Brands that can understand and respond effectively to their customers’ emotional state have triumphed at the engagement challenge. That’s why they spend so much money trying to comprehend customers, whether it’s using tools like brand perception and crafting responses using tools such as personalisation and neuromarketing.
Technology is tackling the issue of how to understand and respond effectively to our emotional states, with the aim of really cracking the human-AI interaction puzzle.
If we can achieve an effective relationship between human emotions and machines, we can completely change the way we interact with them. For brands, this means machines can better be trusted to represent the brand in interactions without detriment to the relationship with their customers.
If machines can judge emotions correctly they may even be able to better respond than humans themselves, as human operators come with their own emotions that need to be factored into transactions.
Some people working in the field of machine-managed emotion believe we’re on a path to achieving a network of connected, emotionally-intelligent machinery that can predict, understand and manage users’ emotional states.
The next step for brands will be drawing value from this expert emotional management in a move that’s been dubbed ‘the emotion economy’.
The emotion economy describes the advent of machines that can understand and respond effectively to human emotion using a response that’s tailored to a particular situation. It’s technology that’s based on intelligent learning and analysis of huge quantities of data.
It’ll be used to guide marketing campaigns and tailor them more effectively. It’ll also be used to manage customers directly, with new chatbot technology that can ace each encounter and delight the customer. And it’s already in use to some extent, handling customer service queries in Japan’s Mizuho Bank and helping salespeople understand how they are perceived.
Humans are emotional animals
We like to pretend that we’re rational beings, taking decisions in our own best interests based on available facts. Economists and policymakers construct most of their arguments around this view. But the reality is that we’re far more emotional animals than we like to admit.
Cloudy days and a national team’s poor performance in major football tournaments seems to impact on the stock market; the ultimate network of decisions that are supposed to be taken rationally. There’s no point denying emotions play a major part in how we behave. But how can they be used to guide decision-making?
It’s a theme explored by many academics and writers, including MIT Behavioural Economist, Dan Ariely, in his 2009 book Predictably Irrational. Research such as this reveals that egos and the placebo effect seem to drive many of our purchasing decisions.
Businesses are already finding ways to understand user emotion based on analysis of their behaviour. Facebook famously ran an experiment in which it modified which posts users saw in order to manipulate their emotions.
The social media giant was widely criticised for the experiment, which helped inform the platform’s advertisers and may just have been the start of the emotion economy.
Voices and emotion
It isn’t just our Facebook posts that provide clues to our emotional status. Israeli start-up Beyond Vocal is analysing human voices to understand how intonations reveal emotional state.
It’s work that could eventually be highly impactful on everything from insurance claims to law enforcement, with a lot of implications for call handling. BeyondVocal also believes it could be used in healthcare to understand a person’s health state, and it’s already inviting companies to participate in trials.
For most brands, the key implication of the emotion economy is to help them better understand and serve customers. By better responding to customer emotions, brands may be able to better serve their needs, get closer to them and have a long relationship.
Used effectively, mastering this kind of technological solution could be a major leap forward in customer engagement at scale.
But there are also potential pitfalls. The popular backlash against Facebook’s early emotional experimentation shows how hostile the consumer environment is for companies using these techniques.
There’s also the potential for behaviours to be grievously misunderstood and result in an offended customer. A good example of what can go wrong in machine prediction of behaviour is when US retailer Target correctly predicted a teenager’s pregnancy based on her vitamin purchases before she’d told her family.
No matter how effectively AI can understand and respond to emotion, humans are particularly effective at spotting fakes. Brands may be best advised to be transparent about the technology they use to manage customer interactions, or they risk angering customers who may feel deceived.
Although better emotional technology may give brands an advantage in customer engagement, it’s also likely that humans may crave more authentic encounters. It’s for brands to decide how best to take advantage of the new technology in a way that best serves their audience.