Editorial
The Gist:
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Changing customer experience. As apps and kiosks replace traditional interactions, customer service is defined by the digital user experience.
Customer behavior reflects emotion. How your customers interact with their devices reveals a lot about how they feel during that moment.
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Tap into tech. New solutions combine data with AI and other tools to deliver a better digital experience and improve customer satisfaction.
Today it’s more critical than ever to understand not only what your customers do but also how they feel. As a recent Qualtrics survey found, feelings are the top driver of consumer loyalty.
When customers feel they’re a priority, brands benefit from increased consumer loyalty and growing revenue. On the other hand, more than half of customers said they would leave for a competitor after just one poor experience, according to Zendesk research.
Fortunately, every interaction now offers the opportunity to gain insights into customer sentiment, which can help brands use actionable data to elevate the customer experience.
The Challenges of Traditional Sentiment Analysis
If you want to capture customer sentiment, there’s still a lot of value in many tried-and-true methods, from online surveys and reviews to live chat and social media monitoring. But these tools aren’t giving you the full story.
First of all, surveys and reviews typically have a relatively small sample size. Perhaps more importantly, the people who choose to answer a survey or post a review are typically those who have something to say. They want to praise a customer service rep or (more likely) complain about an expired discount code, long wait times or some other issue. People typically only share their thoughts when they’re frustrated. This scenario leaves a significant gap between the customer sentiment you’re seeing in the data and what your customers are actually experiencing.
Related Article: Social Listening: Key to Understanding Customer Needs and Preferences
Using Technology to Understand Customer Sentiment
Consumers simply don’t have as many traditional interactions as they once did. One report found that nearly two-thirds of consumers in the U.S. prefer self-service checkout. Even in B2B sales, traditional models are changing. McKinsey research found that 95% of buyers “are willing to make purchases without interacting with salespeople.”
As more customer interactions occur on kiosks, apps and other digital platforms, leading organizations are tapping into key performance data from applications and devices that infer customer sentiment in real time.
Behind the fancy technology is a fairly straightforward concept; you’re simply using performance metrics from customer-facing platforms to infer people’s emotions. The result is a customer service expert’s dream: a real-time model that captures your customers’ emotions as they happen.
Here are a few of the most popular tools and technologies that are helping customer service experts get the information they need:
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Data collection layer: Integrated sensors and device logging capture interactions and metrics around screen taps (including frequency and force), swipe attempts, navigation patterns, transaction and response times and abandoned sessions.
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Machine learning and artificial intelligence (AI): Advanced computer models can detect patterns in interaction data and be trained to recognize when a pattern indicates a specific emotion (i.e., frustration or stress).
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Customer service dashboards: By collecting endpoint data about system health and key metrics, you can create a dashboard with real-time insights and alerts about how device performance may be affecting your customers’ emotional states. Use this information to support UX/UI improvements and staffing decisions.
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Integration with customer service and system response: Automated adjustments and behavior-based UI modifications can offer assistance, a help prompt or even a simplified navigation when they sense negative customer sentiment.
Related Article: The Emotional Drivers of Customer Experience
Get Your 'DUX' in a Row to Improve Brand Outcomes
As you continue to evolve your digital user experience — what I call the “DUX” strategy — consider the many benefits of using these new tools and technologies. By converting raw interaction data into actionable insights, you can act faster and drive more positive brand outcomes. These outcomes include:
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Improved customer satisfaction, loyalty and retention: A seamless interaction shows customers that the brand values their experiences, which leads to higher customer satisfaction levels and positive comments across your brand’s social media channels.
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Higher productivity, efficiency and throughput: Quickly addressing digital frustrations reduces downtime for both customers and support teams. Don’t forget about your employees’ feelings, since “well-supported employees deliver better customer experiences.”
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Lower customer support costs: Do you want fewer repeat contacts and less strain on your resources? More efficient resolutions reduce your overall support costs.
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Increased conversion rates: Smooth and hassle-free digital interactions mean more completed purchases and interactions with brand offers, which improves both sales and engagement metrics.
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As you learn more about the future of sentiment analysis, think of these technologies as new, more powerful tools that let you clearly understand and respond to your customers’ emotions.
Editor's note: The featured photo is licensed under the Creative Commons Attribution 4.0 International license.
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