The advent of personalized products and services has resulted in customers coming to expect a new standard experience that is faster, more accurate, and more personalized. As the customer’s standard has evolved, the amount of raw data being processed and time-consuming activities has skyrocketed.
This is where Digital Assistants, powered by conversational AI, can utilize this information faster and more accurately than humans by finding insights and automating communication prompts to deliver an enriched customer experience. Investing in these improvements and implementing tools that support this can give your business a powerful competitive advantage, particularly by providing custom and fluid experiences for your customers when it comes to their inquiries about anything and everything regarding your business.
The roles of Conversational AI can be conversational, procedural, and intelligent by design. This is facilitated by direct interactions with the customer, but also sorting documents and providing upload portals and confirmation, real-time personalization for existing clients with specific account details that need to be remembered and implemented, and more.
Omni Channel Experience
Real time personalization
Automatic knowledge base & content creation
Predictive sales leads
Digital assistants monitor customer conversations using natural language processing (NLP) and recommend content to support the exchange. They can also support customer service directly in conversations independent of any customers by answering direct queries. With proper conversational AI training and thorough integrations, Digital Assistants deliver a smooth and seamless customer experience.
After the machine learning algorithm is created and the basic framework for the digital assistant is established, developers integrate intent detection. Intent detection connects common customer-entered keywords such as hours or returns to specific responses, establishing standard exchanges to use when interacting with humans. In practice, this allows customers to be routed quickly, minimizing delay and frustration.
Now that you better understand the use cases, let’s link them to the most prevalent organizational outcomes that conversational AI supports:
Improving customer acquisition
Increasing revenue per customer
Reducing cost to serve
Improving employee satisfaction
Increasing Net Promoter Score
Increasing in Sales Conversion Rates
The introduction of chatbots and artificial intelligence is increasing rapidly. According to Accenture, 60% of executives surveyed plan to implement chatbots for after-sales, customer service and social media. Accenture isn't the only organization projecting major movement within the chatbot. Space: Check out these very insightful chatbot stats. At first glance, chatbot technology and AI-supported conversation interfaces appear to be very similar. However, if you go below the surface, the technology couldn't be more different. Continuous improvement and the end customer experience are nowhere near in the same league
While it may look like this on the surface, these two technologies are not at odds. Although conversational AI is diverging from chatbots and is undoubtedly more advanced, chatbots will continue to perform certain needs and tasks. As you learn and understand natural language, conversational AI will evolve and become even more sophisticated. It is clear, however, that the demand for both solutions will skyrocket in the coming decades. 69% of consumers prefer chatbots for quick tasks and 70% of consumers intend to replace their visits to your healthcare provider, store or bank with virtual conversational artificial intelligence assistants.
This is a comprehensive article about natural language understanding. How it works, and the different applications it can have for businesses.