Why do you need attribution marketing ?
Attribution marketing answers a marketer’s need : understand the impact of each marketing channel.
The increase in marketing channels and touchpoints on different devices makes brand marketing and media buying optimization increasingly complex.
Brands can use many online and offline channels →
It is important to calculate the objective performance of each investment in marketing and communication.
Attribution calculates the impact of each marketing channel used by an advertiser in the complex conversion paths of its customers, with three main objectives :
- Optimize the marketing budget for each channel in connection with its real impact in the conversion path
- End the siloed view of marketing channels that lead to count the same conversion multiple times, and to pay the right price to media partners and advertising networks
- Understand how various channels interact and their synergies to generate a clear understanding of your marketing mix
How should I go about attribution ?
The first step is to pick the attribution models that best reflects the reality of consumer journeys.
There are two big families of attribution models : predefined and algorithmic.
Attribution marketing models
The best known attribution marketing models are predefined historical models, that may either be single or multiple touchpoints.
Single touchpoints attribution models start from the assumption that a purchase decision was entirely triggered by a unique touchpoint in the customer journey. The best known single touchpoint model is the « last click » model, that considers that the last click was the only interaction that impacted the purchase decision. Single touchpoint models provide a biased view of reality since they only value one single interaction.
Because of the intrinsic weakness of single touchpoint models, most digital players have moved on to multiple touchpoint models.
Those models are an improvement on single touchpoint models since they take into account the entire customer purchase journeys. However, they rely on a set of arbitrary rules that do not take into account the diversity of customer purchasing behaviors and the evolution of the media mix.
Predefined models attribute conversion on the basis of a predefined model that relies on the intuition of the advertiser and on subjective assumptions to attribution conversions.
Algorithmic attribution
A new view of attribution that closely matches the customer’s behavior.
The weaknesses of predefined models as well as the emergence of big data technologies have led to new attribution methodologies that rely on algorithms. The goal is to analyze the impact of each marketing channel in the conversion path with no arbitrary assumptions.
In a digital ecosystem that grows increasingly rich and where customer purchase behavior is increasingly complex, algorithmic attribution models are the only way to deliver an objective view of the performance of each marketing channel.
Wizaly’s attribution model is not based on any assumption and is only based on the data we collect. It is a 100% data-driven model.
Wizaly’s 100% data-driven attribution model.
What should you expect from your attribution solution ?
― A data-driven algorithmic model
― An exhaustive and granular data collection
― A user-centric view : reconciling multiple consumer paths across several devices
― Beyond a site-centric view : take into account both clicks and impressions… even for social networks.
― The ability to bypass technical limitations such as adblockers
― An omnichannel view that unifys customer data and third-party data
Understanding attribution to pick the right solution
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