Quantifying (Digital) Happiness

We live in a world where people are obsessed with their own happiness. A natural consequence of this is that happiness is increasingly being expressed through social media, like Instagram and Facebook, and specific review sites, such as booking.com. Savvy job seekers rely on Glassdoor, and B2B marketers and customers go to B2B review platforms such as TrustRadius, G2 Crowd, and Salesforce AppExchange. Why believe a persuasive salesperson, when you can check case studies and the testimonials of experts, analysts, peers, and colleagues? Sharing our likes and dislikes has become second nature and businesses do all they can for a good customer satisfaction rating. Combined with data-driven, hyper-personalized marketing and persuasive technologies, companies now have the power to really “move” customers: to directly read and influence their emotions and state of mind.

Happiness is found everywhere

Let’s have a look at a typical vacation day of a customer. We’ll call her Sarah. Her airplane has just landed in Bangkok and when she leaves the plane the flight attendants say that they hope she had a pleasant flight with them and wish her a pleasant day. When she leaves the airport, Sarah walks by a smiley customer satisfaction terminal and pushes a green button; she was content with the flight and her interaction with customs. Outside, Sarah orders an Uber and while waiting she checks the reviews on the driver – purely out of curiosity and just to be sure. After the ride, Sarah gives the driver 4 stars. He talked a little bit too much and didn’t sense she just wanted to soak up the atmosphere of the busy Bangkok streets. She wonders how many stars the driver will give her.

Standing in front of the hotel Sarah realizes how smoothly everything has gone and remembers she needs to mention she doesn’t want to eat breakfast in the hotel. The reviews and ratings on booking.com were unanimous that the breakfast was the only downside of the otherwise lovely place. Before she even sets foot in the hotel, she sees that, according to the reviews from yesterday, the hotel still hasn’t picked up on this point of critique. Quite disappointing. She quickly opens TripAdvisor to look at the top-rated tourist attractions in Bangkok. In two days she’s flying to the next city, so she only has time to visit the top three. Time flies, so she’d better get going!

Quantifying Happiness

Given the enormous opportunity to create new value, companies should pursue happiness improvements as a science and a strategy. But for most, building these improvements and connections is more guesswork than science. At the end of the day most engineers, marketers, and CIOs have little idea what really works and whether their efforts have produced the desired results. It seems only logical that since happiness and the power of the customer have taken such flight, researchers, governments, and companies have developed ways to quantify happiness.

Let’s have a brief look at quantifying happiness on 1) the societal and 2) the individual level.

1) Quantifying Happiness on Societal Level

It’s likely that you’ve heard about the often reported ‘The Gross National Happiness Index‘. This index is based on subjective questions (e.g. ‘How are you feeling?’) and objective metrics like GDP, average life expectancy, graduation rates, crime statistics, and income. In 2017 the happiest countries were (in following order) Norway, Denmark, Iceland, Switzerland, Finland, The Netherlands, Canada, New Zealand, Australia, Sweden. The unhappiest 10 countries were Yemen, South Sudan, Liberia, Guinea, Togo, Rwanda, Syria, Tanzania, Burundi, Central African Republic. (World Happiness Report 2017)

It is one of the many instances where quantifying happiness has become ‘normal’. Once pioneered by Bhutan, many governments are now looking at their Gross National Happiness as a ‘KPI’, for instance next to GDP. And, of course, ‘digital’ also creates new opportunities in the field of happiness. Yearly reports from the United Nations and the worldwide Gallup Survey are increasingly being complemented by big data-based initiatives. Take, for example, a look at the Hedonometer, which continuously measures the (un)happiness of U.S. citizens on Twitter. One of the researchers behind the Hedonometer, Chris Danford, explains their business value: “We don’t have to wait to look at statistics at the end of the year […] This sort of data is available every day. We can tell if a public health campaign to invest in school nutrition is changing the way people talk about food or engage in activities.” (OutsideOnline.com)

2) Quantifying Happiness on an Individual Level

Secondly, let’s have a look at quantifying happiness on the individual level. On this level, we find the most business opportunities. We look at new ways to automatically measure the happiness of employees and customers. These new technologies empower companies to react in real time to customers with innovations like cognitive APIs, emotion recognition, and sentiment analysis. Further, they offer the promise of insights into the real inner feelings of a customer. Expectations for this “happiness measurement” market are very high: it is estimated that the broader market, the “effective computing” market, will grow from $12.2 billion in 2016 to $53.98 billion in 2021. (MarketsAndMarkets)

Measuring happiness real-time and creating feedback loops in activities is the new trend. Companies are learning from and reacting to the emotional states of their employees and customers. This can be viewed as a whole new movement, but also as another variable in the already rich persuasive technology scene where we want to understand every move the customer makes. We are already altering interfaces continuously and measuring the changes in view-through rate (VTR), click-through rate (CTR), Net Promoter Score, shopping cart abandonment rate, etc. And the frontrunners are already creating psychological profiles and digital twins of their users.

The business value seems obvious. Harvard Business Review summarizes: “After a major bank introduced a credit card for Millennials that was designed to inspire emotional connection, use among the segment increased by 70% and new account growth rose by 40%. Within a year of launching products and messaging to maximize emotional connection, a leading household cleaner turned market share losses into double-digit growth. And when a nationwide apparel retailer reoriented its merchandising and customer experience to its most emotionally connected customer segments, same-store sales growth accelerated more than threefold.” (Harvard Business Review)

One of the success factors of these new happiness metrics will be the height of intrusiveness. If you think of intrusiveness on a scale, then brain- computer-interfaces to measure positive emotions are at the far end and regarded highly intrusive. (Even when there’s no operation needed, in the early stages you will likely have to wear something on your head.) At the other end of the scale, the low-intrusive level, you may find real-time text analysis on Twitter, to measure the sentiment around a certain event or product. Measuring emotion in your voice while talking to a call center agent can be regarded as low-intrusive, just as measuring facial expressions in stores or measuring the likes and the star ratings people voluntarily give on social media. Wearable bio-feedback tools, such as the Fitbit fitness tracker, are increasingly trying to measure stress and differ wildly on the intrusiveness scale.

These services and products let you gather actionable, real-time insights about your audience’s reactions to your content. At this moment these emotion recognition tools are mostly used for security, customer service, the health sector, and marketing. Newly emerging commercial usages can be found at insurance company Lemonade where algorithms are being used to determine if the client is telling the truth in his or her claim. Or electronic billboards which can be adjusted in real- time to reflect the emotion shown by the audience. And why not make your new chatbot or VPA sensitive to the emotions that can be heard or read between the lines when interacting with a customer? This way it is possible to customize recommendations based on individual moods and preferences.

In the health, sector emotions can be tracked over time to give a patient more insight into his or her inner feelings. Hitachi has been experimenting with measuring happiness for years now and has created innovations like a credit-card size wearable device that measures a variety of variables like movement, and who-talks-with-who. The result of a study from Hitachi measuring productivity in a call center was that happy employees performed 34% better than unhappy employees (of course this is not the whole happiness story, just think about how misery can inspire writers and musicians). In the Netherlands, there is another interesting experiment going on in the popular bar-street Stratumseind in Eindhoven. Using cameras and other sensors, the emotion of the crowd is measured and acted upon accordingly when the atmosphere gets negative or aggressive, for example with a change in street-lighting.

Concluding bullet points

• We live in an age where we want to quantify, analyze, and understand every breath and every move the customer takes and makes. (And let’s not forget the customer is also really interested in himself or herself; people want to increasingly measure and control their physical and mental health.)
• The examples clearly show new opportunities for understanding the customer, but it is also clear it’s still a field full of pioneers.
• There are still many questions regarding the ownership of the gathered data and where the privacy boundaries lie. It will be incredibly interesting and important to see how the debate on the ownership of data relating to our own bodies, facial expressions, and spoken and typed words will take form.
• Gross National Happiness and related concepts have established themselves in our lives. The wellbeing of our society is increasingly being seen as an important goal, next to GDP and economic metrics.
• Incorporating big data is still in an experimental phase, but the interest is certainly there and the first projects are inspiring. The relevance for companies will probably lie in cross-pollination from new insights in quantifying happiness on a societal level to quantifying the happiness of the customer and employee.
• And maybe, as this domain of research will grow, the amount of details and found correlations will also grow so it will be clearer what the ‘dollar to happiness rate’ of companies will be.