One of the main assets of digital marketing is the ability to measure interactions. This allows you to track the number of conversions generated by each distribution channel (SEM, Programmatic, Social Networks, Email…) in order to identify the most profitable ones and thus determine the best budget allocation.
This is where the notion of attribution comes into play, allowing you to distribute the conversions recorded between the marketing levers according to a relevant model.
Let’s take a concrete example:
If a customer buys from my site after clicking on an SEM ad, should we consider that the sale was made only because of this last click? Should we attribute 100% of the revenue to this ad alone?
In reality, it is not so simple, because before buying, the customer may have learned about the brand through a video on their Instagram feed; then been exposed to a programmatic display banner; compared different products on Google Shopping before finalizing their purchase after clicking on a text ad.
These different interactions are essential contact points to be present throughout the customer’s purchasing process, both in the awareness, consideration and purchase phases.
The choice of the attribution model is then crucial to know which are the effective levers to generate conversions and calculate the profitability of its investments.
All tools using attribution models will then split each transaction and its revenue across multiple acquisition levers.
A conversion that generated $100 in revenue might be split $30 to Instagram, $20 to SEM and $50 to SEO.
Ideally and when possible, it is better to use the data-driven model. Google Ads will make it its default model by early 2022.
However, while this model is the least imperfect, it is not without limitations. Limitations that it is important to keep in mind to avoid analysis bias:
Impressions are not always taken into account as interactions on certain tools, which will favor click-generating levers like search, to the detriment of levers further up the tunnel like social networks or programmatic. Levers that are nevertheless essential to the buying process.
Even on attribution tools that take impressions into account, the installation of impression pixels is not possible on social networks. Only a few solutions such as the Wizaly attribution tool allow to extrapolate the volume of impressions.
Data-driven marketing requires a high volume of conversions to work.
As customer journeys become more complex, attribution becomes an essential concept to consider. While no perfect model exists, the most reliable is data driven. This model can be used on Google platforms, but also for attribution or web analytics tools like :
