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  • MaryGrace Lerin

How to Improve Ad Measurement Through Incrementality Testing and Experiments

Advertising attribution has long been a difficult route for marketers to traverse, yet recent events have triggered a fundamental shift in media measurement, which must be handled promptly before things spiral out of control.

Apple and Google's policy changes might have made an impact on advertising measurement's decline, yet social media platforms have also often reported campaign results using inaccurate last-touch attribution.

Platforms overlooked the notion that some of such activities would have occurred eventually through tracking every conversion an ad was in the path of.

Prior to iOS 14.5 and ATT, incrementality testing frequently revealed that many platforms have reported conversions much more than the actual data, but this was usually overlooked because last-touch analytics made them appear excellent. Depending on the audience type, for instance, prospecting (mild) vs. retargeting (heavy), the quantity of additional credit can differ greatly. Advertisers were probably oblivious of the mistakes or had chosen to ignore them since it enhanced their own image.

However, as data privacy regulations tighten, social media platforms are losing the capacity to track conversions for a large portion of their users, prompting them to underreport conversions using the same faulty last-touch measurement mechanism.

Several companies are seeking to address the loss of visibility through ID substitutes or redesigned attribution models, but these options, which are plagued by ineffectiveness and privacy problems, might take years to implement. Yet advertisers need such help right now.

Although their own measurement techniques can't establish the efficacy of ad campaigns on social media sites, incremental testing can. As such, it will remain at present an efficient tool for advertisers to use, whatever the future of cookies may look like.

As incrementality measurement is built on first-party data and cohort-based analytics, it is unhindered by future policy changes since it does not necessitate user-level tracking to deliver valid findings. Incrementality testing can give continuous data at a tactical level, devoid of platform bias and grounded on established experiment methodology, therefore advertisers may continue to transfer funds to where they have the biggest economic effect.

Over a hundred direct-to-consumer brands allocate a portion of their media spend to Facebook.

Some advertisers use incrementality testing to give grounds for continuing or increasing their Facebook expenditure, knowing that their ads are doing better than Facebook attribution would suggest. Luxury brand Shinola recently discovered in their incrementality testing that Facebook was underreporting prospecting campaign results by 413 percent.

Other businesses are employing incrementality experiments to evaluate and expand through new channels like TikTok, Snap, Pinterest, and CTV in order to shift away from continually rising Facebook ad expenditures.

Marketers may invest a tiny portion of their budget on incrementality and location testing to see if expanding into new channels would be worth their while.

Actions and decisions from companies such as Apple, Google, and others may and do have a substantial influence on the media industry, including all businesses operating inside it, yet regarding the platform attribution, they have merely revealed a faulty system of self-reporting that shouldn't have been allowed to begin with.

Incrementality testing and experimentation can bring an end to the long-standing efforts of both platforms and marketers to establish a standard advertising measurement strategy that is relevant, long-lasting, and satisfactory to all concerned parties.

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