By optimising the account I was able to consistently produce lower cost leads (30% cheaper) and so we were able to increase our spend to generate more revenue overall.

0.3
CPL

The Challenge

GetAgent is a British real estate agent comparison site that uses property data to highlight the best agents to sell your property in your local area.


As a source of leads, Google Ads had not been optimised at all, so I was brought in to undertake an overhaul of the ad account and understand where we could do better in gaining more leads or lowering our CPL.

The Process

The first task was to do an extensive audit, looking at past performance and which keywords were driving consistent lead volume. I then tied leads generated through Google Ads to the back end to analyse lead quality and set up a plan to double down on campaigns and keywords that were working whilst culling or reducing spend in keywords that didn't deliver great results. In a few cases, I decided to test different ad copy and/or landing pages as well.

The Solution

By optimising the account I was able to consistently produce lower cost leads (30% cheaper) and so we were able to increase our spend to generate more revenue overall.

Skills Used

Paid Ads

Industry

Technology

Results by the numbers

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0.5

ROAS

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Please read the Process overview first.


Olivela went against the expert opinions of not only myself, but our paid social lead and their Facebook rep. They wanted to set up their ad sets in a very niche way by targeting each celebrity and their charity. For example, one ad set for Jennifer Anniston and one ad set for St. Jude. Not only did I struggle with targeting challenges, but creative issues as well. The celebrities and charity's representation were later seeing the creative live on their feeds and telling Olivela they were not approved, so I had to pause ads and/or launch new ones. The algorithm was consistently being reset almost on a daily basis due to unforeseen circumstances on Olivela's side.

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  • Industry-standard overall conversion rate of ~2%;
  • Old-school product pages;
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