Scalable price optimization:
Precise pricing for a large number of products
Retailers and many consumer goods manufacturers have to manage hundreds or thousands of prices. Established price measurement methods such as conjoint are too expensive on this scale. Simple methods such as Van-Westendorp or Garbor-Granger produce rationally biased results.
In an online survey of potential customers, Price.AI uses an “implicit” survey method to measure unconscious willingness to pay. This is the scientifically established way to reveal unconscious associations. We apply this to the price range to be tested. 100 seconds and 100 respondents per product later, our algorithm calculates a multiple validated price-demand function and the profit-maximizing price range. The algorithm is calibrated with real sales data and can be further optimized for any specific sales context. This gives you unprecedented pricing precision.
Secure profit increases through a scalable pricing methodology – particularly interesting for a large number of products.