Each hospital previously owned its own website, causing overlap in services. With a new central website with a focus on services and not hospitals, all ads were migrated with a brand-new account structure. This meant there were no previous machine learnings and optimisations, so we had to start from scratch. Another key challenge was that budgets fluctuated greatly throughout the year.
By utilising machine learning, automated bidding strategies and tight keyword control whilst focusing a limited budget on top performing terms, we have greatly improved performance in the year since migration.
Each service line has been reviewed to ensure it is using the correct bidding strategy, with many taking advantage of Google’s Smart Bidding strategies. Beyond this however, CPA targets have also been set based on the service line value and conversion rates to hit the strongest performance target. Finally, CPC bids have also been adjusted within these strategies for the most efficient lead generation.
Keyword sets have been scrutinised to ensure budget is spent on top performing terms, and this has allowed us to maximise the contribution produced for the business by focusing on the highest value services and search terms. To optimise further, unique day parting has been implemented for each service line based on performance at different times of day. This has pushed available investment to the highest converting times of the day.
Notably, Gynaecology saw an increase in conversion rate from 0.67% to 6.77%, despite a 34% reduction in spend. Similarly Urology saw an increase from 1.30% to 3.56%, Obstetrics from 1.26% to 3.80% and Neurosciences saw growth from 1.55% to 4.19%.
Our optimisations meant revenue decreased by only 9% despite a 40% reduction in spend.