Embrace Science And Big Data: The Attribution Revolution
Recently, the topic of attribution has been taking some heat, as agencies and clients try to determine the best way to assign value to various advertising channels. While some are more willing to accept different models than others, all marketers must embrace this movement immediately. I’m going to focus here only on digital media — […]
Recently, the topic of attribution has been taking some heat, as agencies and clients try to determine the best way to assign value to various advertising channels. While some are more willing to accept different models than others, all marketers must embrace this movement immediately.
I’m going to focus here only on digital media — which, as we will see, is hard enough. Figuring out an attribution model that works across all media is the real nirvana.
Given that an advertiser knows if you see their ad, click on it, visit their site, and buy their product, you’d think that measuring the effectiveness would be a snap — just take the amount spent on each media channel and divide it by the number of units sold.
However, companies are spreading their online advertising dollars across various channels like wildfire. This includes leveraging strategies like search engine marketing, search retargeting, site retargeting, contextual targeting, branding/awareness campaigns on premium sites, etc. Given that people see ads from multiple campaigns before they make a purchase, figuring out which one drove them to a purchase is much more complicated.
Below are explanations as to why the current attribution models are falling short.
1. Post-click or last touch attribution: This model is based on the idea that the last channel to persuade someone to click on an ad gets credit for the entire sale. It seems the most logical because why should others get credit if they weren’t able to generate a sale after the click?
However, there is no consideration given to the channel that influenced the consumer in the beginning, or any time other than the last click. Post-click attribution has effectively been killed by the rise of site retargeting (the ability to know who has visited your site and then target ads based on what they saw on the site). Site retargeting generates fantastic results — especially when post-click attribution is being used. To illustrate why, consider the following analogy:
A consumer watches a TV ad about a promotion at Best Buy and then visits the Best Buy store. In the store, they are handed a flyer about the discount. The consumer goes to the cashier with the discount flyer and then makes a purchase. If the retailer were using last touch attribution, then the conversion is attributed in full to the flyer — not the TV ad that actually brought the consumer to the store in the first place.
The way to prove this exists in the online world is surprisingly easy. If you are running a site retargeting campaign, simply cancel all other media and traffic. Obviously, clicks and purchases will decline. However, there will also be a decline in the click through rate (CTR) of the site retargeting campaign, which proves that someone other than the site retargeting campaign is making the campaign perform better and thus should be getting the credit for purchases.
2. Post-view attribution: This model is based on the idea that the last channel to show a person an ad is the channel that receives credit for it. This model is even more inaccurate than the post-click model mentioned above because it encourages media partners to plaster ads as widespread as possible in order to take credit for the conversion, even if a consumer doesn’t actually see an ad. This will still count as an impression and the media partner, typically the one with the largest reach, obtains credit for it.
An example of this model is AOL Instant Messenger (AIM) ads. AIM is typically open on a consumer’s computer screen, so ads are constantly being shown whether or not you’re looking at the AIM screen at that moment. Even when the consumer is on a retail site making a purchase, AIM can be showing the ad and thereby getting credit for the conversion.
3. Having no model at all: In this common model, all of the media channels show their campaign contributing to the purchase, which then results in claims that several hundred percent more goods were sold than in reality.
So, what’s the answer? Science. Attribution is not an art or a guessing game. It’s complicated, it’s a big data problem, and there are companies that specialize in this. Adometry and C3 Metrics are two of my personal favorites.
Some ad agencies have even developed their own tools. The goal of these companies is to provide marketers with a complete picture of consumer touch points and assign weighted values for various levels of engagement throughout the conversion process.
The demand for digital advertising effectiveness will not die down anytime soon. Pressure will continue to rise from two sides. First, major companies/advertisers such as Coke and P&G will push for new attribution models as they shift more dollars to digital. Second, ad technology companies and publishers will advocate for more accurate attribution, as they don’t want to miss out the credit they might deserve.
And this is just the beginning because lack of effective measurement and attribution is the number one reason brands indicate they are limiting their digital advertising spend. It’s time to embrace the attribution revolution.
Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.
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