A MEDDPICC Qualification Prompt That Scores the Deal

Every rep knows MEDDPICC. Far fewer run it on a live deal without lying to themselves. The framework is eight letters; the discipline is scoring each one honestly against what was actually said on the call. A MEDDPICC qualification prompt does the honest part for you — it reads the call notes, scores all eight elements with the evidence, and tells you which gap to close next.

The pages that rank here split into two camps, and both leave a gap. The explainer camp, sites like tldv.io, defines the acronym thoroughly and then offers open-ended "prompts" like "how to prioritize sales efforts with MEDDPICC" with no scoring at all (tldv.io). The tool camp has scored prompts, but they stop at the number. Momentum's call-review prompt scores each element 0 to 4 and rolls up to 100, yet by its own structure it "does not explicitly recommend next actions for underperforming areas" (momentum.io). A score without a next action is a diagnosis without a prescription.

What a scored qualification prompt does

The job is to turn call notes into a deal review with a fixed shape. One pass returns:

• A per-element score for all eight MEDDPICC letters
• The evidence for each score, quoted from the notes
• A clear gap wherever an element scores low
• The single next action to close each gap
• An overall 0–100 with the weakest element called out
• A disqualify flag when two or more core elements are empty
• A what-to-ask-next line for the next call

That last bit is what separates a qualification prompt from a quiz. It doesn't just grade the deal. It tells you what to do about the weakest element before the next conversation.

Anatomy of the prompt

You paste notes, the prompt scores. Keep the rubric and output contract at the end so they aren't drowned by a long transcript.

Variables
  {{call_notes}}   → notes or transcript from the deal so far
  {{deal_stage}}   → where the deal sits (Discovery, Proposal, etc.)
  {{deal_value}}   → ACV, so scoring weight matches the stakes

Prompt
  Role: a deal desk reviewer scoring qualification.
  Task: grade {{call_notes}} against all 8 MEDDPICC elements.
  Rule: score only on evidence present in the notes; no assuming.

Output contract (last lines of the prompt)
  | Element | Score /10 | Evidence | Gap | Next action |
  (8 rows: Metrics, Economic buyer, Decision criteria,
   Decision process, Paper process, Identify pain, Champion, Competition)
  Then: Overall /100, weakest element, disqualify? (Y/N), what to ask next.

The rule that does the heavy lifting is score only on evidence present in the notes. Without it, the model is generous. It'll award a 7 for "Economic buyer" because someone senior was on the call, even if nobody confirmed budget authority. With it, an unconfirmed economic buyer scores a 2 and gets flagged. That honesty is the whole point of qualifying.

Step-by-step usage

1. Gather the notes

Drop in everything you have on the deal: discovery call notes, the demo recap, email threads where the buyer revealed criteria. More evidence means more elements the prompt can score on fact instead of leaving blank.

2. Set the deal context

Fill {{deal_stage}} and {{deal_value}} so the prompt can weight appropriately. A missing paper process is a yellow flag at discovery and a red one at proposal. The stage tells the model which.

3. Run the rubric

Paste and run. Claude honors the eight-row table and the "evidence" column reliably. GPT-4o occasionally collapses two elements into one row on a long transcript, so add "exactly 8 rows, one per element" on the final line. Gemini scores well but editorializes; "no prose outside the table and rollup" keeps it disciplined.

4. Read the weakest element first

The overall score is for the forecast. The weakest element is for you. If "Champion" scores a 2, that's where the deal dies, and the "next action" column tells you to go build a second relationship before the next call.

5. Re-score after the next call

Save the filled prompt. After the next conversation, re-run it with updated notes. Because the rubric is fixed, you can watch a 41 climb to a 68 as gaps close, or notice it stall, which is its own answer.

Prompt-craft patterns that make it honest

Evidence column or it's a vibe. Forcing the model to quote the notes for each score makes it accountable. If it can't cite evidence, the score should be low by default, not high. This is the single biggest upgrade over the explainer-style prompts.

For each element, the Evidence cell must quote or paraphrase a specific
line from {{call_notes}}. If there's no evidence, score ≤3 and write "none".

Next action, not just a number. Pair every low score with one concrete action. A 3 on "Decision process" becomes "ask who signs and in what order" — a thing the rep can do, not a thing the rep already knew was weak.

A real disqualify boundary. A qualification prompt that never disqualifies anything is a cheerleader. Give it a hard rule: if two or more of Metrics, Economic buyer, or Identify pain are empty, flag the deal as not yet qualified.

If ≥2 of {Metrics, Economic buyer, Identify pain} have no evidence,
set disqualify = Y and explain which are missing.

A caveat worth stating: the score is only as honest as the notes. A rep who writes optimistic notes gets an optimistic score, and no prompt fixes happy ears. Treat the output as a structured second opinion on the notes, not ground truth about the deal.

Variables you'll set

Getting started

1. Collect every note and recap you have on the deal.
2. Set {{deal_stage}} and {{deal_value}}.
3. Run the rubric and read the weakest element first.
4. Work the "next action" for that element before the next call.
5. Re-score after each conversation and track the climb.
6. Want a free way to try it? The MEDDPICC Deal Checker is a no-cost single prompt that runs the eight-element check so you can see the shape before you upgrade.

For deal-by-deal scoring across a whole pipeline, the Salesforce Pipeline Agent Pack flags which deals are even worth a full MEDDPICC review.

Qualifying isn't about knowing the framework, it's about being honest with the notes in front of you. A scored prompt forces that honesty and hands you the next move, so the deal's weak spot shows up while you can still fix it. Once a deal scores well, the sales follow-up prompt keeps it warm between calls, and the Salesforce pipeline prompt watches the rest of the pipeline for the deals quietly going stale.