Leveraging Conversational AI as a Strategic Instrument
Today, we find conversational agents, such as chatbots and virtual assistants, everywhere – from your insurance company to online retailers to healthcare providers. Voice-based devices are invading homes and the market is flooded with all kinds of consumer devices that leverage artificial intelligence (AI), raising user fluency, as well as preferences for software applications and devices. Think of Amazon’s Alexa. The Alexa Skills Store alone has over 100k voice apps, which allow users to interact with products by simply talking to them. This quick growth in the number of voice applications in the market reflects consumer demand for the ability to just talk to machines.
Conversational platforms and technologies that enable these types of interfaces and devices are rapidly gaining adoption as organizations try to keep up with consumer preferences. However, despite their widespread use, conversational interfaces are still mostly viewed by companies as a tool for cost reduction that replaces the first line of support from a human to a virtual agent. To that end, most deployments use basic implementations with structured and pre-designed dialogues centered around frequently asked questions about a specific topic.
As technology has grown, conversational platforms have added supplemental AI capabilities, becoming more sophisticated with enhanced development and experience capabilities. The rapid maturation in the market, combined with the large base of existing first-generation conversational bots, has opened up significant opportunities across business areas to develop more complex platforms and tools. In order to differentiate themselves, organizations need to use their conversational AI investments more strategically – business leaders must evaluate conversational AI as not just an interface type, but as an enabler for larger organizational goals. To get a better sense of what that means, let’s highlight some examples of common objectives that chatbots can help address.
Use Customer Interactions to Sustain & Grow Business
The top use case for chatbots is often to increase customer interaction as businesses look to build loyalty by improving support experiences. Today, you can find a chatbot on almost every commercial website, but most have not progressed beyond the catalog-navigation conversations. The more significant opportunities lie in the customer insights that can be gathered through these digital interactions. A combination of advanced technologies, such as natural language processing, machine learning, data science and advanced analytics, can transform data-driven insights into automated, predictive, cross-selling and upselling opportunities. Additionally, integrative technologies – like robotic process automation (RPA) and APIs – can flow information and trigger actions throughout the entire business process, creating an end-to-end, fully automated intelligent capability.
For instance, when a telecom customer asks about their data usage, a virtual agent could not only provide the requested information, but also recommend a customized plan based on the customer’s consumption pattern in the last six months, while also reminding them that they are now eligible for that phone upgrade that they inquired about few months ago. This interaction automatically transforms the experience to a personalized response that potentially increases sales. Further, advanced analytics and machine learning applied to the interaction data (voice of the customer, in a literal sense) gathered by a chatbot or virtual agent can also reveal unmet customer needs and inform new product or service development. In these cases, companies need to ensure they are maintaining the security and privacy of their customers’ data.
Increase Profitability by Enhancing Productivity
Looking inward, conversational AI has a lot to offer in terms of how organizations accomplish work. Turning chatbots from purely navigational tools into truly ‘smart’ bots requires marrying the conversational user interface with a range of capabilities or services in the back end. For example, utilizing smart search, analyzing streaming data, reviewing documents, extracting relevant information and taking a control action when a threshold is met are just some of the tasks that can be automated as individual bots. An employee can then simply text, or voice chat, with a digital avatar to initiate an entirely automated business process by invoking any number and combination of smaller, more specialized bots. This kind of digital coworker—one that can sift through huge amounts of data, analyze the information and even take required action, all in a matter of seconds—lends ‘superhuman’ capabilities. The easy-to-use conversational user interface—backed by fully automated business processes and functions—dramatically improves the worker experience, while saving labor costs and increasing flexible capacity for the business. What’s more, it affords the worker the time and opportunity to upskill or take on other tasks that only a human can do.
Conclusion
Conversational AI holds tremendous promise for business, but executives need to understand that perfecting the interaction design or developing disconnected or sporadic use cases simply isn’t enough. To make chatbots and virtual assistants smarter, business leaders must have a holistic approach and defined strategy to bring the vision, and a broad set of technologies, together. This will enable companies to meet customer demands, reach the true potential of conversational AI and turn it into a competitive advantage.
