- If you're wondering how to measure the effectiveness of a digital marketing campaign, the honest answer is that digital marketing can be difficult to measure. But why is this?
- Users may have interacted with numerous third-party ad platforms within the 30-day "cookie window," but only made one transaction on the brand's website.
- There are different attribution models that can help you strategise your digital marketing and calculate as "close to right" as possible.
- Read on to learn how to measure your digital marketing activities as accurately as possible.
Retail magnate John Wanamaker is famous for the quote: “Half the money I spend on advertising is wasted; the trouble is I don't know which half.” This statement is just as relevant for marketers today as it was at the turn of the century. For as long as marketing has been around, marketers have debated how best to measure success, and even with the rise of supposedly "measurable" digital marketing, building a meaningful attribution model is not easy to do.
Measuring digital marketing is "impossible"
Why is this?
In basic terms, when a user interacts with a brand's digital ads, a small piece of data known as a tracking cookie is used by the third party ad platform (such as Facebook, Google, etc.) to identify that particular user. The user's unique tracking cookie will continue to identify them for around 30 days. If the user proceeds to make a purchase on the brand's website, that purchase will then be attributed to the third party ad platforms that the user interacted with before purchasing.
Where it gets tricky is that the user may have interacted with numerous third-party ad platforms within the 30-day "cookie window," but only made one transaction on the brand's website. If you were to add the total value of all transactions together (as reported by the ad platforms), there would be a discrepancy with the reporting and the brand’s bottom line.
And here’s where attribution modelling comes in.
A marketer will need to determine what percentage of that transaction should be attributed to each ad platform that the user interacted with during the conversion path. For example, if the user clicked on a Facebook ad, then later that day they clicked on a Google ad and finally made a purchase, the value of that purchase would need to be attributed to both Facebook and Google. If Google was the ‘"last click," a marketer might prefer to weight the value of Google at 60%, and Facebook at 40% (rather than a straight 50/50 split).
But what if the user intended to make a purchase all along and they simply clicked on both the Facebook and Google ads as a means of accessing the site (rather than going direct)? If that were the case, did the marketer overspend on their advertising?
John Wanamaker was right.
There are plenty of off-the-shelf attribution models available, but many are costly. Try Adtriba for a more affordable option. Google offers a free version and Facebook is also in the early stages of trialing a new free tool. A new "people-based" attribution model has also come to light, moving away from cookies to combining and de-duping data across several measurement platforms to find a more accurate representation of a user. Theoretically, this could solve many problems, namely accurate cross-device reporting that would allow marketers to gain real insight into the performance of channels and thus be able to adjust spending accordingly.
However, even with the advancements in attribution modelling, marketers will still struggle to gain a complete picture of how their digital marketing is performing, particularly when offline activity is occurring simultaneously.
For instance, a marketer sees an uplift in brand search clicks in a month where offline activity was in play. Obviously, the marketer would attribute some of the brand search uplift to the offline advertising, but the data is still vague.
Even the very best attribution models are flawed; however, thinking about attribution is vital if you want to gain a clearer picture of the customer journey. If you get it close to right, attribution modelling will mean you can spend less on marketing whilst scoring more conversions.
Getting it close to right
How do you get it "close to right"? Accept that it’s not an exact science and that there will be cross-over with the reporting, then decide how much weighting you want to give to each channel and apply the maths. A "last click" report can be found in Google Analytics (under Acquisition > Channels - providing you’ve tagged your ads with a Google Tracking Code). Or you can use the Assisted Conversions report (also in Google Analytics) to help you determine which transactions were "assisted" by more than one channel, then apply a percentage weighting to each channel based on your "best guess". Another way to ascertain the true value of each channel is to simply switch them off for a period of time and see what happens to your sales!
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