Modern Marketing

How can marketers apply machine learning? New report from The Drum explores the power of data-driven marketing


By Ayesha Salim | Content Lead

April 26, 2017 | 4 min read

The Drum in partnership with intent marketing specialist, Iotec, has launched a report exploring the application of machine learning to solve commercial challenges.

New report:  Machine Learning: Empowering the Next Generation of Marketing

New report: Machine Learning: Empowering the Next Generation of Marketing

The report, Machine Learning: Empowering the Next Generation of Marketing, examines what implications machine learning has and will have on the marketing world, identifies common misconceptions and sheds light on applicable AI-driven marketing solutions.

A growing body of research indicates that machine learning is moving to the top of the marketing agenda. A survey by Demandbase and Wakefield Research revealed that 80% of marketing executives believe that AI will revolutionise marketing over the next five years. But the same survey found that only 26% are confident in their understanding of AI technologies and its application to marketing.

Similarly, Forrester’s study of 150 marketers found 94% of marketers are excited by the possibilities of using machine learning to optimise their campaigns but are confused by how best to implement these strategies.

One of the key pieces of information presented in the report reveals that by 2020 approximately 1.7 megabytes of new information will be created for every single person on the planet every second. This highlights the increasingly important role of data scientists and their specialist skills at separating true and relevant data from the noise.

Other discussion points include machine learning’s potential in programmatic marketing as well as its ability to manage the complete customer journey from end to end. Experts in the report discuss how machine learning can be dynamic, exploratory and help brands discover new audiences, but need to caveat the time it takes for the machine to learn. Marketers should not constrain the learning process by asserting human assumption or adding predetermined criterion.

This report examines the differences between AI and machine learning; the role of big data in machine learning; how machine learning powers intent marketing; how machine learning is being used by marketers; how marketers can implement machine learning into their strategies; and the future of marketing.

The report contains contributions from: Dr Gavin Brown, reader in machine learning at The University of Manchester; Fabrizio Di Martino, director of digital marketing Europe at IHG; Thomas Gärtner, professor of data science at The University of Nottingham; Norm Johnston, global chief strategy and digital officer at Mindshare; Ian Liddicoat, global head of data technology and analytics at Zenith; Emily Macdonald, head of programmatic, International at Digitas LBi; and Jeremy Waite, evangelist at IBM Watson marketing EMEA.

Download the full report here.

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