Google Ads has never been shy when announcing new features and 2022 was a year like no other. With the creation and editing of Expanded Text Ads coming to an end, Performance Max campaigns making a splash and bid strategy scripting reducing the need for manual optimisation, all signs point towards automation being the future of the platform. Attribution models faced the same fate, with advertisers receiving note of a new model being not only recommended but automatically adopted – Google Ads’ Data-Driven Attribution model.
Advertisers are already overwhelmed by Google’s range of attribution models and so it raises the question of how exactly this machine-learning based model will impact conversion delegation.
On many occasions, attribution is simple – a user sees an ad, performs a key action and the conversion is rewarded to the ad and keyword responsible. The assignment of such conversion is complicated however, in instances where numerous search queries are conducted and multiple ad variations are reached. This is where a defined attribution model can change the game entirely, with those interactions being credited varyingly based on specific campaign requirements.
Rather than complying to fixed rules like the alternative models, data-driven attribution uses a range of data signals in conjunction with the account’s historical data to appoint credit. This is performed by customer journeys between converters and non-converters being compared and distinct patterns in such identified. Additionally, this attribution method applies a level of future-proofing by modelling conversion delegation, even when cookies aren’t present.
All in all, this means less manual data analysis for marketers and a more holistic understanding of how each ad contributes towards your campaign goals.
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