Columbus x Google Summit pt. 2

Following on from last month’s Value Optimisation piece, Mark Duffy, our National head of Performance is now focusing in on Performance campaigns and just how you can better optimise these campaigns for success.

How top performance advertisers win.

The dial is moving faster than ever in the Performance space. The rapid evolution in the data and technology arenas is paving the way for smarter Performance marketing practices, shifting our approach significantly. Back in the day, (a mere decade ago), agency partners were wholly focused on the ‘Search first’ approach to meet Performance KPIs. Additionally, we treated Performance channels separately with vastly different goals and optimisation methods for Search, Display and Video. The ‘Mobile first’ era then shifted things again. At the time, it was best practice across the industry to build out campaigns and even accounts by specific device.

In the time since there have again been major shifts in the industry. We are now moving into the “Artificial Intelligence First’ era, moving the dial faster than ever before. Within the Performance space, Machine Learning bid strategies are here to stay and have significantly shifted the approach towards optimising campaigns.

What’s changed?

So what exactly is powering Machine Learning and Automation in Performance Marketing in the Google ecosystem? The core pillars that enable Machine Learning (ML) and Artificial Intelligence (AI) to learn complex patterns are;

  • New Data
  • Computing power

Today, Google is processing 5 billion data signals across all Google properties. This is predicted to increase more than 10 fold be 2 trillion by 2020. There is a colossal amount of data that fuels ML and AI. But, it is not only the amount of data but the immediacy at which it is available, that enables ML and AI to learn patterns quickly and make the correct decisions at an increased speed, more accurately. That could be optimising for a person on the verge of making a purchase, based on past behaviours of others who demonstrated the same intent and behaviour signals before making similar purchases. With the sheer amount of data to work with, computing power has evolved rapidly with power increasing 200% every 18 months. This means ML and AI will increasingly be able to make more informed and accurate decisions. ML and AI will be able to process data signals at speed, finding consumers who are more likely to convert; improving Performance campaigns exponentially. We are seeing AI integration in many aspects of Google and its product offering.  Google Photos is a classic example, wherein image recognition accurately identifies facial and contextual recognition. In terms of contextual recognition, your photos are automatically categorised by Food, Selfies, Cars, Christmas and even nightclubs. Additionally, there is now the ‘smart reply’ functionality within the Gmail inbox, saving those precious 37 seconds when we’re on the go.

AI and Performance
So, we’re here now but how has all this data and computing power actually changed the way Performance marketing works?  The days of optimising by a specific channel in isolation, with separate goals and success metrics are gradually disappearing. We first saw this initially with the release of Universal App Campaigns. If a campaign objective is to drive app downloads at a set CPA target, then Universal App Campaigns streamlines the process. Universal App campaigns will allow the promotion of apps across all Google main properties including Search, YouTube, Google Display Networks and Google Play. The creative assets are uploaded with a set CPA cap, eliminating the need to establish campaigns on different channels.

For retailers, a product inventory feed integration into Google Merchant Centre is all that is needed to maximise sales and ROI. Universal Shopping Campaigns are the next evolution to drive improved results. Shopping campaigns are fully automated, delivering a seamless cross-channel experience to consumers for improved ROI. Ads will run across Google Search, Display, YouTube and Gmail. When establishing the campaign, a cross-channel ROI target is set up and the machine itself finds qualified consumers. Having an objective across multiple channels reduces campaign wastage by applying universal frequency capping. Additionally, the ML powered campaign knows when and on which channel to push ads, connect and resonate with consumers.

What this means for clients

Artificial Intelligence and Machine Learning are scaling at an unprecedented rate into the Performance Marketing arena. Google is breaking down the channel silos and enabling advertisers to optimise performance while delivering a seamless experience for consumers. Nonetheless, the best practice fundamentals surrounding account structure and set up are still core to building a solid platform. When these are supported by an additional layer of automation and seamless cross-channel experiences, the value and efficiency are amplified. Artificial Intelligence and Machine Learning are an ever-changing and exciting evolution that we are looking forward to capitalising on for our clients, maintaining our first to market approach and delivering unbeatable wins in Performance.

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