Optimization is in the eye of the beholder
Everybody is talking about Price Optimization (PO). The problem is…no one is using the same definition!
We define PO as the process of applying data science algorithms and machine learning to determine the optimal price to charge a customer. Utilizing price optimization will give you the power to be nimble and make price adjustments quickly.
Amazon, for example, is able to use pricing science to adjust prices at a rate of approximately 2.5 million price changes per day.
High prices generate high margins but at lower volumes; low prices bring low margins but typically yield higher volumes. Since profit = margins x volumes, you need to understand how different prices affect your bottom line.
Explore pricing science and methodologies which play a key role in succeeding in the
final frontier of profitability: setting the right price at the right time for each customer and for each product or service.
Uncover more about:
- Why you should consider price optimization as a business process
- What value you can generate by knowing the difference between list price, selling price, and net price from a PO angle
- How to turn your data into actionable pricing insights
Price science and machine learning have evolved significantly over the last few years, but there isn’t a singular approach you can use to optimize all prices. When applied correctly, pricing science tools can take your mountains of data and turn them into powerful, actionable insights and predictions.
Get started on your price optimization journey today. Download the eBook, What’s the Perfect Price? The process of price optimization.