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With the rapid evolution of machine learning in digital advertising in 2017 and the industry becoming increasingly more involved in artificial intelligence there is little doubt that this is the future.
With the rapid evolution of machine learning in digital advertising in 2019 and the industry becoming increasingly more involved in artificial intelligence there is little doubt that this is the future.
It is important that we unlock every new opportunity for our clients, so we recently had the pleasure of having Kelsey and Ambah from Google at Loud Mouth HQ to provide the team with an Automation training session.
This covered everything from unique Smart Bidding features to Google Translate - however, we've chosen our top 3 helpful pieces of information from the session:
More than half of all searches are now on Mobile, meaning that there is an increased concentration of consumer attention, fewer ad slots and the importance of mobile site speed and measurement is more important than ever before.
Interestingly, there are now fewer brand searches and more product-focused searches being performed, resulting in higher CPCs and a more intense research process before conversion. This emphasises the importance of working from a non-last-click attribution model, to see the full value of all touch points in the customer journey.
To win Search auctions in 2018 we need to really understand our audience, their level of intent and utilise all the data available. Audience data is now a vital component of all Search campaigns, as is selecting the best non last-click attribution model e.g. Position Based or Data-Driven attribution.
There has been an increase in and vast improvement of Machine Learning automation features within Google Ads; for example, a variety of new and enhanced Smart Bidding techniques offer auction-time bid management based on over one million intent signals, unrivalled by any manual bidding process.
As Google Ads Account Managers, Machine Learning equips us with a suite of new tools to utilise Google's wealth of audience data and really drive performance within our campaigns. With better access to Audience data and A/B testing techniques, we can make smarter decisions and focus on more high-level account management tasks including Market Analysis and Conversion Rate Optimisation.
Despite the power of AI and automation tools within Google Ads, the human element is still vital to engineer that data in ways that add real value and accelerate growth for the business. Before Machine Learning can do its job, Google Ads campaigns need to be set up in such a way that gives the system enough data to drive results.
To enable Smart Bidding techniques to work effectively, all eligible conversions should be switched to a non-last-click model to allow split conversion crediting. All Audience data should also be pre-loaded within the account, including RLSA, Similar Audiences, Customer Match and/or In-market audiences.
Finally, make sure to write at least three distinct ad creatives within the same ad group and enable at least four ad extensions to ensure the machine learning system can test each variation and ensure it is serving the right ad experience to the right user at the right time.
If you would like to find out how a Google Ads campaign could help generate more leads or revenue for your business, get in touch with us today.