Is emotion the most important CX indicator?

In Michael Harris’s article, “Neuroscience Confirms We Buy on Emotion & Justify with Logic & yet We Sell to Mr. Rational & Ignore Mr. Intuitive” Harvard Business School professor Gerald Zaltman says that 95% of our purchasing decisions take place in the emotional subconscious, which is the real star of decision making.

Marketing and Sales have made it their raison d'être to both understand and play with this, but what happens to that emotion post-purchase, or after brand interactions? Are we as in tune with how our customers feel after the transaction or communication has taken place?

In Jeff Callino’s article in Forbes – “Three reasons why emotion could be the most important CX indicator” he writes:  

Many organizations today are already attempting to capture and understand customer emotion. We see this most in the execution of post-conversation surveys. You know the ones — after ending a conversation with a customer service agent, you receive a survey request about your experience. The intent of these surveys is to uncover how you felt about the experience and, in turn, help the brand understand what could be improved for the future or your likelihood of purchasing again. 

While the intention is fair the reality is that in the last 20 years, the median response rate for feedback surveys has dropped from around 20% to just 5%. – TruRating research.

Is it then a given that we are missing the majority of customer data and learning?  

Knowing that these surveys capture the slightest moment in time, affording us a very slim window into customers' minds and satisfaction, then YES! How do they feel in a day, a week, or after a month of using your product or service, how is their brand affinity then? Are we measuring anything after the fact?

With modern websites, we can tap into customer emotion at the source. For instance, we can use pop-ups to ask, “is everything ok,” “can we help you today?,” “do you have everything you need?” triggered when the user seems lost, and endlessly scrolling, but what about on our other owned channels or indeed channels like review sites, social media groups and so on?  

With stats like:  

• “90% of consumers worldwide consider issue resolution as their most crucial customer service concern. (KPMG), and  
• After more than one bad experience, around 80% of consumers say they would rather do business with a competitor. (Zendesk)”

It becomes crucial to capture any issues, or bad brand reflections as soon as possible, enabling us to showcase our amazing Customer Service.  

Your most unhappy customers are your greatest source of learning. Bill Gates

All sounds perfect, right!? But how do we gain these deeper customer insights, especially at scale?

With the use of qualitative research, we can gain more profound knowledge of customer satisfaction and brand perception. Research such as, contextual interviews, observational interviews, and focus groups typically involve a small subset of customers and sometimes takes place in an environment where the true feelings are masked. Consideration must be given that again these are the views and perception of “the few,” not “the many,”

Brands need to deal with more vocal and emotive customers than ever before, and these comments are not made in controlled environments with certain questions and criteria... No, No! These are driven by feeling and experience, both good and bad, therefore, uncovering these post-experience customer mentions, become especially important.

This research used to be an extremely costly exercise as you had to have members of staff consistently scouring the web looking for brand mentions in forums, on review sites, social media channels, and so on. Luckily for all of “Brand-kind" Emotion AI saves the day, it is one of the ways that brands can delve into customer emotion, accurately, efficiently, and most importantly, at scale.

By using Emotion AI, you can directly identify the customer feeling associated within your different audiences and use this knowledge to inform everything from customer service, product teams, service designers, UX teams, marketing, and sales.  

In fact, there are so many diverse uses for this new source of data/insight. We can see in a Case Study by McDonald Bulter and Pulsar “Using social listening for account-based marketing success - https://bit.ly/3tPwn9j”, by implementing these listening techniques they were able to build a client pipeline by using the data to define their demand generation campaign.  

The objective of the campaign was to:

• Identify what sites and channels (publications) were being used by partners and competitors alike to consume topics relevant to the client’s focus offering  
• Understand the share of attention the main keywords received in the industry overall  
• Understand how that share of attention was split when segmented by client and competitor mentions  
• Use these insights to develop early-thinking content considerations that could help bring the client top of mind”

The conversation was tracked over the course of 4 months, yielding approx 500,000 mentions (tweets, news articles, blog and forum posts) of the keywords. The analysis yielded answers to questions such as:  

• Where is the conversation taking place?  
• What topics were dominating the conversation?  
• Overall keyword cluster  
• Client keyword cluster  
• Competitors’ keyword clusters”

Currently they are in the process of building a content marketing strategy driven by the data and guided by flagged topics, providing content that is customer & problem specific, offering a huge value add.

With this demand generation, they are building a framework to educate and provide customer value that lasts. With Emotion AI they can judge the message, call to action, tone of voice and timing, to ultimately build stronger relationships via better CX.  

The uses and benefits are endless but we must always temper our praise with, while these AI-driven platforms are amazing at reading and interpreting your customer’s feelings, helping to quickly gauge if your brand is doing the right or wrong things, they are still just tools.

Whether it be for business strategy, or customer experience design, data like this does give you a deeper understanding of your overall performance, and customer sentiment, but as with all data tools, the real success driver is what you do with the insights.

If we are aware that when asked,  

“65% of customers said they have changed to a different brand because of a poor experience.” (Khoros)  

it becomes sensible to at least test and see if these tools can give you the chance to cut out poor customer experiences quicker and make them better. If nothing else, the data gained will empower marketing, sales, and customer service to make more strategic, data-driven decisions on the content, format, or Tone of Voice for every brand touchpoint.  

This is not just all about customer churn or bad customer brand mentions to dish out to customer service agents to deal with, it is so much bigger. By guiding you toward embracing customer emotion and sentiment your business is in the position to create better customer touch points, provide solutions to customer problems, remove any harmful friction points or to make your digital products better and easier to use.  

Understand where to get this data and how to use it, and you have the power to promote true customer-first practices across your whole business, increasing customer lifetime value, referral, and brand advocacy, just to name a few benefits.  

We will sign off with this statistic from Hubspot and hope it spurs you onto improved customer experiences -  

“An increase in customer retention of merely 5% can equate to an increase in profit of 25%. This is because repeat customers are more likely to spend more with your brand — 300% more, to be exact — which then results in your business having to spend less on operating costs.“

And, if we had a mic we would drop it right about.... Now!

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