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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, description
name description
sales-forecasting-model 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?"