Algorithmic SaaS pricing and measuring value

company.com/pricing

Virtually all products have a /pricing page.

Pricing rules of thumb

YC Partner Kevin Hale advises early stage companies to set their prices according to the value perceived by early adopters—users who are not price sensitive—and for whom "value-based" pricing is the most effective strategy:

1. Start with the customers perceived value (aim for a 10x perceived return)
2. Increase your pricing by 5% and observe the effect
3. See which price earned the most sales revenue (the remaining prices form tiers)
4. Price and customer acquisition are positively correlated (low price, affords low sales and marketing spend)—adjust both to achieve a fixed revenue target.

But.... heuristics don't always work

The problem with pricing heuristics, or "rules of thumb" is that they simplify dynamic and non-linear interactions. In the example above, the causal relationship between perceived value and subsequent pricing adjustments may not be simple. How does company growth and competition influence prices beyond the focus on early adopters?

A simpler problem might be how to set an initial price, even if value-based.

/pricing — learn to predict it!

Why not build a prediction model with data on pricing of other SaaS markets, features and tiered/discounted pricing?