Attribution and contribution marketing tools are part of the programmatic terms you need to understand.
So, what is the use of these tools in your marketing actions? What do the terms ‘attribution’ and ‘contribution’ mean? Who are the major players in this market? Are there any recognized certifications in the digital ecosystem? In this post, you will find the main elements to understand the pros of these tools.
Indeed, the most advanced advertisers in the adoption of a data-driven marketing and attribution strategy are reaping considerable benefits from those tools: up to 30%* in cost savings and 20%* in revenue growth. However, only 2%* of advertisers are taking full advantage of this opportunity.
These marketing tools allow advertisers to measure the way each of their marketing levers contributes to events on their website. These events can be a visit or a conversion (leadgen or product purchase) according to one or several attribution models. ‘Marketing lever’ refers to the different budget lines of one’s media mix. For instance: SEA, social, display, retargeting, affiliation, emailing…
For instance, a lever like display is very diversified, both in terms of formats (native ads, IAB, wrapping…) and marketing goals (awareness, acquisition, performance, customer retention…).
In order to make relevant decisions, you need to have the most exhaustive vision possible of your media mix and its resulting interactions. Moreover, the sum of interactions corresponds to a conversion path.
Interactions are associated with an event, more commonly called ‘conversion’. There are different types of conversions:
-Online conversion: arrival on the website, online purchase, subscription to a newsletter…
-Visit in a physical store
-Purchase of a product in a physical store
Here is an example of a conversion path:
It’s important you differentiate ‘attribution’ and ‘contribution’.
This tool attributes an event (such as a visit or a transaction) to a unique lever. It’s a binary marketing tool. One lever is responsible for a transaction, or is not. Historically, tools (such as Google Analytics) attribute the event to the lever that generated the last click. We can then talk about ‘last click attribution’.
This tool attributes a weight of contribution to each of the levers that were involved in the conversion path. It then considers there is not only one unique cause to the conversion: it’s the accumulation of the different marketing levers that has generated this conversion.
Here is a global vision of the major attribution tools. For instance: Easyence, Google Analytics, AT Internet, Eulerian Technologies, Commanders Act, or Wizaly. Adservers like Google Campaign Manager, Sizmek, or Weborama can also make attribution between marketing levers. Note that all tools allowing you to measure contribution also make attribution.
It’s important to note that attribution and contribution tools are not natively integrated into DSPs. Therefore, you need to integrate tracking elements from these platforms to measure the performance of your programmatic campaigns. trading desk A trading desk will then therefore have to juggle between the monitoring on its platform, and the performance observed thanks to the client's tool. This will have to be done according to the attribution model that was set up. Depending on the model, attribution can vary greatly.
These are paid tools for the advertiser. Their cost can fluctuate, depending on the tool’s complexity, the website’s traffic, or the volume of events you have to analyse.
There are three kinds of attribution and contribution tools:
-First off, attribution tools that only take into account ‘click’ events, such as Google Analytics and AT Internet. Those tools are the most widespread - Google Analytics only being free for advertisers.
-Second, attribution tools that integrate ‘touches’, i.e. all of the interactions with a lever, whether it is through a click or exposition. Those tools enable you to measure the performance of levers whose business model is based upon impressions, such as display, social or affiliation.
-Lastly, pure contribution tools that can be added on top of an attribution tool. The French startup Easyence can analyse all of the conversion paths of a website, to establish a custom-made model. This model aims at analysing the contribution of each lever as appropriately as possible, depending on the advertiser’s goals. It helps rationalise budgets between those different levers.
Many models exist. They’re either attribution models (i.e. the attribution of a conversion to a unique interaction), like the ‘last click’ model, or contribution models (i.e. it considers that several interactions have been useful to the conversion), like the ‘U model’.
Given the increasing complexity of digital marketing, the attribution model is increasingly challenged. Indeed, it does not take into account the impact of other interactions along the conversion path. It is therefore interesting to look at contributory models.
An interesting distinction to be taken into account in these models is the notion of ‘a priori’ versus ‘a posteriori’. ‘A priori’ models (called rule-based) imply a bias in the analysis. This bias is linked to the person who chooses the attribution model. Thus, it will inevitably put forward one actor in the media mix compared to another.
The ‘a posteriori’ model (or statistical model), on the other hand, eliminates this bias. Statistical models focus their analysis on a past period of the campaign by using different theories (Markov, Shapley, linear regression…). They highlight the optimal conversion paths to achieve maximum conversions.
Here is a list of the major attribution and contribution models:
The digital ecosystem is complex and technical, and it’s essential to understand it deeply.
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