Challenge

The key challenge was to improve ROI in a relatively mature sector (insurance) on activity (digital display and search) already heralded as delivering best practice. Our experts had already optimised Aviva’s digital communications, but we needed to pursue further improvements relentlessly, and keep on doing so.

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Insight & Idea

With Aviva investing millions of pounds in digital channels each year in the UK, we realised that we needed to produce a more advanced, always-on approach to drive continuous improvement for Aviva, and at a more detailed level than ever been done before.

Marketers are currently faced with a confusing array of multi-touchpoint customer journeys, so Zenith looked at how machine learning could be used to efficiently process large amounts of data and to automate the most complex and time-consuming aspects of digital planning, while reducing the cost per quote.

Execution

Using live Aviva campaigns, the Data Sciences team in the UK collected advertising cookie data from Google’s DoubleClick and matched it with corresponding first-party sales data. Applying Zenith’s machine learning algorithm, the taskforce was able to precisely attribute sales conversions to specific digital interactions.

 

 

Then, in an industry first, Zenith was able to automatically optimise Aviva’s digital planning by pushing the algorithm output back into DoubleClick’s stack. This dramatic move closed the automation loop – data collection, attribution and a full set of planning changes across multiple digital touchpoints all done automatically.

 

ROI

6%

reduction in CPQ (cost per quote) for search

10%

reduction in CPQ (cost per quote) for display

The automated implementation of modelled output into DoubleClick buy platforms has been a world first and delivered impressive results. For a mature business area in a highly competitive sector (car insurance) this is a very significant result.