Gather Historic Service Data and Operational Metrics
Collect operational, financial, and client usage data from past consultancy projects to baseline current performance. The founder aggregates metrics on delivery hours, gross margins, recurring client requests, and implementation bottlenecks across previous engagements.
Gathering empirical venture inputs grounds the productisation strategy in historical performance rather than optimistic projections. This ensures the future product's pricing, delivery mechanics, and feature sets reflect genuine operational realities and customer behaviours.
A comprehensive baseline report combining client timesheets, project gross margins, delivery friction logs, and feature request frequencies across historical engagements. The data set must clearly highlight the true cost of bespoke delivery versus the projected economics of a productised tier.
Five questions an expert would ask when reviewing your output
Use these to challenge assumptions, pressure-test your logic, and check the quality of this action's output in the context of the parent task and wider venture development.
- 1
What historical timesheet or margin data proves that your custom service delivery is becoming commercially unviable at scale?
- 2
How reliable are your delivery cost calculations across past projects, and where have you undercounted hidden account management time?
- 3
Which specific customer cohorts generated the highest gross margins during your agency phase, and are they the same cohort targeted for the product?
- 4
What operational data demonstrates that your team spends excessive time on repetitive onboarding or setup tasks?
- 5
How have you validated that past clients bought your service for the underlying methodology rather than personal relationships with your team?