Insights

Understanding automation within paid search

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Paid search specialists use automation to replace repetitive and time-consuming tasks, such as reporting, sourcing and analysing data, producing ad copy and making decisions on bid amounts.

Paid search specialists use automation to replace repetitive and time-consuming tasks, such as reporting, sourcing and analysing data, producing ad copy and making decisions on bid amounts.

This frees up a lot of time for marketers as they are not spending time on manually collecting this data to inform strategic plans. This allows them to focus on why these things happen and the actions to be taken based on the information provided.

Automation can provide a number of benefits for marketers, such as:

  • Saving time on a number of tasks, allowing more time for more strategic activities.
  • Can save cost as it can improve the efficiency of campaigns.
  • Can reduce human error by automating tasks based on the learned data.
  • Better insight into data as AI technology reports based on the information learned, rather than manually gathering information and forming an opinion around it.

Our Paid Search team have been implementing a number of automated bidding strategies and have been closely monitoring them with the aim to highlight variations in performance when using different strategies across the same data range, as well as increasing the amount of conversions and revenue generated for these accounts.

Note: The Target CPA amount's were either set at the current performance rate over the last 30 days, or the recommended figure suggested by Google as a starting point. 

Client A - Home Security Sector

For Client A, we ran a search campaign targeting a number of keywords associated with their highest selling brand, Yale. Prior to automation, the campaign had always performed at an ROI of between £2 and £3.

An identical campaign was created using the Maximise Conversions bidding strategy, to test the variation in performance. The automated campaign outperformed in almost every aspect.

Across a six week period, it created a greater amount of conversions and revenue from an almost identical number of clicks.

This campaign also performed much more efficiently, by recording a lower CPA, higher ROI and performed closer to the client's 15% COS target.

Across a six week period...

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It is necessary to ensure that the original targets implemented are realistic based on historical performance, are continuously monitored, and are adjusted accordingly. By utilising Google’s advanced machine learning algorithms, as well as the various different contextual signals that Google has access to, it prioritises our bidding towards 'good' auctions, which are more likely to result in a conversion - therefore having a positive impact towards the return generated from the specific campaigns, and the account itself.

It is critical to consider the client’s specific KPI when determining which auto-bidding strategies to implement for search campaigns. For example, in scenarios where clients may have a revenue target, it would most likely be the best option to implement the Maximise Conversions strategy, whilst implementing target CPA for client's who are more focused on generating more conversions at a lower cost, and target ROAS within search campaigns for client's who are primarily focusing on a specific ROI target

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