How to use emotion data to predict product performance

In his 1999 book The Age of Spiritual Machines, Ray Kurzweil proposed the ‘law of accelerating returns’. Based on the concept that the rate of technological progress speeds up exponentially over time, Kurzweil suggested that the 21st century can expect to experience 20,000 years’ worth of advancement during its 100 year period.

Kurzweil’s rate of change can be seen in the breakneck speed by which smartphones have developed in the last 10 years; as well as the rapid advancement of supportive technologies such as batteries, photovoltaic solar cells, and (as Moore’s Law predicted in the 1960s), in the diminishing size of transistors.

Such is this technological evolution that – faced with overwhelming choice and innumerable new products and services on almost a daily basis – humans are becoming increasingly capricious.

For any brand looking to launch a new technology into consumer markets this can be a perilous reality; for brands looking to invest in technologies their customers might use, this can also mean spending big on items that can quickly become obsolete.

Take Google Glass. Launched to great global fanfare in 2013, the eyewear limped out of production less than two years later, despite a more than positive reception from industry.  

So is there a better way to predict how a consumer is likely to take to new technologies such as Google Glass? Forrester’s senior analyst, Anjali Lai believes the answers lie in getting to understand and interpret customer emotions.

“Change, in terms of consumer behaviour, is occurring so much faster than it ever did. Behaviours are evolving, expectations are evolving. In this new context, traditional metrics that brands have used to predict say, product uptake, don’t necessarily hold water.

“Demographics are a classic example – looking at a customer segment and identifying a group of customers that are most likely to respond to a product or experience. With the ubiquity of the internet and the fact that consumers have access to the cheapest products across the globe, that demographic cut doesn’t necessarily have the same predictive power that it used to have.

“In place of that, businesses have to key into the emotions that are fuelling consumers’ desires to engage with a brand or product and play to them to pull consumers into the brand experience.”

Emotion Evaluator

Alongside a team of fellow analysts and data scientists, Lai has developed the ‘Emotional Evaluator’ at Forrester; a tool that helps establish the emotional lifecycle experienced by consumers in the adoption of new technology.

Built around an algorithm that scrapes the web for publically posted consumer-generated content, social media posts and comments, words, abbreviations and other forms of expression, the Emotion Evaluator can help brands establish what emotions are likely to be elicited at different points in a customer’s journey. The insight gleaned is increasingly becoming mission critical to businesses, says Lai.

“Emotion is becoming so vital in the business world because so much new data exists giving us insight into the science of emotion; now we’re able to put numbers against how emotions work and slice and dice emotional data by different consumer groups or brands, draw correlations between certain emotional responses and behaviours and tie that to different KPIs and brand performance metrics.

“That helps build emotion’s credibility in a business world that is fundamentally numbers-orientated; having that science crystallised is critical and that’s what we’ve been able to do with the explosion of data and the data science tools available.”

Virtual reality

Because the Emotion Evaluator casts a net wider than single channels, such as social media, it can map semantics to emotions beyond standard positive, negative or neutral ‘intent’, adding an additional layer to social listening and semantic analysis tools many brands currently use.     

“We looked at data across forums, blogs and review sites also. We then built a proprietary emotional taxonomy to essentially use text analytics and understand how closely specific words are related to particular emotions.

“This helps us understand how consumers are talking about happiness, for instance, in its various forms; i.e. what is the actual language and the colloquialisms being used to express this emotion? We then used a word vector space model to essentially calculate the distance between all the words consumers are using to talk about emotions. We came up with a taxonomy that is a statistical measure correlating consumer content with key emotions. We’re able to assign an emotional value to any type of conversation.”

Forrester’s analysis has so far revealed a number of enlightening insights that have only been feasible due to the enhanced taxonomy the evaluator leans on. For instance, it found that the expression of happiness for a product or service has a very different behavioural effect than mere appreciation or gratitude: consumers are more likely to open their wallets and spend more with a brand that makes them feel appreciated, but they are also more likely to go out of their way to continue doing business with a brand that evokes a genuine feeling of happiness.

Emotion is becoming so vital in the business world because so much new data exists giving us insight into the science of emotion; now we’re able to put numbers against how emotions work

However, it is a particular case study related to virtual reality (VR) that provided the clearest example of how emotions can play a role in product and service adoption.

“We found that when people discovered and began experimenting with VR, emotions were as you’d expect – surprise and anticipation really dominated their emotional responses. But that level of excitement gives way to anger when it comes to buying a VR device; mainly because people usually have to pay a high price to acquire a product and that’s not usually a pleasant experience.

“If you think about other high-end expensive purchases like a car or a luxury item, consumer anticipation is statistically strengthened at this point or purchase. So with VR, the analysis indicates that the manufacturers and retailers selling the devices have an opportunity to work on new ways to improve the experience by drawing out the anticipation and aspiration further into the purchasing process, as with other luxury or high-end goods.”

The VR research also discovered that consumer trust plummeted through the course of the adoption curve, and that disgust was commonly the overriding emotion felt at later stages of a consumer’s use of VR products, due to concerns around privacy. Words like ‘evil’ and ‘invading’ were often mapped out by the analysis. It’s a similar consumer response that derailed Google Glass, and suggests VR providers could do more to communicate the privacy levels of their products, post-purchase.

Source: Understand Emotion to Drive Technology Engagement (Forrester)

Future use

Whilst the analysis is revealing, Lai believes the benefits may be in priming consumers for future technology as for VR brands themselves.

“Something I think about is how a current experience or behaviour sets the stage for an extension of that experience or a new experience that conditions consumers in a new way.

“For example, the mobile phone has changed the way consumers behave but also primed us to use more portable technology like wearables and work with even smaller screens and have a psychological need to check screens for instant information for things like checking the time or reading messages.

“Similarly, if you were to track emotional response to virtual reality, you could theoretically understand how the technology is resonating with consumers and what that sets the stage for in the future – for tech companies and other product developers it’s helpful to understand the evolution of the emotional journey of VR to map potential responses to other future emerging technologies.”

It is also a powerful tool to help predict potential points of negativity along a customer journey and work out methods of avoiding them.

“Negative emotions can be indicators of behaviour change but companies that foresee those negative emotions have the capacity to predict and tackle and change this future behaviour,” Lai adds. 

“A retailer, for example, knows that this element in the experience elicits not just a negative emotion, but a particular negative emotion like disgust that often drives consumers away from the brand or weakens their likelihood to return, so that retailer can jump in at specific points in a journey and offer some kind of surprise and delight to immediately change the mood and the tone of a customer that’s statistically more likely to shift their perception and their emotions from positive to negative.”

Given that attention spans are getting shorter and that consumers are increasingly stepping away from products and services that elicit negative emotions, understanding where negativity might exist in a customer’s journey and taking steps to reverse it is becoming increasingly important.