Welcome to the first installment of our Intro to Incrementality series, where we’ll use real-world examples to explore how to uncover the true impact of your advertising campaigns. By isolating the effect of specific media types or campaign variables, incrementality analysis provides actionable insights into what’s driving performance–and what isn’t.

Warning: this post involves (basic) math.

Isolating the Impact

In today’s crowded media landscape, customers are bombarded with ads across multiple channels—from paid search and display to OTT/CTV and streaming audio. As a result, performance marketing has devolved into a game of attribution, focusing on whether an action occurred after an ad was served. This has largely been driven by platforms like Google and Meta, prioritizing their own attribution models to capture the lion’s share of ad dollars, and by marketers eager to show results.


While attribution can show whether an action occurred after an ad was served, it fails to answer the crucial question: Did this ad actually cause the action, or was it just along for the ride?

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Enter incrementality analysis. By comparing a test group (exposed to a new campaign, publisher, creative, or other variable) with a control group (unexposed), you can measure the true lift in media performance caused by a specific variable and separate correlation from causation.

The Basketball Analogy

Let’s use a non-marketing example to simplify the concept. Imagine an NBA team with two players who each make 40% of their free throws. To improve performance, the team hires a shooting coach to work exclusively with one of the players, Player B. Both Players A and B are told to maintain all other factors, like gym time, diet, and training routines.

2024-25 Season:
Player A: 40% of free throws ┃ Player B: 40% of free throws

After the 2024-25 season, Player B’s free throw percentage improves to 80%, while Player A’s performance naturally rises to 50%. Both players improved, but Player B improved more. So, how do we measure the shooting coach’s impact?

2025-26 Season:
Player A (control): 50% of free throws ┃ Player B with Coach (test): 80% of free throws

We calculate two metrics to measure the impact:

1. Incremental Lift: After introducing the shooting coach, how much more likely is Player B to make a foul shot?

Formula:

(test: 80% – holdout: 50%) / holdout: 50%
The result is 60%

A 60% lift means Player B was 1.6 times more likely to make a free throw after working with the shooting coach.

60% more likely to make a free throw

2. Incrementality: What percentage of Player B’s improvement is attributable to the shooting coach.

Formula:

(test: 80% – holdout: 50%) / test: 80%
This result is 37.5%

Incrementality reveals that 37.5% of Player B’s improved free throw performance is directly due to the new coach, while the remaining improvement stems from other factors. 

Backing it Back to Marketing

Now, let’s apply this concept to advertising. Imagine a brand running search and social media campaigns, both yielding a conversion rate of 0.1%. The brand has a hypothesis: Adding OTT/CTV advertising to its media mix will increase the conversion rate.


To test this, the brand introduces OTT/CTV ads to one audience subset (test group) while keeping the other subset as a control (search and social). At the end of the campaign:

Using incrementality analysis, we can calculate:

  1. Incremental Lift: 

(test: .2% – control: .15%) / control: .15% = 33.33% (1.33x)

  1. Incrementality:

(test: .2% – holdout: .15%) / test: .2% = 25%

This means OTT/CTV ads made the test group 33.33% (1.33x) more likely to convert and were directly responsible for 25% of conversions.

Incrementality analysis allows marketers to isolate and quantify the impact of specific campaign variables, leading to smarter decisions about budget allocation and media strategy. Instead of just tracking performance, you can:

Looking Ahead

By measuring the true impact of advertising, incrementality analysis helps brands and agencies focus their budgets on the campaigns and publishers that matter most. In the next part of our series, we’ll discuss how to create effective control groups for accurate incrementality analysis. Can’t wait? Speak to a member of our team today.

CTV viewership has exploded. To take advantage of the channel’s surging audience, e-commerce and retail brands are making CTV a key part of their advertising strategy. CTV allows brands to apply an audience-first, data-driven approach to TV similar to other digital channels. However, as ad strategies continue to become more CTV-reliant, brands need greater clarity on performance and ROI. Our proprietary performance CTV platform, Flip, provides that clarity to e-commerce and retail advertisers.

Tying CTV ad impressions to app installs, site traffic, in-store visits, cart amounts, and more

Flip connects mobile location data with CTV ad impressions to help brands granularly understand campaign performance, attribution, and Return on Ad Spend (ROAS). Flip helps advertisers and agencies accurately and granularly measure CTV campaign effectiveness. The platform provides an easy-to-use dashboard that shows CTV buyers exactly which campaigns are working across which devices, publishers, demographics, and more – all in real time. Using proprietary software, Flip can tie ad impressions to app installs, cart amounts, and site visits. The platform can even match a CTV impression to an in-store visit when that device shows up in a physical store, uniquely tying digital impressions to physical actions. With its full-funnel attribution capabilities, Flip traces every CTV impression to a conversion and sheds light on ROAS as CTV investments grow.

“With Flip, we’re able to connect real-world sales events to CTV impressions to let retailers know, definitively, that someone was exposed to their CTV ad, and then visited their site or made a purchase. We’ve set our sights on elevating CTV to a fully accountable performance media channel — driving real-world results for our clients by allowing them to activate against their data or third-party data to maximize return on ad spend. Flip has answered the call for a new benchmark for measuring campaign success, even on platforms that don’t have a lot of transparent reporting, and we’re thrilled to extend it to e-commerce and retail brands.”

Head of Activation at Agency Partner

Flip is the cornerstone of our full CTV/OTT offering, helping digital ad buyers optimize targeting, tracking, and campaign management across multiple platforms and devices. Now, e-commerce and retail clients can leverage and unlock real-time insights, measure the true impact of campaigns and optimize to drive results. With Flip, e-commerce and retail marketers can:

“As the industry aims to keep pace with consumer demand for personalized experiences in an economic environment where every dollar counts, measurement and performance have become critical metrics for retail advertisers. We’re ecstatic to extend Flip’s capabilities in the retail and e-commerce sector and remain committed to providing a holistic solution by which advertisers can unlock and optimize real-time insights, measure campaign effectiveness, and drive valuable results.”

– Matt Sotebeer, Chief Strategy Officer at Digital Remedy

To learn more about Flip, visit www.digitalremedy.com/flip or speak to one of our team members to book a demo and see the platform in action.