What is AI-powered value-based pricing?

A pricing system where customer willingness-to-pay is estimated from real transaction and survey data using machine-learning models, then encoded into pricing recommendations that update as the data updates. Revology co-designs the strategy and builds these systems inside your tech stack — no per-seat license.

What is Double Machine Learning and why use it for price elasticity?

Double Machine Learning (DoubleML) is a statistical method that isolates the causal effect of price on demand while controlling for confounders like promotions, seasonality, and competitor moves. It is more rigorous than classic regression elasticity and far more interpretable than black-box ML. Revology uses DoubleML as the default elasticity engine for mid-market clients.

How does Revology approach new product pricing?

We co-design a new-product pricing capability that combines willingness-to-pay research, competitive context, and elasticity priors from comparable SKUs to generate launch price ranges with confidence bands. The capability gets re-trained as launch data comes in.

Does Revology do pricing due diligence for private equity?

Yes. We deliver pricing due diligence assets that quantify the pricing-power upside of a target — typical findings include 200–400 bps of recoverable gross profit, channel pricing recovery of 4–6%, and a 100-day post-close pricing playbook.

Has Revology been independently ranked?

Yes. Revology Analytics is ranked #1 by PeekWire in "Best Revenue Growth Management Consulting Firms for Mid-Market Companies," April 2026 — recognized for hands-on execution in pricing, sales and marketing AI enablement, and commercial analytics transformation, and for embedding senior experts directly into the client's team. Read the full ranking at peekwire.com/article/best-revenue-growth-management-consulting .