The SMS Self-Service Revolution
How machine learning will redefine customer care in 2016
Last month we covered 4 Powerful Reasons to Text-Enable Customer Care. Interacting with a customer care agent via SMS is a proven way to reduce costs while delivering a superior customer experience. This month we look at extending this paradigm to include virtual agents using state of the art natural language processing algorithms – otherwise known as machine learning. Virtual agents have enjoyed tremendous growth in 2015 with spectacular launches of services like Magic and GoButler.
These services fulfill the following need: “I want something and can you get it for me?” What if a virtual agent is used in the context of answering questions during a customer need event? For instance, you’ve just received a text message from your bank stating there has been a charge on your account. Wouldn’t it be convenient to just text back your bank requesting more information? And what if this can be done without the need for a human agent or intervention?
Machine Learning is the Future
This is a job for Natural Language Processing (NLP). NLP is a technology that coupled with SMS, is poised to revolutionize self-care. By now, most people understand what Siri does or Facebook “M”. Simply ask a question and you get an answer – most of the time it’s relevant, sometimes the answer is comical. This is NLP. There are gaps in today’s deployment of NLP-like services. In the above example, you can’t ask Siri to ask your bank for more information on a transaction that just occurred.
One sector that can benefit enormously from easy self-service is the hospitality industry. In December we looked at how hotels and restaurants can use SMS. A simple use case was requesting more towels when you are staying at a hotel. What if machine learning was able to intelligently handle 90% of requests without a human? That would save time and money.
Use Case Scenario
Let’s walk through an SMS self-care scenario to understand the benefits. You just checked into the Awesome Hotel. As part of the check-in process, you are asked to provide your mobile phone number in order to receive alerts, promotions and instant customer service. You get a welcome text message with a simple question, “How can we help you?”
This allows for easy, personal and fluid interactions with the hotel . Simply type a question likes the one below
How do I get on the internet?
Is the Wi-Fi free for guests?
What is the checkout time?
Can we store our bags for the day?
Where is the pool?
Is it possible to check-out late?
When does the fitness center close?
How much is parking?
Where can I leave my car?
What is the weather going to be like tomorrow?
All of these questions can be answered without requiring staff resources. Even better, machine learning technologies do a great job at figuring out what the “intent” of the question is and not just the keywords that are coming from the text request.
For instance, a guest can request information like; “Where can I leave my car?” or can request an action like; “I need my car”. Both feature the word “car” in the message, but the response is completely different. This is the magic of NLP.
Machine learning is an ideal companion to a robust self-service customer solution. It learns as more guest use it. With each new question the technology adapts, creating a product that almost emulates human interactions. Furthermore, there are no apps that need to be downloaded and the experience for the user is completely contextual.
Companies interested in leveraging the latest cutting-edge machine learning technology should contact our representatives at OpenMarket to see if this can help bring your customer care self-service strategy to the next level.