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If you advertise shoes on Facebook and 100 people buy them while the ad is running, is your advertising working?
The answer, of course, depends. It depends on how much you spent on advertising versus the revenue generated from those purchases. It depends on factors like other ads on other channels, email marketing, or word of mouth that may have influenced shoppers’ decisions. And most importantly, it also depends on how many sales would have occurred if you didn’t advertise the shoes at all.
Marketers often overlook this “gold standard” metric of incrementality — the only way of measuring true net-new revenue generated from advertising.
Incrementality is commonly ignored because it’s always been difficult to measure and optimize. Instead, marketers turn to attribution models that try to paint an accurate picture of how online advertising truly pays off.
Unfortunately, they all fall short in multifaceted campaigns.
When you take a closer look at the most common attribution models used in digital advertising today, it’s easy to see how they don’t measure up.
Last click attribution
Since the advent of online advertising, the industry has settled on last click attribution as a default metric.
As many have pointed out, last click (or last touch) attribution is like awarding the win to the baseball team that scored last, regardless of how many runs each team racked up throughout the game. In advertising, a consumer may have seen 15 ads, but 100% of the credit goes to the last one she clicked.
The alternative to last click is multi-touch attribution, which awards a value to each ad a consumer sees along the purchase journey. For example, a billboard might get 10% of the credit, a Facebook ad gets 40%, and the rest may be divided across search, display, email, direct mail and an endless number of organic influences.
It’s an imperfect measurement, of course. Collecting the depth of data required to measure every factor (paid and organic) impacting a consumer’s buying decision is an insurmountable task in the real world. No model will tell you exactly how much that billboard contributed to an eventual purchase. So even with the best tools, multi-touch will never be a true measurement of a single ad’s influence.
Marketers who are trying to build complex attribution models to better understand their true ROI are fighting the wrong battle. Last click attribution is easily managed, but fundamentally flawed. Multi-touch attribution is a marketer’s dream, but it’s impossible to fully implement in reality.
"Trying to pinpoint attribution for every single conversion is a waste of effort because if you can prove that an ad generated net-new revenue for your company, then nothing else matters."
The end goal of performance advertising should always be to drive incremental (net-new) revenue. But neither last click nor multi-touch attribution can tell you anything about incrementality.
Focusing on incrementality instead of attribution sidesteps the challenges of trying to connect all the dots in a complex consumer journey. Trying to pinpoint attribution for every single conversion is a waste of effort because if you can prove that an ad generated net-new revenue for your company, then nothing else matters.
Measuring incrementality can also reveal how much you’re wasting on ads that don’t contribute to your bottom line growth.
For instance, say that Consumer A and Consumer B are both in the market for a new laptop. Both have searched online and maybe even asked others on social media for recommendations. After a week goes by, Consumer A buys her laptop without ever seeing an ad for the model or brand. Consumer B buys the same laptop too, but she did see an ad. When you compare many Consumer A’s to many Consumer B’s, it becomes clear just how many additional laptops were sold as a result of advertising.
Of course, this isn’t a new idea in marketing. If you’re running an out-of-home campaign, how do you know if it’s working? Since no one can click through a billboard or a TV ad, the best gauge is to look at a similar city that didn’t run an out-of-home campaign. But in digital, we’re spoiled with too much available data and too many proxy metrics. CPAs (cost per acquisition) or purchase rates may seem like a strong indication of efficacy, but they can just as easily be misleading.
The upside is that digital media does let you change course when an ad campaign is performing well. So if one ad seems to be converting more Consumer B’s than usual, you can allocate a greater share of ad spend to reaching more people like Consumer B who will generate higher incremental returns.
Marketers are often faced with an age-old challenge: “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” Incrementality can finally show you which half is working and which half is wasted so you can grow revenue faster, more efficiently and more profitably than ever.
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