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[Estimated read time: 3 mins]
What does a personalized customer service interaction look like? Does your picture include a live agent? Until the not-too-distant past, it had to, because only a human had the intelligence and decision-making abilities to pull off personalization.
But that’s all about to change with the latest advances in digital self-service.
Web self-service started out with the dreaded FAQ list, which was essentially a company’s best guess about what its customers needed to know. Those guesses were rarely accurate, though, and as time passed and new questions popped up, they would be tacked onto the end of the list. Few companies took the time to refine or even organize their FAQs, so customers had to work hard to find an answer—an answer that was often incomplete or out-of-date.
Remember the pop-up avatars from a few years ago, like this one? They were the first stab at virtual service that felt like a conversation with a human, but they could only respond with pre-programmed answers. If you didn’t find the magic combination of words to prompt one of those answers, the avatars just gave you an 800 number to call. So they didn’t make much progress toward the goal of providing self-service that would reduce contact volume without sacrificing the customer experience.
Today, most companies have turned their FAQ lists into searchable, indexed knowledgebases. And many have added a virtual agent that achieves what the avatars never could. Because they use natural language processing (NLP), they can understand the intent of a question, not just the keywords it contains. They then search the knowledgebase for you, and return an accurate and relevant response, not just a list of possibly related topics.
For example, a customer can ask “What do I do if I don’t like the color of my sweater?” and receive a response like “If you aren’t completely satisfied with the product you purchased, click here to print a return label.” Without NLP, they would likely see a list of knowledgebase topics about colors and sweaters.
We’re starting to see the adoption of bots for web and mobile self-service, which will eventually blow everything else out of the water. Bots use artificial narrow intelligence (ANI) to perform specific tasks in place of a human, and are equipped with deep learning technology that allows them to continually improve their performance.
Forward-thinking companies are providing personalized self-service with bots that connect to their CRM to pull in customer information, purchase history, previous interactions, and more. When that context is added to a customer’s current request, bots can deliver not just the one right answer, but the one right answer for each individual customer.
“[Bots] in the path to purchase can save the sale and the customer’s loyalty.” -Brendan Witcher
Let’s take another look at the example above, of the customer who asked “What do I do if I don’t like the color of my sweater?” Both a virtual agent and a bot would use NLP to identify that the customer is actually asking about product returns and exchanges. And they both would search the knowledgebase to find the best answer.
A bot goes further, though, by looking at the question in the context of the information it pulls from the CRM and personalizing the answer. So while the virtual agent would respond with information about returning a product, the bot might reference the specific sweater ordered, list the other available colors to encourage an exchange over a return, and even offer suggestions for coordinating pants or accessories.
By personalizing the self-service they offer, companies can do much more than reduce contact volume. They can increase conversions and up-sells and improve customer retention.
Drive satisfaction and online conversion with knowledge management and web & mobile self-service.