Attribution (modelling) is a hot topic in digital marketing. All stakeholders have been focussing more and more on attribution: companies, agencies and especially big players like Google have been working and pushing on this subject. The “Why?” is quite clear: since measurability is the big advantage of digital marketing, it’s only logical that we want to measure and value our marketing investments as well as possible. Enter the different attribution models at our disposal.

As we all know, AdWords & Google Analytics use as a default the last-click attribution model, meaning that the last touchpoint will get 100% of the credits for the conversion when it takes place. This will already get you as a marketeer a long way as you’re able to pinpoint exactly which channel is giving people the extra push in the back & make them convert. Off course, last-click is not the only ‘standard’ attribution model:

So, which attribution model should I use as a marketeer?

As mentioned here above, Google-products use as a default the last-click model. Although this model is not without its merits, it doesn’t portray the full picture neither. After all, a customer journey (also an online one) rarely consists out of only one touchpoint between you(r brand) and the prospect. Therefor, it wouldn’t be fair to push all previous touchpoints that come before this last click to the side & stop all investment on those channels.

This doesn’t mean that you should dump the last-click model and pick one of the models pictured above which take into account more than 1 step in the customer journey like the linear or the time decay model. It’s not really fair neither to give the same value to each of the touchpoints prior to conversion as people are probably not always equally as engaged/influenced during each of those touchpoints during the (successful) customer journey.

This means it’s essential to value each element of your marketing approach fully to the actual net worth it delivered for your business + to do so as objective as possible (eliminate the gut feeling). To make all of this a little more concrete, I would like to refer to a sportive exemple:

In a football exemple, we can make the statement that the market value of football players isn’t exclusively determined by the amount of goals they score (even though it’s the most important element in a football game).

Off course, goalscoring strikers will cost you more money if you want to buy them than a goalkeeper, but this doesn’t mean that you can buy a goalie or a defender for a penny. Like marketing, football is a team effort meaning that each player attributes to the success of the team according to his/her role in the team. Same goes for marketing where each channel brings a value in its own way.

Introduction off the DataDriven attribution model

Googles most recently developed attribution model tries to give an answer to the following question: how much value can we attribute to which campaign when we look at the bigger picture?

What’s the reasoning behind the DataDriven attribution model? By comparing the customer journeys of consumers who convert to the journey of customers who don’t, the model identifies patterns among those clicks that lead to conversions. There may be certain touch points along the customer journey that have a higher probability of leading a customer to complete a conversion. The model then gives more credits to these important & valuable clicks during the customer journey. This way each of your channels will get attributed its own value.

The added value of the DataDriven model is that it’s taking the whole customer journey in consideration while this either isn’t the case in other preset models (first or last click model) or it’s being done based on some assumptions that are either not proved or not applicable to a specific campaign (e.g. the linear or time decay model).

How does the DataDriven model help me with deciding on my marketing plan?

When you’re working on your marketing plan, you generally start from a certain idea/vision/goal and from a certain, given, budget. The challenge is then to try to decide which marketing channels you’ll use to reach that goal and how you’ll spread your budget across your marketing channels.

We’re often drawn towards results of previous campaigns to determine how we should make this budget split. Unfortunately, when we use this approach, we risk to under-estimate the impact of channels that play their role in the beginning/first half of the customer journey and thus rarely lead towards a conversion. Cutting budgets on these channels could lead to an overall decrease as well, even if you invest more in your performance channels.

The DataDriven approach will allow you much better to estimate the real value of each channel and to decide which budget each of your channels should have in order to reach the best possible overall result in the end.


publication author vincent saelen
AUTHOR
Vincent Saelen

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