Sales promotions are a critical tool for businesses to attract new customers, retain existing ones, and drive revenue. However, not all promotions are created equal, and understanding their impact on your business is key to making informed decisions. In this blog, we'll explore different types of promotions, the importance of measuring the true return on investment (ROI) from these promotions, and why using a method like difference-in-differences (DiD) regression is more reliable than simple before-and-after comparisons.

Different Types of Promotions

Sales promotions come in various forms, each with its unique purpose and impact on consumer behavior. Here are a few common types:

- Discounts: Offering products or services at a reduced price.

- Buy One Get One Free (BOGO): Encourages customers to buy more by offering a free product with the purchase of another.

- Coupons: Provides customers with a code or voucher to receive a discount on a future purchase.

- Loyalty Programs: Rewarding repeat customers with points, discounts, or free products.

- Flash Sales: Limited-time offers that create urgency and drive quick sales.

Why Measuring True ROI is Crucial

Understanding the true ROI of your promotions is essential for maintaining the financial health of your business. It's easy to get caught up in the excitement of increased sales during a promotion, but without a clear understanding of the actual return, you could be spending more than you're making.

Accurate ROI measurement helps you identify which promotions are truly beneficial and which ones are draining resources. This understanding allows you to allocate your marketing budget more effectively and make data-driven decisions that support long-term growth.

Why Simple Before-and-After Comparisons Aren’t Enough

Many  businesses make the mistake of measuring the success of a promotion by simply comparing sales before and after the promotion. While this approach might seem straightforward, it fails to account for other factors that could influence sales, such as seasonal trends or external events.

This is where a method like difference-in-differences (DiD) regression comes in. DiD helps isolate the true impact of the promotion by comparing the difference in sales before and after the promotion between a group that received the promotion and a group that didn’t.

Understanding Difference-in-Differences Regression

Let's break down the concept of DiD regression into three levels:

Level 1: The Basics

At its core, DiD regression compares the change in sales over time between two groups: one that experienced the promotion (treatment group) and one that did not (control group). By looking at the difference in these changes, we can estimate the true impact of the promotion. Below is a very simple example of this concept, but in reality it can often get more complex.

Level 2: Adding Some Context

To make this comparison meaningful, we need to ensure that the treatment and control groups are similar in every way except for the promotion. This helps us rule out other factors that might influence sales, like economic conditions or competitor actions. This can either be done be picking a "twin" from the control group for every person in the treatment group based on key attributes, and then getting rid of individuals who do not have a close match. There is another alternative to the "matching" approach that we will cover in level 3.

Level 3: The Full Regression Model

In a full difference-in-difference regression model, we use statistical techniques to control for various factors that might affect sales. This involves using a regression equation that includes variables for time, group, and the interaction between time and group, which represents the impact of the promotion.

While this might sound complex, the key takeaway is that this method allows us to isolate the true effect of the promotion, giving us a clearer picture of its success.

Conclusion

Sales promotions can be powerful tools for driving business growth, but only if you understand their true impact. By using advanced methods like difference-in-differences regression, you can get a more accurate picture of what’s working and what’s not. This knowledge allows you to make smarter decisions, ensuring that your promotions contribute positively to your business's bottom line.