With nearly half of consumers reporting they would pay a higher price for a product in exchange for better customer experience (CX), there’s no understating the importance of driving loyalty through CX. With technology such as loyalty cards, chatbots, etc., brands have more data available about the customer journey than ever before. However, for many brands, this massive trove of information may be overwhelming, begging the question: How do I use this data to improve CX and meet customer needs?

By merging Data Analytics and Artificial Intelligence (AI) with the human touch, looking at sentiment for its emotional value rather than numerical value, and creating better employee experiences (EX) through data-driven processes, brands can create CX strategies that will help them compete within their industries.

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Merging Technology with the Human Touch

Creating a customer service experience that pushes the customer journey in the right direction and drives word of mouth referral is critical to brand success. In fact, nearly one in three (30%) consumers say they would post a negative review online to prevent others from shopping with that brand. With critical data points recorded from customer service interactions nearly every minute, it can be difficult to figure out how to use that slew of data to create meaningful results that improve CX.

Data management has become a major part of our industry and is even creating a path for more jobs. While AI helps us collect, sort and understand the data, people are still needed to create and continue to help evolve the algorithm, as well as provide recommended outcomes of the results. AI and Data Analytics can help point customer service managers to problem points within in the customer journey, but a person still needs to create the right plan of action to address the problem.

Understanding Sentiment as an Emotion – Not a Number

Emotions run high during customer service calls, whether it’s frustration and anger or even happiness and relief. While many brands categorize sentiment as a number, it’s tough to quantify emotions in a purely numerical way. Instead of working to decrease your sentiment score, for example, from a 10 to a 7, looking at the specific emotions such as anger or empathy and creating specific goals for those emotions can create a more meaningful, yet still quantifiable solution for measuring sentiment.

Using Data Analytics and AI to identify moments of heightened emotion through keywords and phrases allows customer service agents and managers to improve their skills through real-life examples. For example, using AI to flag higher agitation by the customer and scoring responses – such as ownership and active listening – allows associates to understand the triggers as well as best practices for representing the proper brand voice.

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Improving Employee Experiences

Nearly all (95%) employees believe that the EX impacts CX, and therefore to improve the CX brands must start by improving experiences for their employees. One major area that impacts EX and overall employee satisfaction is training. In fact, more than a third (37%) of employees say they would leave their current job/employer if they were not offered training to learn new skills. It’s critical that managers provide their employees with training in areas of growth that help them progress in their field and challenge their skill sets.

To improve CX, specifically within customer service, brands should consider implementing AI and Data Analytics to provide employees with real-time feedback. Implementing this technology also helps improve training and coaching for employees. By using AI to flag specific phrases and words within a call or interaction, managers are able to recognize employees’ strengths and weaknesses and ultimately provide the training they need to improve and grow their role.

By using AI and Data Analytics to pinpoint moments along the customer journey where CX could be improved managers and leadership are able to create solutions that improve the experience for both employees and customers.

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