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Managed IT service Funnel Sales Forecast

Combine explicit funnel-stage assumptions into expected sales.

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Managed IT service / client month economics

Managed IT service Funnel Sales Forecast

Your result22.5 expected sales

184,00020.254,50022.55,00024.755,500276,000Relevant visits
Other inputs stay fixed. Point labels show the calculated result in expected sales; this is a scenario comparison.

Sales = visits × enquiry rate × qualified share × close rate

What you’ll need

Gather project time logs, licence invoices and retainer scopes. Include licenses, support labour, and monitoring. The starting figures are examples. Replace them with your own records.

Formula and worked example

Sales = visits × enquiry rate × qualified share × close rate

Example figures
InputExample
Relevant visits5,000
Visit-to-enquiry rate3 %
Qualified share of enquiries60 %
Qualified lead close rate25 %
Calculated result22.5 expected sales

Choose reliable inputs

Include software licences, delivery time, revisions and ongoing support when costing a project. For this managed it service calculation, use project time logs, licence invoices and retainer scopes and a consistent definition of one client month.

  • Licenses: include the portion belonging to this client month or reporting period, and record where the value came from.
  • Support labour: include the portion belonging to this client month or reporting period, and record where the value came from.
  • Monitoring: include the portion belonging to this client month or reporting period, and record where the value came from.

Use the same currency for every money input. Do not mix weekly costs with monthly revenue, or count the same expense in both an itemised cost and allocated overhead.

Can I multiply rates from different customer cohorts?

Only combine aligned cohorts and time windows. Mixing unrelated stages can create a misleading forecast.

Fractional expected sales are averages, not guaranteed individual outcomes.

Compare a different assumption

What if this input changes?

If relevant visits rises by 10%, this example changes by 2.25 expected sales. This shows the effect of one change; it does not predict what will happen.

Open the calculator, save your baseline, then change the input supported by the least reliable estimate in your records. Compare both scenarios before committing to a price or capacity promise.

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