Transform your marketing with machine learning
No doubt you’ll have heard the phrase ‘machine learning’ throughout the marketing department over the last two years. Even if you haven’t, this article aims to tell you all you need to know and why you may start to hear more and more about it in 2019 and beyond.
First off, what is machine learning?
Machine learning sits within a constellation of related technologies that are all part of ‘artificial intelligence’. Artificial intelligence – AI – is an approach to technology that aims to create more human-like responses in computers. For many years, computers have been programmed so that they perform specific functions. AI is an approach to computing using a programming framework that is conceived by a human but where the computer is able to write future programs based on a desired outcome.
For example, let’s say we ask a computer to sort pictures in a database into subjects such as animals, people and buildings. Initially, we program the computer to determine the difference between the images so that they can be sorted. However, as the volume of pictures and the complexity of them increases, we ask the computer to write code that is able to evaluate those differences and build a database of learning and decision trees that support the desired outcome.
In the example above, we are talking about machine learning where the computer learns how to solve problems by writing new algorithms aimed at solving complex problems.
So what does this have to do with marketing?
There is a growing trend to automate large parts of marketing inventory to drive greater effectiveness. The premise is that a machine is able to learn how different creative formats perform. Based on an analysis of the performance, the machine learns what works well and what works less well. This takes a huge burden from the marketing department in terms of number crunching and also increases the speed with which advertising creative is optimised. The aim is to move to a model where advertising and content is serviced in real time based on a number of factors, particularly user behaviour, language, time and place. To operate at real scale and with speed, companies are turning to machine learning to gain a competitive advantage, increase efficiency and drive down marketing wastage.
There are a number of large technology companies that offer AI as part of a marketing automation service. Companies such as Adobe, IBM Watson and Google have all invested heavily in creating machine learning solutions to solving common marketing problems. Bain & Co in partnership with Google, published a report in 2018 that showed what we have long suspected, that advertising messages shown at the right time, aimed at the right person, are more likely to find revenue and sales growth through marketing effectiveness.
Adidas has learnt that truly effective marketing depends upon not only the right messaging, but also on the right delivery and a seamless connection between marketing and the
e-commerce sales funnel. “Data gives us a real time listening tool that shows us, ‘Is what we’re saying mattering to our consumers? Is it resonating?’ We are finding that we know very quickly if something is working or it’s not.” In the case of the recent campaign for Ultraboost X, female runners who saw the optimised creative were 102% more likely to purchase versus the standard product ad.
At Splash, we work with a number of the world’s leading brands to get the best from their marketing technology solutions by helping them to manage performance. There are two elements to this: increasing the amount of creative that is automated and then optimising the performance of that creative by utilising machine learning to help drive specific outcomes.
Chris Goddard, Global Creative Director at Splash: AI and machine learning technologies are already integrated into our day-to-day platforms, allowing us to tailor campaigns for our client and their consumers. With the data generated by machine learning comes more scope for Splash to be genuinely relevant through our creative.
If you would like to know more about how machine learning can help transform your marketing, please get in touch with email@example.com to find out more.