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 in our price optimization glossary page.

Get started on your price optimization project today!

View Other Use Cases

Churn Prevention

Identify customers likely to leave, take preventative action.

Customer Lifetime Value

Distinguish between customers based on business value.

Customer Segmentation

Create meaningful customer groups for more relevant interactions.

Demand Forecasting

Know what volumes to expect to improve planning.

Fraud Detection

Identify fraudulent activity quickly, and end it.

Next Best Action

The right action at the right time for the right customer.

Predictive Maintenance

Predict equipment failure, plan cost-effective maintenance.

Product Propensity

Predict what your customers will buy, before even they know it.

Quality Assurance

Resolve quality issues before they become a problem.

Risk Management

Understand risk to manage it.

Text Mining

Extract insight from unstructured content.

Up- and Cross-Selling

Convince customers to buy more.