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skills/mohitagw15856/pm-claude-skills/sales-forecasting-model

sales-forecasting-model

1
mohitagw15856/pm-claude-skills·Audit passed·Snapshot d484a682e16c

Summary

This source did not publish a separate summary. Review SKILL.md before using the skill.

SKILL.md

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:

StageDescription% of deals that advanceAvg time in stage
ProspectIdentified, not contacted——
QualifiedDiscovery done, confirmed fit
[X%]
[N days]
ProposalProposal sent[X%][N days]
NegotiationCommercial terms being agreed[X%][N days]
Closed WonContract signed[X%]—

Overall pipeline conversion rate: [X%] (Qualified → Closed Won) Average sales cycle: [N days from Qualified to Close]

3. Current Pipeline Snapshot

StageNumber of dealsTotal valueExpected 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

ScenarioAssumptionRevenueProbability
UpsideAll Negotiation + top 50% of Proposal close£[X][%]
BaseWeighted pipeline conversion at historical rates£[X][%]
DownsideConversion 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:

AssumptionValueConfidenceSourceLast 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?"

Anti-Patterns

  • Do not present a single forecast number without scenario analysis — a forecast without upside and downside cases hides risk
  • Do not use 100% confidence on conversion rates that are not backed by historical data — flag them as assumptions
  • Do not skip the activity sanity check — a forecast number that requires unreachable activity levels is not credible
  • Do not use top-down quota as the only forecast method when pipeline data exists — bottom-up is more accurate and defensible
  • Do not omit the coverage ratio — without it, stakeholders cannot assess whether the pipeline is sufficient to hit target

Related skills

capacity-planningcompetitor-teardowncontext-engineering-reviewrunbook-writerreceipts-audit