Territory Forecast
Forecasting each patch with evidence, not hope.
Workflow
Step 1Territory Assigned
ObjectiveStart from a defined patch.
InputTerritories
OutputActive territories
Key activities
Confirm the patch and its owners
Decision points
Is the patch clear?
Tools: CRMRoles: Sales ops
Success: Patch confirmed
Quality gate: Go: assigned. Loop back: unclear.
Why it matters
- A territory forecast tells you where the number will come from — and where it won't — before it matters.
Best practices
- Base the model on historical conversion, not intuition.
- Scenario-plan: best, base, worst.
- Hold reps accountable to the evidence.
- Measure accuracy and refine.
Common mistakes
- Forecast = rep's guess summed up.
- No scenario analysis — one number, no range.
- Never checking forecast accuracy.
Key questions
- What is the evidence behind this territory's number?
- What scenario would break it?
Agents that drive this
Forecast AnalyserComp & Quota
Tools we use · alternates in [ ]
Metabase[ Looker Studio, Power BI, Grafana ]HubSpot[ Salesforce, Pipedrive, Attio ]