Using the power of machine learning to drive efficiency and performance in paid search

Services: Paid search

Markets: UK

The challenge

The financial services paid search landscape is increasingly competitive. Hiscox, the premium home and business insurance provider, needed to be much smarter in their PPC tactics and leverage better targeting to mitigate costs.

In order to remain competitive in an increasingly aggressive marketplace, Hiscox needed to increase the volume of conversions from paid search, whilst decreasing the overall cost per click and cost per action. Therefore, Hiscox enlisted the help of Croud.

The Croud difference

Turning to Google’s machine learning products, Croud used Dynamic Search Ads, Smart Bidding and Smart Lists to help drive efficiency across the Hiscox account. Following a deep-dive analysis, Croud gathered insights to inform and optimise full roll-out of each feature.

By adopting a test-and-learn approach, the Croud team was able to continuously optimise the campaign towards conversions, and make full use of the sophisticated machine learning capabilities available.

The results

The machine learning-based approach yielded impressive results for Hiscox. For instance, Dynamic Search Ads (DSA) boosted click-through rate by 8%, whilst keeping cost per quote low. DSA also enabled Hiscox to identify new opportunities, such as targeting people searching for personal camera insurance using long-tail keywords.

Similarly, Smart Lists saw a 62% better conversion rate on average than standard search, whilst Smart Bidding improved conversion rate by 48% and reduced cost per quote by 39%.

All in all, the power of machine learning enabled Hiscox to outperform the competition and stay ahead in a highly saturated marketplace. Google also showcased Croud and Hiscox’s use of machine learning as a best-practice example on Think with Google.



better conversion through Smart Lists


reduction in cost per quote

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