A pragmatic approach to pricing and packaging decisions when your data is incomplete and your sample size is small.
Anchor on value stories and real deals
Begin by writing out a small number of value stories that describe how different customer types use the product and what they get from it. Attach concrete numbers whenever you can, even if they are ranges or estimates.
Then review recent deals through that lens. Which elements of your pricing model helped the deal move forward and which created friction or confusion. This qualitative analysis is often more useful than fragile willingness to pay surveys at small scale.
Choose a small number of pricing levers
Complex metered pricing is attractive in theory but hard to sell and hard to manage internally. In many early B2B SaaS companies, a seat based or tiered packaging model with one or two add ons is sufficient.
Identify one primary value metric that tracks reasonably well with customer value and cost to serve. Use that to structure tiers. Keep discounts and exceptions visible so you can refine them over time rather than burying them in bespoke deals.
Treat each change as an experiment
Instead of searching for the perfect model, define a version you are willing to run as an experiment for a defined period. Decide in advance how you will evaluate it: win rates, average contract value, sales cycle time, expansion in the first year.
This posture lowers the psychological stakes for the team and makes it easier to adjust. It also creates a clearer story for customers and investors: you are learning your way into the right structure rather than guessing in the dark.