Incremental Measurement in Marketing

How to Understand the True Impact of Your Marketing Efforts

Incrementality is a key term in the world of digital marketing, focusing on the core goal of measuring the true effectiveness of marketing campaigns. It aims to answer the central question: What is the added value directly generated by a specific marketing effort? This powerful tool enables marketers to distinguish between actions attributed to marketing efforts and those that occurred as a result of them. The objective is to assess how many sales, conversions, or customer actions took place because of the marketing effort that wouldn’t have occurred otherwise.

For marketing managers, understanding incrementality is crucial as it reveals the true impact of each marketing activity. While traditional attribution models give credit to ads based on the final interaction with the customer, incremental measurement focuses on evaluating the real contribution of each campaign. It helps marketers see the full picture of what truly drives conversions and sales, providing more accurate insights into the effectiveness of their investments.

Direct Benefits of Incremental Measurement for Organizations

Whether you’re a B2B or B2C marketing manager, incremental measurement offers significant advantages:

• Improved ROI: By identifying the campaigns and channels that generate real incremental value, you can allocate your budget to the channels that provide the highest return on investment. This helps avoid wasting resources on campaigns that don’t contribute to real growth.
• Deeper Understanding of Customer Behavior: Incremental measurement allows for a better understanding of what motivates your customers to take action. It uncovers which messages, channels, or touchpoints lead to a purchase, helping shape a more targeted strategy.
• Enhanced Decision-Making: With data-driven insights, you can make more informed decisions about your marketing strategy. This enables you to plan campaigns more effectively and focus on generating new demand, rather than simply leveraging existing customer interest.

Attribution vs. Incrementality: Why Attribution Alone Isn’t Enough

In traditional marketing measurement, attribution models have long been the standard for assessing campaign effectiveness. These models attempt to attribute customer actions to the marketing touchpoints they’ve been exposed to, using approaches such as ‘Last Click’ or ‘First Click.’ For example, if a customer saw an ad on Instagram, clicked on it, and purchased a product, the attribution model would give credit to that ad—even if the customer may have already intended to make the purchase due to other ads or influences.

The main issue with these models is their inability to assess the true impact of the campaign. They overlook the most important question: Would the action have occurred without exposure to the ad? In other words, did the campaign create incremental value? Attribution models often focus on the top of the marketing funnel and give credit to the last (Last Click) or first (First Click) marketing touchpoint, ignoring the complexity of the customer journey and the contribution of various channels along the way.

Incrementality works differently. It aims to isolate the direct impact of marketing activity and measure the real value it generates. For instance, let’s say a sporting goods company launches a broad advertising campaign on Facebook and Google. They see an increase in sales attributed to these ads, according to the attribution models of the advertising platforms. However, incremental measurement would seek to discover how much of the sales increase would have happened without the campaign. It’s possible that many customers already intended to make purchases due to factors such as seasonal sales or recommendations from friends. In this case, the credit given to the ads doesn’t reflect their real value.

Practical Implementation of Incrementality: How to Measure and Understand True Value

Understanding the incremental value of campaigns requires the use of advanced measurement approaches. One of the key approaches is Randomized Controlled Trials (RCTs), which allow for isolating the direct impact of the campaign on customer behavior. In an RCT, the target audience is randomly divided into two groups: a test group that is exposed to the campaign and a control group that is not. After a defined period, the results are compared between the groups to determine the incremental effectiveness of the campaign.

For example, a digital fashion company launches an online advertising campaign for a new collection. To measure the incrementality of the campaign, they randomly divide their target audience into two groups: a test group that is exposed to the ads for the new collection and a control group that is not. At the end of the trial, the company finds that the test group made more purchases than the control group. By analyzing the trial results, the company can determine the incremental value of the campaign and understand how many sales were directly driven by it.

Tools and Technologies for Controlled Trials

Many advertising platforms, such as Facebook and Google, offer tools for running controlled trials (A/B Testing) that allow marketers to measure the impact of campaigns on different target audience groups. Advanced tools like Google Optimize or Facebook Lift Studies help conduct controlled trials and analyze the results. There are also external tools like Optimizely and VWO that enable tailored incremental testing.

Case Study: How a Large Retailer Implements Incremental Measurement

This case study illustrates how incremental measurement can influence a marketing strategy. It involves a large retail company in the north offering a wide range of non-food products. The company has an e-commerce site with over 17,000 products in various home-related categories such as kitchen, baking, furniture, textiles, baby care, and more.

The company launched a paid advertising campaign on search engines and social media to promote the variety of products and categories on its site. The target audience included customers who had shown interest in similar products in the past, focusing on users who had visited the site or engaged with the brand via email or social media. According to the attribution models of the advertising platforms, the campaign appeared successful, showing a significant increase in site traffic and sales.

However, the company’s marketing managers wanted to understand whether the campaign actually generated incremental value or if the sales increase would have occurred regardless of the ads. To determine this, they decided to conduct a Randomized Controlled Trial to measure the campaign’s direct impact.

During the trial, the company’s target audience was randomly divided into two groups:

• Test Group: Exposed to the new ads in the search engine and social media advertising campaign.
• Control Group: Not exposed to the ads and continued to experience the company’s standard advertising environment.

After a certain period, the sales results in both groups were analyzed. The results showed an increase in sales in the test group, but there were also similar sales in the control group. The findings revealed that a significant portion of the sales identified in the test group would have occurred even without direct exposure to the campaign ads.

By using this incremental measurement, the company realized that the current campaign did not generate the new value they had hoped for. Instead, it primarily accelerated purchases that would have occurred anyway. Based on this insight, we recommended that the company redirect its budget to other marketing strategies. Our recommendations included: creating content focused on new customers, building brand awareness among new audiences, and developing a unique user experience on the e-commerce site.