Emotions are the driving force behind every decision. When we’re sad because of a breakup, we buy ice cream. When we’re excited about an event we went to, we buy memorabilia. When we’re scared for our safety, we buy personal protection training or equipment.
As Dan Emodi, a technology-marketing veteran, explained, “Understanding emotion applies to almost everything we do, from working out to understanding brands to providing service and call centers to interacting with our loved ones.”
Emotions in many ways are the book ends of the customer journey. It’s because of an emotion tied with a need that they search for a solutions, and at the end of their journey they should experience emotions associated with satisfaction. With emotional analysis, you can understand your audience like never before by reaching a new depth of granularity in customer behavior, market, and competitor data.
Why is Emotional Analysis Important Social Analytic?
Your business began in order to solve a need or want and you continue to solve it today. Over time, you’ve determined buyer personas based on details like geographical location, income, likes and interests, gender, age, etc. But how many of those demographic descriptions say what emotions drive customers toward your product and which emotions lead them to complete the goal of your strategy, like conversion.
Studies have shown that there are three key elements to successful customer experience (CX) strategies, which focus on the customer journey and customer relationship management:
- Success- Are they able to do the things that they want to do?
- Effort- How easy or hard is it to do the thing they want to do?
- Emotion- How did they feel about it?
When customers come to purchase your product or service, they expect to complete the purchase with little effort. Yet, as the studies found, those two factors didn’t assist as much in generating brand loyalty as they’d supposed. What they did find was that CX strategies focused on instilling positive emotions in their audience and associating those emotions with their brand proved to have the biggest impact on loyalty.
The benefits of emotion social data analysis in a marketing platform don’t end there. A study outlined the benefit of emotion on ROI. The study evaluated the impact of customer experience improvement over a three-year period and demonstrated how loyalty behaviors (developed due to a positive emotional association with a brand) differ between the consumers who gave companies a very poor CX rating to those who gave a very good CX rating.
This study analyzed companies with $1 billion in annual revenue across 20 different industries. On average, these companies gained $775 million over three years by improving the experience they delivered to customers, that’s almost a 78% increase!
Year over year, companies can gain as much as a 25.8% increase in annual revenue when they consistently provide “good” customer experiences.
In order to provide “good” customer experiences, brands need to ask two essential questions:
- What emotion(s) are tied to the need(s) our company solves?
- How can we capitalize on or better incorporate those emotions in our strategies?
Customer experience management is all about understanding the emotions behind customer behavior, how they affect strategy and ROI, and implementing emotion marketing tactics with the goal of associating positive emotions with your brand in the mind of your audience.
What is Emotion Analytics?
Emotion analytics (EA) is a software that collects data on how a person communicates verbally and nonverbally to understand the person's mood or attitude. It is most often used to improve customer relationship and reputation management, but it can also be used for crisis and brand management as well as market research.
In the customer experience SaaS industry, companies are starting to add emotion analytics to their social listening tools. Nuvi: The Social Customer Experience Company, one of the first to equip their customer experience marketing software with emotional analysis, is utilizing Rober Plutchik’s Wheel of Emotion, simply termed the Plutchik Model, as a basis for the addition. Plutchik’s psychoevolutionary classification for general emotional responses considers eight emotions as primary due to their intrinsic involvement in triggering behavior. These emotions are anger, fear, sadness, disgust, surprise, anticipation, trust, and joy.
If you’re familiar with a social listening platform, you’ll see that it’s most commonly used for sentiment analysis, which is the analysis of social mentions to determine whether the content’s tone is positive, negative, or neutral.
While sentiment analysis is extremely helpful for brands analyzing their audience’s position or disposition towards their brand, products or services, event, etc, it doesn’t answer key questions for more granular audience analysis.
“In the world of social media analytics, we often think of sentiment as a key data point for understanding content en masse,” Jake Jenne, Software Engineer Manager at Nuvi, expounded on why Nuvi went to such great lengths to include emotion analytics in its software. “Emotion analysis is a finer-grained form of sentiment analysis that helps brands better connect with and understand their customers.”
Some of the questions emotional analysis can answer that sentiment alone can’t include: “what kind of positivity is my audience showing?”, “is my audience happy about or anticipating our new product?”, “what is it about our event that’s surprising people?”, or “why are customers angry about our announcement?”. This list of questions can go on and on.
Another benefit of emotion social analytics in conjunction with sentiment analysis is that a single emotion on both ends of the sentiment spectrum can be analyzed. For example, fear is usually considered a negative emotion. However, in certain fandoms or time periods, such as Halloween, fear is more likely a good or positive emotion.
Sadness is another emotion that can be both positive and negative. Let’s take the phrase ‘I’m crying’, for instance. On the negative side (the one we’d expect), someone might say, “My boyfriend and I broke up and I’m crying as I watch the Notebook and eat ice cream”, while on the positive side, someone might say, “I just pulled the best prank! I’m crying so hard right now.”
No matter your question or analysis goals, emotion analytics help enterprise brands filter social data so emotions can be analyzed alongside sentiment for deeper insights.
How to Use Emotion Analytics
Emotion analytics, as with most data sets, will vary in its use or in the approach taken to gain insights depending on the strategy or event being analyzed.
For example, during an event or product launch, you may have a goal of generating high emotion metrics such as surprise, anticipation, joy, and trust. If you see these emotions at the levels you’re hoping for, then your strategy has been successful, but if emotions of anger and fear are more prevalent, then you know something is wrong. Emotion analytics can help you find the core of the issue quickly so you can remove it or adjust your strategy accordingly.
As a further example, we used Nuvi Language Engine's emotion analysis to unpack the feelings behind the discussion of Halloween in 2020. Halloween is a holiday of high emotions—fear is at its center, but this spooky season brings plenty of people joy, too.
The most frequent emotion that appeared in the monitors was Anticipation; social media users are eager to celebrate the upcoming holiday. Most of the anticipation is due to costume discussion:
Next was Surprise: this elevated score could be due to expressions of astonishment at governmental suggestions of how to still enjoy Halloween while not spreading COVID as well as expression shock at how people are mistreating Dia de los Muertos.
Joy came next. In an effort to enjoy the holiday and still maintain quarantine regulations, many are hosting or participating in online events such as customer contests.
Sadness was also high this year due to COVID restrictions not allowing traditional celebration, disappointment that adult nurse costumes are acceptable at Halloween but not at any other time or setting, and people expressing their desire to purchase a costume but don’t have the money to afford one.
As we can see across these top four frequent emotions, Americans are understandably upset that the continued health crisis will put a damper on their Halloween celebrations. This is generating a lot of focus on costumes as that is one of the only holiday activities that are quarantine friendly.
We can also see that most of these examples above don’t have the sentiment we’d think would be associated with the emotion category. Surprise is the best example. Most people tend to think of surprise as a good emotion, or on the happy side of the spectrum, but, in this Halloween monitor, that isn’t the case. Most of the surprise was associated with negative sentiment. If we’d just been analyzing sentiment, Surprise and Sadness would be lumped into the negative category and it would have taken manual filtering to determine the general discussion points that made up that sentiment.
Emotion analytics can be used for more than just social listening, which is primarily used for market research, brand management, and strategy development. Nuvi has shown that it can be used for customer engagement, content marketing, and review management, among many more.
Join our webinar Designing Empathy Experiences: The New Way to Customer Loyalty and ROI to learn more about emotion analytics and how important it is for business today and in the future. The webinar will be held on October 29th at 10 am MDT and guest speaker Dr. Markus Giesler, Professor at York University and regular consultant for global brands like Apple, Google and BMW, is an expert in the emotion economy for businesses.
