Price Optimization
Humans are pretty bad at determining how much something should cost. Make better, more scientific pricing decisions with historical data and other factors.
Set prices that balance demand, profit and risk
Sometimes, it all seems to be about price. But it’s not as simple as that, and even pricing itself is a complex practice. Low prices risk negative margin impact. High prices might scare away buyers. And then there are competitive pressures, geographical and market variations, and ever-changing cost of inputs that need to be factored in. Data science can make pricing easier, more scientific, and less subjective or even whimsical – taking into consideration all possible factors and historical data.
Consider all factors
Set prices optimized for all possible influences – competitors, suppliers, consumer preferences, risks. Leverage all available data for better pricing decisions.
Price anything
There’s no limit to what can be priced scientifically. From manufactured goods to those on the retail shelf to hospitality to professional services, make any price more impactful.
Make dynamic pricing a reality
Make one-price-fits-all a thing of the past. Employ pricing models that change dynamically throughout the day, or for each individual customer.
Separate prices for each market
No more glossing over regional or customer segment differences. Create pricing that satisfies each specific customer group and yields the best profit margin.
Learn more about price optimization including how customers react to different pricing, the four key prices to determine, and how machine learning can help.
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