Why is it essential to understand the business impact of Price changes and Promotional investments, and what are the analytical approaches to estimating Price elasticities?

With the continued customer, transactional, and 3rd party data proliferation and the democratization of popular Machine Learning methods, knowing your Price and Promotional elasticities at the Customer-Product level is fundamental to finance, sales, and revenue management.

How many of us have been in situations where:

1. We are giving away too many promotions and discounts to customers.

2. Our pricing strategy is to index to competitor prices.

3. Our price investments (promotions, discounts, rebates) are growing faster than our Operating Profits.

4. Margins and Net Revenue are substantially lower than they could be.

Knowing our Customer and Product level Price Elasticities are critical enablers, allowing us to:

1. Increase Price Realization and Promotional ROI

2. Minimize Pricing Risk

3. Optimize our Inventory and Liquidity

4. Drive Net Sales and Gross Profits

5. Set the Foundations for more robust Price Optimization

In this webinar, geared towards the Pricing and Analytics/Data Science practitioner, we'll go through a Manufacturer case study in modeling Price Elasticities using two methods - one that employs Linear Regression and another using Machine Learning.

We'll discuss the pros/cons of each method and give specific guidance on how to build more robust Price Elasticity models for your organizations.

Attendees will receive a copy of my Miro board with a complete blueprint and outline and the accompanying R code they can leverage in their organizations in just a day.s here