Incrementality & Attribution
In past installments of our Incrementality Explainer series, we have gone in-depth on both incrementality testing and common attribution approaches. This week we look at one of the other most important questions on the minds of marketers - how do incrementality and attribution work together?
The fact of the matter is that best-in-class marketing organizations are using incrementality and attribution together to drive outcomes that matter. Incrementality testing is not only complementary to marketing attribution, it’s becoming a necessity for every marketer and the success of their brand.
Why is Incrementality Testing Important?
This past March, an in-depth Harvard Business Review article hailed marketing mix modeling (MMM) and incrementality testing, referred to as ‘experimental calibration’, as the gold standard for ad measurement in a post-iOS 14.5 world:
“As privacy advances fundamentally change the digital ad measurement landscape, we recommend embracing MMM as a key part of the marketing analytics toolbox…if you rely heavily on online advertising, regularly calibrate your MMM using ad experiments to make sure your measurements are accurate and your digital marketing decisions are well-informed.”
There’s a consensus, and it’s simple - if you aren’t validating, calibrating and enhancing your attribution models with frequent incrementality testing, you do not have a best-in-class marketing analytics practice.
The Pros and Cons of Incrementality Testing and Attribution
Incrementality testing and attribution have different strengths and weaknesses.
- Incrementality testing gives you a causal read on the impact of your marketing.
Tests offer a point-in-time snapshot of how a media channel or tactic is driving incremental sales for your business. They also provide fast insight into how changes in business, marketing, or environmental factors are impacting your media effectiveness in a matter of just weeks.
- Attribution models provide always-on measurement across most or all of your media channels but use correlation rather than causation to determine the impact of your marketing. They’re also typically slow to adapt to business change since they’re built on months or years of data.
It’s exactly these complementary strengths and weaknesses that make it so important that your marketing analytics practice incorporates both to be successful.
The Key to Marketing Success
In short, you should be running regular incrementality tests across all of your key marketing tactics and using the results of those tests to calibrate, update, and enhance your attribution model. Marketers need the combination of incrementality testing and attribution to work closely together to stay on top of today’s rapidly changing environment.
Schedule a demo today to see how incrementality testing can help your brand.
Interested in learning more? Follow our ongoing Incrementality Explainer series for weekly insights.