Causal Price Optimization

Pricing is all about quantifying how different attributes influence people’s willingness to pay for a product. In real life the true causal influence needs to be rooted out from many competing influences.

Practical problems deal with many variables at once, in a network of causal influences

To keep track of all this, statisticians use causal graphs — diagrams with associations as arrows, and rules on which controls will identify the true causal effect. Our software helps you use the full power of causal graphs, letting you translate your expert knowledge into better estimates, and turn mere correlations into actionable insights.

Promoting best practices in statistical estimation

Our CEO is Amro Nagy, a pricing professional certified by the Professional Pricing Society, with over 22 years of work experience at several multinational corporations including Schneider Electric and ExxonMobil. He has a B.Sc in mechanical engineering, and brings a unique set of skills across various domains, including pricing, channel management, marketing, sales, sales ops, training, CRM, and project management.

Our software

Any statistical estimate relies on assumptions, but most people simply don’t know what they are. Our software ensures that as much as possible of your expert knowledge is accounted for in your prices, and lets you handle far more complex webs of interaction than you could keep track of in your head.

Our software has two stages. First, users choose variables from our data catalogue, and specify which ones are causally related; the software then tells you which variables to control in order to ensure a clear causal path. Second, we use AI to estimate the specific equation that links these variables together.

Interested in a visual method to separate causation from correlation?