We recently attended IBM’s World of Watson conference in Las Vegas, which addresses ways that brands can use data science, advanced analytics, cognitive computing and artificial intelligence solutions like Watson to extract new insights, enhance their expertise, and improve customer experience.
While the possibilities for using Watson in business seem endless, two that resonated the most with us based on conversations we’re having with brands were AI conversation modeling—or chatbots—and AI predictive modeling.
According to a recent survey carried out by Facebook IQ, 63 percent of consumers are using messaging apps (in this case, Facebook Messenger) to contact companies, find information, and buy products. And brands are beginning to roll out chatbots to help them deal with the influx of customers reaching out.
As a result, we see a wide variety of applications in which our clients can use chatbot technology in order to help reduce costs and increase sales – including product registration, customer service, and cross selling/upselling products and services (such as extended service plans) through a portal with an e-store. For example, imagine a chatbot effectively and accurately, in several different languages, handling almost half of your customer service inquiries, saving your customer service team hundreds of hours and you thousands of dollars.
A growing number of customers currently prefer using these types of channels when it comes to communicating with businesses. Recent research shows that 49 percent of people would rather contact a business through messaging instead of speak to a live human via phone.
While many brands may see chatbot development as expensive, time consuming and resource intensive, the technology, like that of Watson, is rapidly improving to allow a brand to have an intuitive chatbot built in several days versus several months. In addition, the learning and language of chatbots have become so natural that customers either don’t realize it’s AI, or they realize it and they enjoy their experience so much with it that they don’t care.
Now consider predictive modeling. Registria’s customer data shows that customers who interact with brands through events like product registration tend to be more brand-loyal “Super Buyers” across the globe. Imagine identifying and layering in an AI feature that intuitively connects with these buyers and offers them products and services that are timely and relevant to them.
At Registria, as we prepare for the launch of our Facebook Messenger app, we realize this launch is just the tip of the iceberg in terms of how we can help brands connect with customers. We are excited to begin working with Watson AI communication and predictive modeling technologies in order to further explore and roll out new ways to broaden and deepen customer connections.