As cross-channel measurement becomes increasingly complex, brands are leveraging incrementality to understand true value and hone their ad strategies.
American-Swedish fashion retailer Gant operates nearly 4,000 stores in 81 countries and has a complex multichannel ad strategy that spans the full customer journey. Last March, the brand wanted to gain a better understanding of the relative performance of two crucial channels: Facebook and paid search. So, over the course of three weeks, it ran cross-publisher conversion lift tests in the UK to establish the efficiency of each platform.
The results were both clear and fascinating: Compared with paid search, Facebook ads delivered a 1.8 times lower cost per incremental order, 2.8 times lower cost per incremental add-to-cart and 2.2 times lower cost per incremental traffic. Armed with this data, Gant was able to evaluate the precise contribution of each platform and better allocate its media spend.
Key to gaining these insights was taking an experiment-based measurement approach anchored in incrementality—the business value generated as a direct result of a marketing campaign or media exposure. As marketing strategies become more multifaceted and as the ads ecosystem evolves to meet people’s expectations of privacy, incrementality-based measurement helps ensure every ad dollar is going as far as it can go by revealing the true value of each marketing activity.
Understanding incrementality through experimentation can deliver significantly more accurate cross-channel measurement. For example, Meta’s Marketing Science team found last-click attribution—when credit for a conversion is given to the last touchpoint—undervalued ads on Facebook by 47% when compared with incrementality-based lift studies for campaigns in a wide range of verticals.1
As with Gant, UK-based online retailer JD Williams found incrementality-based experiments enabled it to compare the true value of different platforms—Facebook versus paid search—and hone its cross-channel ad strategy. Last March, it ran a cross-publisher conversion lift study and found Facebook was 2.5 times more cost efficient in driving incremental orders and 3.5 times more cost efficient in converting new customers compared with paid search.
In addition, the brand saw that when Facebook and paid search were used together, they worked better. Ads on Facebook drove a 26 percentage points higher lift in incremental new customers when paid search ads ran at the same time.
Through incrementality-based measurement, JD Williams was able to not only understand the value of Facebook and paid search individually, but also see the different roles they played and how they could be used together to help drive stronger business results.
The results of the GeoLift helped us to quantify the effect of our digital efforts in our physical points of sale. This large-scale analysis allowed us to execute our budget intelligently in order to continue strengthening our brand with an omnichannel vision. Irmin Gonzalez Veruete, Digital Marketing Manager at Liverpool
For Mexican department chain Liverpool, a key challenge was to understand how its campaigns on Meta’s platforms and on paid search affected sales not only online but also in its physical stores. To do this, the retailer built a cross-publisher test design using GeoLift—a Meta Open Source solution that enables advertisers to measure incremental impact from advertising using geographical holdouts—to measure and compare incremental impact from two media channels at the same time. The test ran from July to August 2021 and showed that Meta ads drove 42% higher lift compared with paid search and that both platforms helped spur omnichannel sales.
Ultimately, because of the breadth and complexity of today’s advertising ecosystem, the most effective cross-channel marketing strategy will be different for every advertiser. Moreover, as people’s expectations and behaviors change, so will relative channel performance. That’s why anchoring measurement in true value and incremental impact is essential. By making incrementality the north star—and by constantly testing, learning and calibrating—advertisers can continually determine the right channel mix and find the most efficient budget allocation across platforms.
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