The way agencies run pay-per-click (PPC) campaigns is about to undergo a seismic shift. As a Premier Partner, Space & Time were invited to take part in a recent session hosted by Google called ‘Performance Excellence’, where we learned that spending lots of time managing thousands of keywords within bloated accounts will soon be a thing of the past. Instead, Google’s machine learning will simplify account structures and automate many day-to-day management tasks that used to be done manually.
Why do we need more automation?
The customer journey has become ever more complex. Around 60% of retail searches on Google now use broader and longer keywords, with consumers switching between exploring their options and then evaluating their choices. This is what Google has called ‘the messy middle’. The diagram below shows how consumers loop between these two processes until they are ready to make a purchase:
Different tactics are required to connect with consumers depending on whether they are exploring or evaluating, and marketers need to provide the right information at the right time for every search query in order to move people out of this infinite loop. Only automated machine learning has the capacity to do this. Accounts therefore need to be re-structured to enable the machines to do their job effectively.
How will this work?
The automation of day-to-day tasks can be used by Google Partners in the ‘auto-applied recommendations’ (AAR) tool. AAR has 33 different tasks that can be automated at the behest of the account manager, ranging from creative set-up and keyword recommendations to bid strategy implementation, and targeting suggestions. The AAR is focused on improving the account optimisation score. This is a 0-100 scale provided by Google to assess an account’s health. Maximising this is crucial for performance, with a 10% increase in optimisation score leading to a 10% growth in conversions.
The other aspect where automation will feature heavily is in changes to account structure. Previously – when humans managed accounts – thousands of keywords were segmented out into an extremely granular structure. However, machine learning requires data, which can only happen when broader keywords are grouped together. This allows for fewer keywords, that can then be categorised based on metrics. The consequence of this will be more efficient performance, easier account management and insights that can be identified quickly and more effectively.
Won’t agencies become redundant?
Rather than becoming redundant, PPC agencies will be more important to clients as their focus shifts from day-to-day management to business strategy. This meets growing client needs, with Google reporting that 82% of companies want their agencies to be more strategic. With the adoption of automation, agencies can spend less of their time on marketing objectives and more on business objectives. They can look at elements such as A/B testing, leveraging first party data, acquisition funnels, storytelling, and landing pages – growing relationships and developing trust.
So, are robots about to take over the (PPC) world?
In short, no. Humans still have a very important part to play in PPC campaigns. Companies that adopt machine learning can see a revenue increase of 20% within their accounts, but this increases to 35% when human supervision and intelligence is combined with artificial intelligence.
Whatever the future holds, it is vital to future-proof your accounts and start testing features such as AAR and simplified account structures as soon as possible. If you have any more questions, feel free to reach out to a member of the PPC team at Space & Time and we’ll happily answer these.