How conversational AI gives you a competitive advantage
6 min read
With the advent of personalized products and on-call delivery, customers have come to expect a new standard experience: fast, easy, accurate, and personalized. Accomplishing this can be hard without sacrificing your standard workday, since the data processing required to meet these needs is immense. Luckily, AI customer service chatbots can utilize this information faster and more accurately than humans, finding insights and automating communication to deliver an enriched customer experience. If you invest based on these improvements, you’ll find that implementing these tools delivers a powerful competitive advantage.
The conversational AI advantage
As shown in the diagram above, chatbots are comprised of a series of systems. In practice, these interwoven elements allow access to and processing of data for businesses and their customers, creating a seamless and informative conversational experience. At Logic20/20, we understand that all four systems are necessary to produce an effective and long-standing business solution. For businesses and their customers, chatbots utilizing the entire pyramid above can deliver a handful of key improvements.
Diverse business benefits
Save time and money. Automated support is available 24/7 and able to handle simple requests, allowing customer service representatives to respond to concerns more quickly and lowering overall resolution times.
Lower cost of customer care. This is a high-impact benefit for businesses, since customer care is an expensive operating cost. Chatbots can handle a higher volume of requests than humans can, provide the relevant and correct information faster, and increase accuracy and complexity over time.
Interactive brand messaging. AI as a brand messenger is woven into our daily lives in the form of Apple’s Siri, Microsoft’s Cortana, and Amazon’s Alexa. Chatbots allow you to follow this lead and personify your brand, moving beyond static display ads, web copy, or paid social to create a truly interactive experience.
Increased tNPS. With chatbot messaging, brief tNPS surveys can be done at the end of the chat, providing a quick and easy way to gauge the quality of your customer’s experience. Even if you choose to query your customers some other way, your tNPS score will improve based on the ease and productivity that chatbot messaging provides.
Personalization. Using personalized data like location, preferences, and account history, the machine learning behind chatbots can create a heavily personalized chat experience for every customer. When the ai chatbot has established these customer characteristics, they can provide highly relevant information and recommend next steps based on the customer’s best interests and/or wishes. This contributes to upsells and a reduced need for further interaction. When relevant information is gathered and implemented effectively in the customer’s first conversation, their questions are answered properly, eliminating the need for them to contact customer service a second or third time.
Increased accessibility. Increased availability improves the customer experience before it even begins. Customers can interact where they are most comfortable: in mobile chat. They receive answers to their queries instantly and can skip waiting in long phone queues. Chatbots help them engage in a convenient and easy way.
So chatbots are good for your business and your customers, but how do they work?
Making it happen
Chatbots monitor CSR/customer conversations using natural language processing (NLP) and recommend content to support the exchange. They can also support CSR’s directly in conversations independent of any customers, answering direct CSR queries. With proper artificial intelligence training and thorough integration of resource systems, chatbots deliver a smooth and seamless customer experience.
After the machine learning algorithm is created and the basic framework for the chatbot is established, developers integrate intent detection. Intent detection connects common customer-entered keywords such as hours or returns to specific responses, establishing standard exchanges for the bot to use when it interacts with humans. To accommodate the emotional aspect of human interaction, sentiment analysis helps bots analyze text for customer state of mind, flagging those that should speak to a human immediately. In action, this allows customers to be routed quickly, minimizing delay and frustration. The process of training these machine learning algorithms develops three important conversational elements:
Complexity. Chatbots learn to process increasingly complex queries through continuous learning from historical chat and conversation data.
Speed. As their experience grows, bots can more quickly provide relevant content, tapping into up-to-the-minute data sources and conversational understanding.
Perspective.Machine learning has a uniquely holistic perspective, one comprised of numerous rich and historical data sources. Combined with incredible speed, this perspective allows chatbots to recognize complex data patterns that humans otherwise may not have found.
Artificial intelligence and chatbot messaging are on the forefront of customer service and business operations and are paving the way for many businesses that are looking to use voice channels in the future. The competitive advantage gained by integrating these tools now can position businesses well as the intersection between technology, industry, and human experience continuous to evolve.
Interested in conversational AI for your organization?
Read about how to integrate it smoothly.
Lionel Bodin is the Director of Digital Transformation at Logic20/20. He manages highly complex, multi-faceted digital programs related to CRM systems, cloud and on-prem implementations, Big Data, and more.
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