Modeling the Revenue Hidden in an Evaluation Pipeline
The Challenge
The team could only show investors very small revenue from product evaluations. They needed to credibly paint a picture of the revenue streams that could realistically emerge from that evaluation activity — across five distinct product lines, custom development projects, and sporadic but potentially large clinical diagnostic conversions.
What I Did
- Mapped five distinct products aimed at different market segments, each with its own growth and adoption curves, into a single integrated revenue model.
- Modeled custom development projects that yielded new control sequences for inventory and product development — capturing how these triggered growth in both price and adoption over time.
- Built a simulation to model the sporadic but high-value conversions from R&D evaluation sales into clinical diagnostic use — where a fraction of evaluation customers convert to dramatically larger unit volumes. A standard forecast would either ignore these or wildly overstate them; the simulation modeled them probabilistically.
- Designed the model from the start to be handed off: clearly documented assumptions, modular structure, and a logic the team could follow, update, and present to investors independently.
Outcome
The model gave the team a credible, detailed picture of where their revenue could go — grounded in the evaluation activity they already had. It became their primary tool for investor conversations and internal planning, structured to be updated by the team as their pipeline evolved.
Working on a similar challenge?
Let's talk →- Integrated five-product revenue model with distinct adoption curves per segment
- Custom development project revenue flywheel model
- Probabilistic simulation for clinical diagnostic conversion opportunities
- Fully documented assumption framework for ongoing team use
- Model structured for investor data room presentation
All supporting analysis is documented professionally and structured for inclusion in an investor data room.