Case Study – Experiment –
Playing with bid strategy options for paid search Google Ads –
Maximize Conversions bidding strategy
Client – engineering services company: software development, automation, system integration
The Journey
Marketing for engineering companies evolves. It’s a good idea to experiment with new techniques and tools. The challenge is to find the balance. You need to sift through a lot of noise and be selective about which things to try and which to let pass you by.
In that vein, recommendations from paid search platforms (Google Ads in this case) are tricky.
You get inundated with new recommendations constantly.
But you know you should take them with a grain of salt, because you have a sense that the platform’s goal is to get you to spend more advertising dollars.
Having seen many recommendations pass by, the concept of the maximize conversions bidding strategy made sense to me to at least try out.
Why?
Because this strategy incorporates machine learning that leverages feedback from conversions within the account, as well as real-time searcher signals. It seemed plausible that this technique could be helpful.
But, you don’t know until you try. So an experiment was created.
The focus for this experiment was Sales-Ready Leads, as opposed to marketing-qualified leads, brand awareness, or email sign-ups.
Snapshot of experiment results
The results for the campaigns below showed improvements, both from a cost/conversion and conversion quantity standpoint. It’s worth noting that this wasn’t true for all campaigns that were experimented with.
With the evolving dynamics of the Google Ads platform, the market environment, and client preferences, it’s important to monitor, not “set it and forget it”.
