SalesPipeline & Forecasting

AI Prompts for Pipeline Review and Analysis

A pipeline review is a diagnostic, and it needs the right measurements: stage conversion and where deals die, days in stage and where they wait, coverage against target by period, aging, and slippage. Reviewed as a list of deals, a pipeline is a set of stories; reviewed as a system, it shows the two or three places where the process is losing value — and which deals need inspection this week.

This page keeps the original export-analysis prompt and adds the metric definitions and the review format around it. Deal-level inspection has its own page (deal review), as does forecasting; this is the health check on the whole.

Before you use these

Have these ready to replace the highlighted [variables]:

Pipeline export: opportunity, stage, stage entry dates, amount, close date, source, owner, segment, last activity
Definitions of stages and what qualifies a deal to enter each
Targets for the period and the coverage ratio you expect
Historical conversion and cycle time by stage, if known

The prompts

1. Analyze a pipeline export
2. Define the pipeline health metrics for your motion
3. Run the pipeline review meeting

1. Analyze a pipeline export

Best forA first-pass analysis of conversion, velocity, stalled deals and win-rate patterns from a CSV.

Inputs needed

Pipeline export
Stall threshold

How to use itThe original prompt from this page. Paste a real export or a representative sample; set the stall threshold to your typical stage duration.

Expected outputTables for conversion by stage, days in stage, stalled deals, win rate by source and size band; the five at-risk deals with reasons; three process changes the data supports.

Act as a RevOps analyst. Here is my pipeline export: [paste CSV/data]. Analyze: conversion rates by stage, average days in stage, deals stalled beyond [X] days, win rate by source and by deal size band. Flag the 5 deals most at risk with reasons, and give 3 process changes the data supports. Output tables first, narrative after.

2. Define the pipeline health metrics for your motion

Best forA small metric set with exact definitions, so reviews compare the same things week to week.

Inputs needed

Stages and entry criteria
Targets
Historical rates

How to use itGive your stage definitions and targets. The model defines each metric with formula, exclusions and the threshold that should trigger attention.

Expected outputMetric definitions (coverage, stage conversion, velocity, aging, slippage, creation rate) with formulas, exclusions, thresholds, and the review cadence for each.

Act as a revenue operations lead defining pipeline health metrics for [team / motion].

Stages and entry criteria: [list]
Targets: [bookings by period; expected coverage ratio]
Historical rates: [stage conversion, cycle time, win rate — if known]
Deal profile: [size, cycle length, seasonality]

Define, with formula, inclusions/exclusions, and the attention threshold:
1. Coverage: open pipeline expected to close in the period ÷ remaining target — by period and by rep; the ratio that is healthy for our win rate (derive it: 1 ÷ win rate, adjusted for stage mix).
2. Stage conversion: by stage, by cohort (deals created in a period), not by snapshot; the stages where drop-off is worst.
3. Velocity: (opportunities × win rate × average deal) ÷ cycle length; and days in stage versus historical norm.
4. Aging: deals past the stage norm; deals past their original close date.
5. Slippage: close dates moved in the period, by count and value; repeat slippers.
6. Creation: new pipeline created versus the rate required to sustain coverage given cycle length.
7. Hygiene: deals with no activity in [n] days, missing next steps, amounts unchanged since creation.
For each: the review cadence (weekly / monthly), the owner, and the decision it informs. Keep to eight metrics or fewer.

3. Run the pipeline review meeting

Best forA weekly review that ends with named actions on specific deals and process, not a status read-out.

Inputs needed

Current metrics
Flagged deals
Prior actions

How to use itPaste this week's metrics and the flagged deals. The model builds the agenda, the deal inspection list and the action log format.

Expected outputReview agenda with time allocation, the deals to inspect this week with the reason and the question, process findings, actions with owners and dates, and the forecast implications.

You are preparing the weekly pipeline review for [team].

Metrics this week: [coverage by period, conversion, velocity, aging, slippage, creation, hygiene — with prior week for trend]
Flagged deals: [from the analysis: at-risk, aged, slipped, stalled]
Prior actions: [last week's actions and status]
Time: [minutes]

1. Headline: the two or three things that changed this week and what they mean for the period target.
2. Deal inspection list: the deals to review in the meeting (no more than [n]), each with the reason it is flagged, the one question to ask the owner, and the decision needed (re-baseline, escalate, disqualify, keep).
3. Process findings: patterns across deals (e.g. drop-off at a stage, slippage concentrated in a segment) and the process action.
4. Coverage gap: pipeline creation needed by when to protect next period, by rep.
5. Action log: action, owner, due date, the metric it should move — carried forward with status.
6. Forecast implication: deals that should change category as a result.
7. Agenda with time per section; deals not on the inspection list are not discussed.

Keep the review to decisions. Deal stories without a decision go to one-on-ones.

Related prompts

Logical next step

After this, most sales teams move on to Deal Reviews.

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