We worked alongside an industrial manufacturing client to address their recent decline in market share. The client was aware that this was partly due to their extremely manual and tedious process for determining optimal pricing strategies on a seasonal basis.
The Opex Analytics team carefully sifted through their historical pricing and the resultant market share and profits. We addressed the complex problem of pricing in two parts. First, through extensive model testing, a core set of custom data features were determined to have the best predictive power for each portion of the pricing process. These predictions along with operational constraints and capacity limitations were then used to set each commodity’s optimal price.
Once the model was created, Opex Analytics then built a multi-user platform application providing automated custom pricing recommendations, allocation solutions and an intelligent dashboard. Planners are now more confident in their pricing decisions and leadership has a constant pulse on the state of the competition.
Since working with Opex Analytics, our client:
Talk to us to learn more about how we demystified and automated dynamic pricing.