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pm-claude-skills/skills/sales-forecasting-model/SKILL.md
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mohitagw15856 f3b9d008fe feat: 100 skills milestone — 7 new skills + quality improvements across all 93
New skills added:
- teaching-lesson-plan: structured lesson plans for any subject/audience/setting
- seo-content-brief: complete SEO briefs with intent, competitor gaps, and outline
- media-pitch: story-first journalist pitches with angle development framework
- change-management-plan: stakeholder analysis, comms strategy, adoption metrics
- workshop-facilitation-guide: activity instructions, decision protocols, facilitator moves
- sales-forecasting-model: pipeline model, scenario analysis, assumption log
- tax-planning-checklist: year-end tax planning across income, pension, CGT, reliefs

Quality improvements across all 93 existing skills:
- Standardised description format: "Verb the thing. Use when X. Produces Y."
- Added Required Inputs section to all skills missing it (prompts for missing info)
- Added Quality Checks section to all skills missing it (specific, not generic)
- Fixed broken multiline YAML descriptions
- Removed non-standard frontmatter keys (tool_integration, metadata blocks)

README updated to v6.0.0 with 100-skill count, new skill tables, and article series

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-20 20:52:31 +01:00

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---
name: sales-forecasting-model
description: "Build a structured sales forecast framework for any business or team. Use when asked to build a sales forecast, create a revenue model, project pipeline, or build a bottom-up forecast. Produces a forecast methodology, pipeline model, scenario analysis, and assumption log."
---
# Sales Forecasting Model Skill
Produces a structured sales forecast framework — from pipeline conversion modelling to scenario analysis. Built for revenue and sales leaders who need a defensible forecast, not a spreadsheet guess.
## Required Inputs
Ask the user for these if not provided:
- **Business type** (SaaS / Transactional / Services / Marketplace)
- **Forecast period** (monthly / quarterly / annual)
- **Sales motion** (inbound / outbound / channel / PLG / mixed)
- **Current pipeline data** (number of deals, stages, values — rough is fine)
- **Historical conversion rates** (if available — otherwise model will flag as assumption)
- **Average deal size and sales cycle length**
## Output Structure
---
# Sales Forecast: [Team / Business] — [Period]
**Forecast type:** [Bottom-up pipeline / Top-down quota / Capacity-based / Hybrid]
**Period:** [Month / Quarter / Year]
**Created:** [Date]
**Forecast owner:** [Name]
---
## 1. Forecast Methodology
**Chosen approach:** [Bottom-up / Top-down / Hybrid] — and why for this context.
Bottom-up (recommended when pipeline data exists):
> Start from real deals in the pipeline. Apply stage-by-stage conversion rates. Sum to a revenue number.
Top-down (useful for planning, not for calling a number):
> Start from market or quota. Work backwards to activity targets.
---
## 2. Pipeline Stage Model
Define the sales stages and the expected conversion rate between each:
| Stage | Description | % of deals that advance | Avg time in stage |
|---|---|---|---|
| Prospect | Identified, not contacted | — | — |
| Qualified | Discovery done, confirmed fit | [X%] | [N days] |
| Proposal | Proposal sent | [X%] | [N days] |
| Negotiation | Commercial terms being agreed | [X%] | [N days] |
| Closed Won | Contract signed | [X%] | — |
**Overall pipeline conversion rate:** [X%] (Qualified → Closed Won)
**Average sales cycle:** [N days from Qualified to Close]
---
## 3. Current Pipeline Snapshot
| Stage | Number of deals | Total value | Expected close (weighted) |
|---|---|---|---|
| Qualified | [N] | £[X] | £[X × conversion %] |
| Proposal | [N] | £[X] | £[X × conversion %] |
| Negotiation | [N] | £[X] | £[X × conversion %] |
| **Total** | | **£[X]** | **£[weighted total]** |
**Coverage ratio:** [Weighted pipeline ÷ target = X×]
*Rule of thumb: 3× pipeline coverage is needed for confident forecast; 2× is tight; below 1.5× is at risk.*
---
## 4. Scenario Analysis
| Scenario | Assumption | Revenue | Probability |
|---|---|---|---|
| Upside | All Negotiation + top 50% of Proposal close | £[X] | [%] |
| Base | Weighted pipeline conversion at historical rates | £[X] | [%] |
| Downside | Conversion rates drop 20% from historical | £[X] | [%] |
**Committed forecast:** £[X] — [The number the forecast owner is willing to call. Between base and downside.]
---
## 5. Key Assumptions Log
Every forecast is a set of assumptions. Name them explicitly so they can be updated:
| Assumption | Value | Confidence | Source | Last updated |
|---|---|---|---|---|
| Avg deal size | £[X] | High/Med/Low | [Last N deals] | [Date] |
| Sales cycle | [N days] | | | |
| Close rate from Proposal | [X%] | | | |
| Seasonal factor | [e.g. Q4 +20%] | | | |
| Churn/contraction | [X% of ARR at risk] | | | |
---
## 6. Activity-Based Sanity Check
Work backwards from the forecast to check if the required activity is achievable:
To hit £[target]:
- Deals needed to close: [N] (target ÷ avg deal size)
- Qualified pipeline needed (at current conversion): [N deals or £value]
- Discovery calls needed per week to build that pipeline: [N]
- Outreach needed per week (at [X%] meeting rate): [N]
**Does the team have capacity to generate this?** [Yes / No — flag if not]
---
## Quality Checks
- [ ] Forecast methodology is stated (not just a number)
- [ ] Stage conversion rates are based on historical data or flagged as assumptions
- [ ] Coverage ratio is calculated
- [ ] Three scenarios are modelled (not just one number)
- [ ] Assumption log is explicit and dated
- [ ] Activity sanity check confirms the forecast is achievable with current capacity
## Example Trigger Phrases
- "Build a sales forecast for [period]"
- "Create a pipeline model for [team/business]"
- "Help me build a bottom-up revenue forecast"
- "What is our forecast for Q[N] based on current pipeline?"