Zenith has brought machine learning to planning. The agency has developed automation of digital planning that it believes will deliver improvement in effectiveness for marketers and allow better optimization of digital media.

Over the past six months, a task force comprising data scientists and strategists from Zenith has been developing automation of digital planning using the network’s machine-learning technology and bespoke algorithms. Marketers are currently faced with a wide 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 complex and time-consuming aspects of digital planning.

Using live Aviva campaigns, the taskforce collected advertising cookie data from the technology stack of a demand-side platform (DSP) and matched it with corresponding first party sales data. Applying Zenith’s machine learning algorithm, the taskforce was able to attribute sales conversions to specific digital interactions.

Then, in an industry first, Zenith was able to automatically optimize 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.

Zenith is also 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 optimization.

“Zenith is leading the way in changing the business model for digital. This important programme is part of our strategy to leverage the power of data and technology to drive profitable growth for our clients,” said Vittorio Bonori, Global Brand President at Zenith.

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

The agency informs that this application saw Aviva benefit from a 6 percent cost-per-quote (CPQ) improvement on car search through implementation of the automation programme. For display, Aviva saw a 10 percent improvement in CPQ through automation.

“We’re delighted that as part of our commitment to digital and media transformation at Aviva we are breaking new ground with this pilot automation of our search and display. The benefits of attribution modelling will be realised in terms of ROI improvement as well as through operational efficiency,” said James Turner, Head of Marketing (Trading) at Aviva.