Founder XMplify Consulting Ltd
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The next step in CX will take EI and AI

22nd Sep 2017
Founder XMplify Consulting Ltd
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A lot is being said about Artificial Intelligence (AI) as an enabler to great Customer Experience (CX) at the moment and it’s easy to see why; when so many companies are facing a perceived commoditisation of their products, where service excellence is the ‘new normal’ and highly positive satisfaction scores are a given, the hope is that AI will enable organisations to understand and address changing customer needs in a more agile and personalised manner.

A number of organisations are making advances in linking machine learning to customer journey analytics to identify critical points of inflection - behaviours that are tied to quantified results and determining what works in nudging customers towards a desired outcome. The theory is that AI is able to ‘understand’ language and observable behaviour, learn from past examples and recommend next best actions. However, many of these systems lack an important aspect – the Emotional Intelligence (EI) that deals with the difference between machines and people - feelings.

So, I have noted with interest the recent examples/claims about AI-enabled facial recognition that can identify emotional state, possibly even sexual orientation or political leaning. Other systems can already extract, categorise and quantify some emotion from the linguistic ‘micro-expressions’ of the written or spoken word using Natural Language Processing (NLP), whilst voice stress analysis systems can help measure tonality and levels of stimulus. There is even work underway to give computers the ability to mimic emotions. We live in interesting (if a little disturbing) times!

Why is this subject important? because the neuroscience shows that emotions play an enormous part in our decision-making. Even seemingly simple, logical decisions are subject to the vagaries of the human heart. So, whilst we like to think that we are informed, rational human beings – making decisions by weighing up the pro’s and con’s - the reality is much more complex and messy. Furthermore, this is not restricted to just business-to-consumer environments, it's true for business-to-business as well.

Whether our behaviour is rational or irrational doesn’t really matter to these AI systems – just so long as it’s repeatable and statistically significant, so that they can ‘learn’ about cause-and-effect in related to events. The challenge of course is the individual context of each customer. We all have different backgrounds, the way we process experiences (for example, linguistically – using the other NLP: Neuro Linguistic Processing) and especially how we feel, are unique to us: even identical twins will react differently to the same stimuli. Therefore, whilst the logical decision-making premise may be straightforward (I need the product + you’re the cheapest option = I will purchase from you) the emotional journey defied machine analysis (until now).

Part of this is about acknowledging that observed behaviour (what we can see and measure about customer behaviour) is only the tip of the iceberg. Below the waterline lurks feelings, beliefs, attitudes, biases, even the ways we perceive the world and whilst 'understanding' facial expressions and language might be enough for the here-and-now, they struggle to deal with the relationship between customer experience (as perceivedby the customer) and future behaviours, which are in turn based in our prior experience.

Take for example the concept of ‘forgiveness’: how likely I am to forgive your mistakes is a mix of how serious they are, how sensitive to them I am and how predisposed I am to judge you favourably. If I already ‘like’ you, I am much more likely to forgive you than if I already ‘hate’ you. There’s a temporal aspect to this too – if your last error was yesterday, it will have a bigger effect than if the last time was a month, a year ago or never.

So, unless all customers are making purely logical, functional purchasing decisions (doubtful – see above), the next generation of operational CX environments will need a degree of Emotional Intelligence to match the Artificial Intelligence they are currently starting to use. And to operationalise these insights will need a new kind of learning machine and data: one such approach is the Customer Experience Vector (CXV) – a marriage between data science and behavioural science that can cope with individual experiences and non-linear customer journeys – about which I will write more at a later date.

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