Everyone loves a buzzword and when corporations began adopting AI in the 80’s this was no exception. Millions of people around the world latched onto it. Deeming it the vehicle that would transform the world as we know it. Disrupt industries for the better and have the potential to reverse engineer all the damage we’ve caused our planet.
Don’t get us wrong, Artificial Intelligence and Big Data has led to numerous innovations and discoveries.
It’s done and continue to do remarkable things. Pioneering several technologies that depend upon artificial intelligence (AI). Which accelerate growth, create new opportunities and advance an array of fields. There is hardly any industry that is not trying to include AI and the use of Big Data for better analysis and results.
Even the fashion industry thanks to AI works better. Enabling us to track, measure, monitor and predict new ways to maximise outputs whilst minimising impacts.
AI alone will not save fashion.
AI can play a big role in guessing and understanding how humans react to any particular situation. It can ingest enormous, complex datasets, predicting outcomes in just seconds. But it is behavioural science data and psychological science which can be gathered without sampling that makes what AI does impactful.
Behavioural science is the WHY behind why we humans do what we do.
The thought process we go through that determines our decisions, our biases when making those decisions and the subsequent actions that we take. It is psychology present in our day to day lives. Everything you do is related to behavioural science.
Your thinking patterns, talking patterns, eating patterns, sleeping patterns and yes, including your shopping patterns. Think about your clothing – it’s more than just your second skin, it’s the way in which you express who you are, what you believe in and the stance you take in this world to say “here I am, this is what I believe in.”
What we wear says a lot about us. We make a judgement about whether we like someone in under a second and seek evidence to support and extend judgment to relate to nonphysical characteristics like temperament and abilities.
But we also do this in the choices we make for ourselves. If I consider myself a conscious shopper or an environmental do-gooder, I’m going to want to follow through with decisions and actions that empower and support these beliefs right? Well not always.
Just because I think I am (or want to be) a conscious shopper or environmental do-gooder does not mean I am. At times when I am faced with conflicting offers or benefits that are too good to pass up, I can easily be swayed, going against my “ideals”. We are only humans after all.
This is where behavioural data science outsmarts AI’s predictability.
Unlike AI that uses historical data to build pattern recognition to predict future actions and results, behavioural data science does not solely rely on this data as true to predict accurate results in the future. It knows that humans are far more complicated than what a standard dataset can tell us, that every experience is fraught with biases and layers and layers of cognitive bias go into the decision making process.
By combining behavioural data science models with AI algorithms, we are able to significantly improve and simplify predictions of human behaviour in a wide variety of contexts in a way that is accurate.
AI and Behavioural Science Data can save fashion
AI is already engaged by many companies to reduce their waste, by analysing data and predicting inventory levels and quantities of products needed by stores. But what’s often missing and where behavioural science data closes the gap: is the ability to accurately predict human behaviour, not just purchase intention, which is not the same thing.
AI is also frequently used to suggest sizes to online shoppers to avoid garment returns. An insanely big problem that costs the fashion industry around $400 billion a year in lost revenue, with an even greater impact on our planet, as every return generates at least 50 kg’s of CO2. By incorporating behavioural science principles and showing shoppers what making the right size choice means in CO2 savings, you do 2 things: tap into our “feel good” receptors that influence our purchasing decisions and facilitate more informed buying behaviours of clothing that does not get returned.
Another area that AI is said to be making headway is in trend forecasting. The idea being to improve the accuracy of forecasting to reduce over production, sell-through rates and waste. However this is an area that has not been nailed, with overproduction from inaccurate forecasting still being between 20-50%. Incorporating buying behaviours influencers instead of relying solely on purchase intent can be the shift required to minimise overproduction and maximise profits without waste.
One key area that AI and behavioural science data can reshape the fashion business model from the current linear model of “take-make-dispose-waste” to the Circular Economy, a regenerative model of “make-use-return”. Combining an analytical approach, behavioural data, historical and real-time data from producers and users, predictive models can be used to not just reduce fashion waste, but eliminate waste completely.
AI and Behavioural Data Science can save fashion. But it needs to be used in the right way, for the right things in order to transform one of the most polluting industries on our planet.