Automation within the search channel

In part two of a series that deep dives into different digital channels we spoke to Gemma Howly, Search & Automation Lead UKI at Google, about how the search channel is using, and embracing, automation. 

How is automation currently being used within search?

Automation is having a big impact on search marketing and is being used in two core ways; to drive business results and operational efficiencies.

To drive business results, advertisers and agencies are using automation and machine learning, in real-time, to make smarter decisions. Smarter decisions include bidding to the right value, spending more efficiently, choosing the right users; being there when it matters with the best possible message.

Automation can also lighten the burden of setting up and optimising Search campaigns, as well as making reporting and dashboarding quicker

In short, automation helps advertisers and agencies free up time on tasks that were previously repetitive or manual, allowing time to focus on higher-value, business differentiating, tasks.

At what stage of a search campaign can you use automation?

It’s important to start with the business challenge: what are you trying to achieve? You’ll find in most instances that automation can play a role. Want to grow the volume of customers or sales and revenue? Use automated ad formats to enter new auctions or bidding and audience technology to reach new people in a cost-effective way. Want to understand the value of your pay per click spend? Automation allows you to properly value each touchpoint. Fighting for market share in a competitive sector? React to the auction in real time using bidding strategies.

Automation is being used across all areas of Search marketing, from budget and media planning to ‘what if’ scenario planning, from keywords to ads to bids and beyond. It can be used to save time, which can be invested in other areas, like tackling that to-do list that never seems to get any smaller!

What are the current benefits of using Automation within search?

You couldn’t manually choose the right ad, the right landing page or the right bid for every user in every context for every search query based on your business goals. Automation is the only way to maximise the impact of the multiple relevant signals available for optimisation, in real-time, based on business objectives. It is the speed and accuracy it enables that makes automation such a fundamental part of Search marketing today.

Automation can help advertisers and agencies meet business objectives, be that driving volume, understanding the value of their activity, driving market share or delivering efficiencies. By utilising Machine Learning, it meets these business objectives at lightning speed and accuracy and at the same time, gives time back so the focus can be on higher value strategic tasks. Ultimately, if you’re not using automation to unlock workflow efficiencies and make impactful marketing decisions, your competitors will be.

What are the current challenges to using Automation within search?

Advertisers and agencies can feel like they’re relinquishing control by using automated features in Search and as a result, there is a perceived lack of transparency.

It’s an understandable challenge; for years in Search when we have managed campaigns manually, we have had full control over every keyword and bid, taking pride in seeing the results change after we’ve flicked a switch or pulled a lever. Allowing Machine Learning to handle these decisions for us is key to success, but marketers still have control and are needed to set boundaries for the machine (targeting) and to steer it in the right direction (targets, goals).

At Google we’re constantly working on being as transparent as possible across our product set, from insightful Search Terms reports for Dynamic Search Ads to simulation data and signal insights for Smart Bidding to asset reporting for Responsive Search Ads. 

What one top tip would you give to advertisers and agencies who are running automated search campaigns?

Advanced technology can drive rapid business performance in digital marketing but it takes human input to achieve maximum impact. Businesses must have people in place to make smart strategic decisions, optimise the technology, and decide how best to apply machine learning-based algorithms to campaign objectives, category characteristics, and customer behaviours.