude. NO_DECISION driven by no compelling event points to earlier qualification of the trigger. PRICE losses that cluster at one tier point to packaging. A competitor winning late points to multi-threading sooner. Name the change, not the feeling.
- No theme reported below MIN_SAMPLE. A single bad-luck loss is not a trend.
- Every loss lands in exactly one primary bucket, so shares add up and nothing is double-counted.
- Preventable is only claimed with a reason from a field, a note, or a transcript, never a hunch.
- Competitive claims name the source. No invented win reasons for the other side.
CLOSED-LOST ANALYSIS · 41 losses, trailing 4 quarters Loss reasons Bucket Share Lost $ Note No decision 37% $520K Status quo, no compelling event Competitor 27% $410K Lost late, after Solution Validation Price 20% $300K Clustered at the mid tier Timing 10% $140K Real, revisit next cycle Fit 6% $70K Wrong segment, disqualify earlier Preventable vs structural Preventable: 54% (no-decision + late competitor losses) Structural: 46% (timing, fit, no-budget) Who we lose to Competitor Losses Wins late? Segment Rival A 8 Yes, 6 of 8 mid-market Rival B 3 No enterprise Fixes: 1. No decision. Qualify the compelling event before Stage 3, or park it. 2. Rival A. Multi-thread by Stage 2. They win by out-flanking a single champion. 3. Price at the mid tier. Revisit packaging, not discounting.
MIN_SAMPLE (5) and the trailing-4-quarter window are defaults, not laws. They suited a mid-market SaaS cycle with steady loss volume. If you lose a small number of large deals, widen the window so the buckets are not built on three data points. The preventable-vs-structural split is always grounded in your own notes and fields, so the fix list is yours, not a benchmark's.
Where an operator takes this next.
The read is step one. Here's where an operator takes it once the manual version proves out.
You built the read once; now it runs itself.
Point a scheduled Claude task at Salesforce closed-lost exports and drop the themes into Slack before the next deal review.
Push the "qualify compelling event by Stage 2" rule into a Gong scorecard so reps get flagged live, not in a postmortem.
Route every COMPETITOR loss into a competitive-battlecard update automatically, so the sheet reps wish they had actually gets built.
One skill is the on-ramp.
A single skill does one job. Chained into a playbook, or run as a full build, it becomes a system. Here is where this one plugs in.