“The customer experience is the next competitive battleground.”
Jerry Gregoire, the former CIO of Dell, got it right when he said this. In today’s world, where consumers have more choices and information at their fingertips than ever before, providing a stellar customer experience is critical to success.
A top-notch customer experience goes beyond simply providing great customer service. It means focusing your entire organization on meeting your customers’ needs by collecting their feedback, analyzing it, and – most importantly – acting upon it.
Of course, this is easier said than done. Collecting customer data is easy enough; in fact, most companies have more customer data than they know what to do with. The biggest challenges are identifying what types of customer feedback will yield the most fruitful, actionable insights, and extracting those insights from the data.
This is where natural language understanding comes in. Natural language understanding combines artificial intelligence (AI) and natural language processing (NLP) to understand what people actually mean when they speak or write. It enables machines to pick up on the context beneath all the nuance, jargon, and slang inherent in everyday language.
Natural language understanding makes it possible for companies to more quickly and accurately analyze their customers’ text-based feedback, including open-ended survey responses and product reviews. They can then identify patterns and trends within that data and take action. More and more companies are realizing that implementing a natural language understanding solution provides strong benefits:
NLU unlocks the richest and most detailed source of customer feedback available.
Quantitative measures such as NPS scores and 5-point scales are easy to analyze, but they can only take you so far. They won’t help you uncover root causes of satisfaction or dissatisfaction, because they don’t give customers the opportunity to tell you why they rated your company the way they did. Customers offer far more nuanced and specific feedback on your company via product reviews, open-ended survey responses, and social media posts – in other words, in the form of unstructured text data. Natural language understanding makes this rich source of data accessible.
It uncovers critical customer insights more quickly than traditional analysis methods such as hand-coding.
Until recently, the high investment in time and resources needed to hand-code or ma
nually read through customer feedback data hampered companies’ attempts to analyze this data. As a result, many companies only processed small subsets of their text data, and some companies stopped asking open-ended survey questions entirely. New AI-based methodologies – especially natural language understanding – have significantly sped up the analysis process, enabling you to understand and take action right away.Ultimately, analyzing text-based data and acting upon the insights you uncover improves both customer retention and revenue.
The Aberdeen Group[1] recently found a clear, quantifiable link between acting upon customer feedback and business performance. Companies who integrate customer feedback across all channels and operationalize those insights retain 55% more of their customer base and enjoy an almost 10-times greater year-over-year increase in annual company revenue than those who simply collect – but neither analyze nor act upon – customer feedback.
The benefits of natural language understanding are clear. Your customers’ voices will reach you clearly and quickly, you’ll be able to take action right away to meet their needs, and customers will reward you with increased business and loyalty. Sounds like a win-win situation to us!
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[1] Aberdeen Group. (April 2015). The Business Value of Building a Best-in-Class VoC Program. Omer Minkara.
