HOW TO USE MACHINE-LEARNING THE RIGHT WAY: TOOL FOR A NEW MARKETING PARADIGM
To own the future, marketers must embrace machine-learning as a tool to empower people and bring data to life. If your marketing platform does not offer this, you’re already falling behind.
When some companies think of machine-learning they still make the mistake of viewing it as a replacement for human insight and thinking. The problem here is with perception and imagination, and ironically can inhibit the possibilities of true creative innovation.
Databowl recently launched their machine-learning department Skunkworx, making it an available option to companies who license their software. Before this Databowl had only used machine-learning tools with an exclusive group of blue-chip clients on very speciﬁc campaigns. The results of this cutting-edge software, when used in conjunction with brilliant minds, led to some of the most powerful results we had ever seen.
The application of machine-learning algorithms to large volumes of data instantly revealed unique patterns and insights into consumer behaviour that would never have been identiﬁed by a human-built model. The next stage of the process was giving these unique insights to brilliant chief marketing officers (CMOs) and creative teams to further the potential of their own innovation.
This system, of augmenting human creativity, of stimulating imagination with unique machine-learnt insights, led to unparalleled developments in the marketing efforts of these companies.
For the people at the back:
Machine-learning is a tool to increase the power of people
When it comes to machine-learning being used within marketing, it is no longer a question of if, but when. Our clients are already using machine-learning to improve their marketing. If your marketing platform doesn’t give you the option, then you have already fallen behind.
I am not a piece of data
The mistake of viewing machine-learning as an upgrade on human intelligence, as opposed to treating it as a tool to empower people, draws an interesting parallel with some of the problems that made GDPR, or general data protection regulation, so necessary.
Without wanting to get too deep into the speciﬁcs of data protection, one underlying issue which can be looked at is the fact many businesses used, and continue to use, the idea of data without linking it to the person it represents.
While data can be reduced to nothing more than information converted into binary digital form, behind this is always a real person. As such, data should be afforded the same rights as the person it represents. Any company that continues to make this mistake is deeply antiquated.
Moreover, the mistake itself can only be made by a human as machine-learning can only be objective in its handling of data. With that said, a human will still always be required to deal with the data and to treat it as fundamentally human. Ironically, in this sense, machine-learning can be used as part of a process which brings data back to life and enables you to market to people instead of numbers.
We are at the start of creating a new marketing paradigm, the shape of which will be formed by the possibilities of new marketing technologies. To maximise the potential growth of this new world, we need to encourage an almost, dare I say it, symbiotic relationship between the brilliance of both humans and computers. This goes directly against setting machine-learning and human creativity in conﬂict with one another. This goes directly against treating data as lifeless ones and zeroes.
Future CMOs and leaders of this new paradigm will be the ﬁrst to embrace this relationship and push for progress. The biggest companies of tomorrow will be the ﬁrst to step foot into the new world today. All you need is passion, bravery, innovation, and a marketing platform that understands and enables you to lead instead of follow.
Again, this future is a case of when and not if.
At Databowl we say TODAY.
This article was first featured in “The Future CMO” Magazine in The Times. Click to see the original article on Raconteur, here.