Why the Right Measurement Matters Part Three: The Real-World Benefits of Optimizing Lift

This is the last in our three-part series exploring modern measurement and the ways in which marketers can achieve better outcomes from their advertising by moving away from outdated, proxy metrics. Now that we are (hopefully!) in agreement that lift measurement is the most appropriate methodology to evaluate the success of most kinds of campaigns, let’s take a look at some real-world success stories.

Consider the case of a digital solutions company that helps businesses establish and maintain their online presence. Targeting small business owners and entrepreneurs, they sought to drive more signups for their product suite. Using Ghost Bids to measure lift, this marketer was able to achieve and demonstrate a 66% increase in signup rate. In contrast to CPA, which generally measures unit cost in a vacuum, lift demonstrates the effect of media exposure on conversion rate above that which was seen in the control group.

Therefore, unlike most other methodologies, lift is able to definitively isolate the impact of media exposure. 

What’s especially interesting about this example is that the ads were run entirely on audio channels. Moreover, leveraging a device graph, the marketer was able to deduplicate users across devices, to help prevent contamination of the control group. This improved study accuracy and provided a high degree of confidence in the study results.

Another example is that of a genetic testing company that wanted to drive traffic to their landing page. Executing across multiple channels and leveraging audience targeting, the marketer learned that they were able to achieve a 30% increase in site visits, and that the combination of channels produced better results than any single channel alone. Additionally, they learned that showing a user 10 impressions maximized their lift rate.

Which brings up an important point: you’ll generally find that optimizing to lift requires more ad exposures per user. Without a doubt, this will increase your CPA (i.e., because you’re serving more impressions to each user who converts.) This is not a bad thing! A single media exposure can’t be expected to cause a user to convert - historical studies show that between 5-20 impressions per user are needed to drive an incremental conversion. Inversely, optimizing to CPA favors fewer impressions, because media is taking attribution credit for users who would have converted regardless.

Optimizing to, and using CPA as your sole measure provides at best an incomplete picture of your advertising effectiveness, and at worst, produces outcomes that are contrary to your business goals. 

Moving to lift-based measurement and optimization requires a significant change in how marketers think about what “good” looks like. It’s easy to get caught up in focusing on how much money it takes to generate a desired consumer action. While that may sound like an intuitive way to measure advertising effectiveness, it’s the wrong metric because it doesn’t look at the true impact on actual business performance resulting from marketing. 

Within the lift measurement realm, there are many different approaches, each of them valid and with their own pros and cons. Consider which of them is most applicable to your use case; then, test and learn. Recall from our first post in the series that incrementality tells you much more than CPA: it helps marketers understand how many conversions took place as a direct result of their advertising -- not those that would have happened regardless. Optimizing to incremental lift, while a sea change at first, will be something that you wish you had done sooner.

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