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Key takeaways
Anyone that is human will understand the importance of emotions. They influence our feelings, and those feelings have the power to completely determine our decisions. So when it comes to the design of services, customer emotions are an important aspect to consider.
In my last article, I talked about how brands can set themselves up for success by understanding the emotional levers of an experience. Now I want to turn your attention to sustaining that success and the technology that can be leveraged to help.
The fragility of emotions mean that they’re easy to swing, but rising consumer expectations makes them increasingly harder to satiate. Therefore, despite having designed emotional journeys to provide customer and business value, organisations must remain agile by responding to changing needs.
To support this, brands should establish a cadence of emotional data collection, analysis and personalised responses to target individual customers. This is not a periodic cadence but one that, with the right technology, runs constantly in the background. This approach will help organisations to:
These interventions need to occur discreetly, though. This allows customers to reap the benefits of a feedback loop that offers personalisation in a timely and effective manner. Otherwise, if distracted by the presence of the technology, the customer may act differently and the reading of their emotional state may not be authentic. This could trigger unintended business responses by acting on the wrong emotion. Brands also need to leverage a wide range of emotional data sources and validate the customer’s true emotional state to avoid responding to emotional peaks and troughs that could be attributed to outside factors.
Fortunately, there’s a range of evolving technologies — from wearables to sentiment analysis, from the Internet of Things to social media crawling — that can help brands to stay at the forefront of the emotional game.
The problem: Incorrect or absent interpretations of the emotional state
The solution: Artificial emotional intelligence
Think about an occasion when you needed to make a phone call for an essential reason, but were kept on hold for an extended length of time. Perhaps it was to update your address after a house move, for a service that couldn’t be done online. The long, lonely wait, accompanied by some patchy queue music, only served to build frustration.
Customers live in the ‘now’ society. Technology has taught us to expect things almost instantly. Made to wait without justification, we become impatient. By not sensing the customer’s frustration, by leaving them in the queue, they will form an increasingly bad impression of the organisation. Small experiences like this can do irreversible damage when customers are saturated with alternative choices.
In a case like this, artificial emotional intelligence could be used to identify individuals that may feel angry, stressed or impatient. The organisation can then take action and put them back on a positive pathway.
This can be done even before the customer speaks to an agent. While in the queue, artificial emotional intelligence can use speech recognition to detect changes in the caller’s tone, tempo, volume and language, to determine their emotional state. This data collection can then be used to trigger alternative flows that may place them in a priority queue, for example, or to alert agents to the caller’s stress, so they know to adapt their conversational style.
The real power of artificial emotional intelligence comes when it is combined with the contextual insights that are gained from segmentation frameworks (which identify the needs of specific groups), past interactions and trend analysis. This combination of emotional intelligence and context then helps agents to provide personalised solutions and recommendations. It is these intelligent interactions that have the power to truly delight customers.
The problem: Saturation of choice means it’s harder to influence emotional triggers
The solution: Social listening and sentiment analysis
Abundance of choice means that brands have to compete for their customers’ attention. Designing an emotional journey is the first step to success but societal expectations are changing so fast that what once was a positive experience may now be an experience customers feel indifferent about. This is why organisations need to continuously raise the bar when it comes to elevating emotional states.
Social listening and sentiment analysis helps businesses uncover how their audience feels about the industry, their brand and competitors. By trawling different social media sites, organisations can build a picture of how they’re delighting customers, how they’re failing them, and how they could be doing more. This collectively provides the knowledge for designers to re-design or iterate future emotional experiences that delight and inspire loyalty.
The problem: Not knowing the right time to ‘surprise and delight’
The solution: Predictive analytics
When you first witness a magic trick, it may astound you. If you were to see that same trick over and over again, however, it often becomes repetitive: the element of surprise has worn off.
Creating positive emotional journeys is partly about keeping customers on a path that retains their interest. Providing interactions that surprise and delight at every opportunity, though, is overkill.
The art, then, is in using emotional states and customer attributes to understand the right time and opportunity to truly delight your audience and keep them reflecting on that experience.
Predictive analytics is key to making predictions about unknown future states with some certainty. The technology uses structured (ie. demographics) and unstructured (ie. social media posts) data to uncover future patterns, and help brands preemptively meet customers’ emotional needs.
Such insights can help the organisation to tailor its marketing strategy. Based on these customer attributes, it may be able to:
Let’s take an example. Structured data can determine that a person is a 40-year-old male, with a wife and two children. Unstructured data determines he’s interested in rugby. Dates for the Rugby World Cup have recently been announced and his social media feed brings up a promotional deal for an all-inclusive family package to the World Cup. The relevancy and timing of this post was useful for him, and he clicks through, grateful he hasn’t missed out. Without predictive analytics, the timing or content of his social media posts would have been more accidental, meaning he could soon become immune to them or worse, annoyed – serving no benefit to either party.
The technology discussed here has been rapidly evolving but the true power of it to interpret emotions has yet to be realised.
That being said, there are already some interesting use cases of emotionally intelligent technology. For example, researchers at the Stanford University School of Medicine use Google Glass to help people with autism better understand emotional cues.1 Facial and voice recognition in vehicles, trained to identify and alert fatigued or distracted drivers, is already on the market.2
By developing a strategy to harness this power early on, brands will be at the forefront of anticipating and responding to customer needs. Now, isn’t that a reason for everyone to be happy?
Read the prequel to this article How to design your brand around emotions.
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References
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