Personalizing the Customer Experience: Getting in Touch through Context-Based Information
A funny thing happened on the way to 2016. After decades of asking us to speak to it in its own language, our computers began making great strides in their ability to converse with us in our own language. Advances in natural language processing are making both text and voice interactions more and more like a conversation with a friend.
And that transition is revolutionizing not only the way each of us uses our various devices but – importantly for digitally active businesses – customer experience management as well. Almost without noticing it themselves, consumers have come to expect – or rather demand – consistent, streamlined, and personalized interactions at every touch point, across devices and channels.
One result of that has been that carefully crafted and engineered context-based information has become an increasingly critical aspect of the customer experience in digital commerce. No longer can various channels – be it websites, social media, or mobile apps, for example – exist independently of one another, effectively fragmenting both content, messaging, and communication, and undermining the continuity of the customer experience. Such disruptions and frustrations are nobody’s recipe for business success.
Not every customer interaction is a sale, but every one of them is a customer experience
It was Will Oremus, senior technology writer at Slate, who traced the evolution of natural language processing (NLP) from the earliest days of computing through keyword searches to the emerging conversational technologies that play an increasingly central role in personalizing the customer experience.
Marketers have long noted that, sale or not, every time a customer brushes up against a business touchpoint, that customer has had some kind an experience – good, bad, or indifferent. NLP has become a powerful tool for tipping the scales of customer satisfaction heavily in the “good” column because it takes the burden of effective communication off of the customer. Instead of having to adapt to, say, the stilted language of keyword searching, the customer only has to seek and receive information in his or her “natural language.”
It’s not perfect yet, perhaps, but NLP has already achieved remarkable results and has become an essential element of personalized customer experience management in the digital marketplace. As might be expected, Google has been the industry leader in advancing natural language search functionality, but AI assistants such as Apple’s Siri, Microsoft’s Cortana, and Google Now have become a part of daily life, and chatbots are routinely used for a wide range of e-commerce interactions.
In fact, it would be difficult to imagine a future for e-commerce in which NLP does not play a central role in shaping the customer experience. At nanorep, an industry leader managing the digital experience, natural language search is seen as the key to delivering satisfying and personalized customer experiences by making it easier to understand the customer’s intent when asking a question. Context is critical because language differs from person to person, of course. Not everyone will phrase a query in the same way, but we do have one thing in common: we all want to be understood.
Given the variations in the way people use human language, nanorep emphasizes the need for a system to have the capacity to sense, think, learn, and act upon not only the specific words used. In order to properly interpret the customer’s intentions and meaning, nanorep software uses artificial intelligence to discern what the words mean within the context of a particular query or interaction.
Customers approach businesses through multiple messaging interfaces such as Facebook Messenger, Slack, Telegram, Kik, and others, and nanorep’s NLP solution integrates with these through its Service Bot solution that further breaks down potential language barriers to provide a consistent self-service experience.
The right answer at the right time
One measure of how adept NLP has become at discerning context and understanding a query can be found in enhancements to the search engine Bing, which is capable of “continuing the conversation.” That is, you can ask follow-up questions to your original query and they won’t be treated as separate interactions. For its part, Google touts improvements in search technology that make it possible for search engines to understand complex, inter-related multi-faceted inquiries. As one example, Google points to the ability to answer a simple question such as “Who was the U.S. President when the Angels won the World Series?”
Similarly, nanorep’s NLP is extremely sensitive to context that the same question, phrased in exactly the same terms, will elicit different answers depending on the product the questioner is viewing.
Consider what that means for the customer in terms of simplicity, efficiency, and overall experience.