Dynamic Pricing: How to Enhance Your Decision-Making

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Whether you realize it or not, you encounter dynamic pricing nearly every day. From the fluctuating cost of airline tickets to surge pricing on rideshare apps, dynamic pricing permeates our lives. This pricing strategy, which first appeared in the airline industry in the 1980s, is now revolutionizing various sectors, allowing businesses to leverage real-time data to optimize their prices.

With increased data storage and access, more businesses—from concert ticketing to e-commerce giants like Amazon—are using dynamic pricing to maximize profits and stay competitive. This approach can boost revenue and address supply chain challenges to ensure products are priced appropriately to reduce holding costs and avoid stockouts.

Empowering Decision-Makers with Dynamic Pricing Models

The Aimpoint Digital team built a Dynamic Pricing Model in Databricks and made it accessible through Sigma to business users. Our solution provides real-time insights for brand managers and price managers to enable them to make smarter, data-driven decisions. These real-time insights help them to:

  • Determine implications for price increases and decreases
  • Understand seasonality and other demand factors for their SKUs
  • Identify poor performing brands and SKUs

By quantifying price elasticity, key decision-makers can determine customer sensitivity to price changes, ensuring they can set the best prices to maximize profitability and avoid stockouts due to supply chain disruption.  

Walking Through a Dynamic Pricing Model

Many companies have isolated and inflexible data systems, which severely limits their ability to make educated and nimble pricing decisions. However, by combining modern platforms like Databricks and Sigma, they can leverage historical context to predict and understand how dynamic pricing will impact their bottom line.

Let’s assume the role of a pricing manager who notices sales for a product (Product ID=12) have been on a steady decline. They would like to evaluate two discount options and their impact on sales volume forecasts. In our Sigma dashboard, we edited the Discount Design Input Table to compare the effects of a 20% and 50% price discount. For the 20% discount scenario, we see that our volume is forecasted to have a 12% increase.

Dynamic pricing example of sales volumes displayed in Sigma
Ex. Scenario 1, a 20% discount, (note customizable Input Table in red box) results in an estimated 12% sales volume increase

Switching to scenario two, we see that a 50% discount is expected to lead to a 30% increase in sales volume. As a pricing manager, we would weigh the benefits of setting these limits in a dynamic pricing scheme to determine if this is a long-term option for our product and how it aligns with our strategy for high volume vs high margin SKUs.

Dynamic price explore example in Sigma
Ex. Scenario 2, a 50% discount, (note row 2 of Input Table) results in an estimated 30% sales volume increase

How Can Sigma and Databricks Be Integrated to Create Interactive Scenario Modeling?

Using Sigma’s Input Tables, which write back to the underlying Databricks warehouse, our pricing manager can seamlessly interact with powerful models without leaving the platform. We leverage Sigma’s ability to call a UDF within Unity Catalog. This UDF leverages AI_QUERY to access our dynamic pricing model serving endpoint passing through the selected product and our target discount. The model then returns the expected quantity which is passed back to Sigma for availability for calculation and visualization.

This all culminates with an easy-to-use tool for product managers to make informed business decisions without having to write any code or have knowledge of the complex models driving the predictions​.

Logical flow of Sigma and Databricks dynamic pricing solution
Ex. Logical Flow of the solution

Unlocking Your Pricing Potential

As this example demonstrates, Sigma’s Input Tables combined with the power of Databricks makes answering what-if questions accessible to anyone with any level of knowledge. By implementing this setup, your organization can harness the combined power of your data and the valuable expertise of your team, leading to more insightful and agile decision-making.  

At Aimpoint Digital, our experts help you navigate your most complex data challenges to build actionable solutions. We partner with your team to accelerate your strategic vision through data and analytics by rapidly developing, refining, and deploying actionable analytics applications like this one.  

Ready to unlock your data and empower your team with Databricks and Sigma? Sign up for a demo by clicking the “Meet an Expert” button.

Rachel Eaton
Rachel Eaton
Analytics Consultant
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