Zenith Breaks New Ground in Digital Planning via Machine Learning
Posted on November 11, 2016

Zenith has developed ground-breaking automation of digital planning that delivers significant improvement in effectiveness for marketers and is set to fundamentally change the way that agencies and their clients optimise digital media. 

In fact, over the past six months, a taskforce of data scientists and strategists from Zenith has been developing sophisticated automation of digital planning using the network’s machine-learning technology and bespoke algorithms. 

Marketers are currently faced with a confusing array of multi-touchpoint customer journeys, so Zenith has 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.

Using live Aviva campaigns, the taskforce collected advertising cookie data from the technology stack of a leading demand-side platform (DSP) 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 the DSP’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. 

But Zenith is not stopping there, the network is adding first party drivers-of-demand data into the algorithm in order to enhance the effectiveness of the automated planning changes. In this way, data - such as how price affects sales or the success of creative assets - will be fed into the automated optimisation. 

This radical automation of digital planning is being done using cloud-based technology, with the client retaining full ownership of their first-party data throughout the process. 

This application of machine learning saw Aviva benefit from a 6% cost-per-quote (CPQ) improvement on car search through implementation of the automation programme. For display, Aviva saw a 10% improvement in CPQ through automation.