Machine learning and AI has been the poster boy of 2018. Almost every marketing email, webinar and conference that I’ve engaged with has had a track or theme dedicated to it. It’s no surprise then, that marketers are taking it seriously, but the learnings (and the mistakes) are coming thick and fast.
Despite the appeal that machine learning has to offer, it lacks some of the essential human skills and qualities that are vital to business and, more importantly, to growth. Machines can’t (yet) feel, though we know they can be taught to recognise sentiment in large data sets. The challenge with this, is that one of the key drivers of change is emotion or how people feel about your brand, products and services. We all relate to brands via our feelings, both in-the-moment and over time. The feelings we experience are connected to our values and sometimes the forming of new value sets during our complex lives. The formula here is simple; the greater the positive emotion, the stronger the relationship we have with the brand or the product or service we are using.
But it’s not only this lack of 'feeling' where machines run short, it’s the ability to empathise that they can't yet deliver on.
Why is this important?
Consumers demand humanity from brands. This means that a brand needs to focus on demonstrating an empathy with the inpidual through its values and purpose. Empathy is an incredibly powerful currency. The way brands create empathy is the same way people do it; they have, as the idiom goes, to walk a mile in someone’s shoes.
Cultural and human insight
During the course of a typical research project we might observe small, intimate groups of inpiduals, but also engage several hundred consumers in questions and activities designed to surface their unmet needs, their everyday challenges and, critically, their conscious and non-conscious thoughts and processing.
When analysing the data and outputs from these interactions and observations, we combine our human skills - led by our team of experienced social psychologists - and machines. The machines rely on the derivation of explicit rules to follow, but this where the limitations creep in and why we combine the two.
To use an example, if a verbatim response contains the word ‘sick’ it could be coded as negative. Yet in today’s parlance, ‘sick’ might also mean ‘awesome’ or ‘great’. Taking another example, if an image featured a bike with two wheels then the machine could be trained to tag it as ‘bike’. But what would the machine do if the two-wheeled item came out of a Kinder Egg? Should it be tagged as a bike or a toy?
The machine buts up against its limitations and, as yet, can’t comprehend the multitude of ways of categorising artefacts, discourse and expressions. As we know, humans have a variety of ways of communicating emotion as well, including verbal and non-verbal forms, so the social scientists work kicks in aided, of course, by machines.
Humans and machines in harmony
Researchers, supported by the smartest (analytical and data collection) machines, give us the best chance of quickly unearthing the real meaning, human truths and stories that brands need to build on and communicate with. They are harmonious, supportive and complimentary when applied with integrity. Good research should never value one over the other, they should be seen as one. For researchers, strategists and marketers, this more efficient way of concluding human strategies is enabling more human-centred brands and interactions every day, and allowing us to explore with a greater speed and scale than was previously possible. Above all else, this new relationship is driving the organic growth of brands and is essential to the uncovering of human insight and creation of stories that brands can use to connect them to the modern mainstream.
Further, helps brands and business create new propositions, products and services that create a strong emotional and empathic connection based on them creating real value for the intended audience. Our work is grounded in cultural insight that is elicited through human interaction, observation and the application of social sciences to deduce how factors such as other people, environments and artefacts influence behaviour.
Interested? We hope so.