VP, Strategic CX Transformation
Many customer service interactions are now resolved through the use of bots and AI. This software enables customers to get help through natural language recognition and provides agents with the information they need to provide better customer service.
AI is used to manage customer interactions in call centers. It can be used to answer customer questions, route customers to the right department, and provide information about products and services. AI can also be used to detect customer dissatisfaction and provide solutions to improve customer satisfaction.
AI is software that thinks, acts, talks, and performs like your best human agents. Businesses possess a tremendous amount of data about their customers, and AI can process that data to extract the consumer’s intent when they contact the business. Through AI, we can determine the next best action based on the consumer’s intent, and over time through machine learning, chatbots can perform more like the best human agents.
There are a variety of technologies call centers use, but the most common are:
There is no definite answer to this question as AI still has a lot of limitations when it comes to tasks that require human interaction. For example, AI is still not capable of correctly interpreting human emotions and providing the appropriate response. Additionally, AI is not yet able to handle complex customer queries that require human expertise. Therefore, it is likely that AI will not completely replace call center agents in the near future. However, AI can be used to support call center agents by automating simple tasks such as data entry or customer profiling. This can help to improve the efficiency of the call center and ultimately provide a better customer experience.
Most companies have several people with various needs who are all looking to use AI to solve a range of problems. It can be anything from creating a more seamless customer experience, to reducing resolution times for the consumer, or helping agents work better and more efficiently. We try to combine the pain points and show companies how AI can help them achieve business results across a range of goals. A lot of executives are still unsure of exactly how AI can help their business, why they need it, what they’ll get out of it, and we help them build business cases that will answer all those questions.
Companies need to be sure they’re choosing a vendor that can grow with them. Our solutions are based on a ‘build once, deploy anywhere’ model, meaning that they use the same business logic and natural language processing across channels so you’re not constantly having to reinvent the wheel when you want to add a new channel. That also provides a more consistent experience for the consumer.
If you can offload a lot of the routine tasks to chatbots and let human agents monitor the chatbots’ performance and intervene when required, this will help dramatically improve call times and contribute to a number of other efficiencies. This will make customers happy by allowing them to self-serve, which is the experience most are after today. Automating a lot of the tedious tasks can also improve job satisfaction for agents and help them develop more complex skills moving forward.
Average handle time (AHT) will evolve into total customer interaction time (TCIT). Regardless of what channels a customer is using, or even if they’re using multiple channel throughout their journey, they need to be able to get to a solution fast, without getting frustrated.
Companies need to be transparent with their customers. This can be achieved by something as simple as a little icon in the chat window that lets a customer know they’re talking to a chatbot, or being transferred to a human agent or back to a chatbot again. No matter who is helping the customer, transparency is key.
Compared to chatbots, humans are still much better at understanding emotions or complex questions, but technology is getting better every day. For example, if you ask an airline chatbot “what is your bereavement fare, and can I take my guitar on the plane,” a human would understand that those are two separate but related questions, but a chatbot would likely get confused. Chatbots can be trained to recognize questions with multiple intents, but this will take time. The more the bot learns from humans, the more effective it becomes.
A lot of frustration around IVR comes from not knowing the consumer’s intent. Most IVR systems are based on old technology and don’t possess the business logic or natural language processing that are present in digital channels, which is why most people end up asking for a live agent. What if when customers call, they were told “It’s going to be 20 minutes to speak with a live agent – but if you’re online you can speak with a live chat agent right now instead?” We find that when offered that choice, about 25 percent opt for the live chat option. This eliminates any potential frustration by clearly managing the customer’s expectations from the start.
Chatbots will interact more with other chatbots and other brands. Think of it in terms of booking a trip–with one request, you can book a flight, rent a car, and get a hotel. Chatbots will function more as a personal concierge moving forward, but it’s going to take a lot of work to enable that future. Companies will need to figure out the handshakes between them, as well as a host of data privacy and security issues.
Companies will take a more proactive approach for their high-end customers. For example, if you’re a frequent traveler and your flight is cancelled, a representative could proactively contact you letting you know that they’ve booked you on the next flight and arranged for you to spend some time in the executive lounge before then. This will be done through a combination of AI and human intelligence and will help companies lock in brand loyalty.
The secret sauce to enhanced engagement and reduced turnover rates.
Strategies for enhanced customer experiences in the digital age
