While chatbots today are becoming intelligent enough to address several simple and complex queries of users, there will always be situations where a conversation needs a human touch and should be handed over to a live agent. In an ideal scenario, chatbots should act as a first line of support by capturing users’ information and either solve issues completely or transfer the conversation to an agent.
This transition should be quick, seamless and non-intrusive to ensure swift response times and a great user experience. Chatbots with human-in-the-loop capabilities, can deliver differentiated service experiences that delight your customers and employees.
In this article, we’ll discuss the different scenarios where a human hand off is needed and how a chatbot can execute it successfully.
Even though the chatbot technology is advancing at a rapid pace, bots today aren’t always capable of grasping the needs of a customer. Customer needs and queries are diverse and always emerging. For instance, say you launched a new product/service. Needless to say, you’ll see a surge of varied requests from customers who’re trying it for the first time. Even if you deploy a basic FAQ bot, live agent support is always needed as there’ll be numerous unexpected questions that the chatbot can’t answer and need personalized human attention.
Let’s take another example. Maria, a customer of XYZ bank, wants to purchase tickets for a popular concert. She tries to make an online payment through her debit card and finds her card has been disabled for some unknown reasons. She tries to interact with the bank’s chatbot. The bot couldn’t solve Maria’s rather unique problem and offers generic solutions. Maria, who is already in a hurry to buy the tickets, is now further frustrated due to the lack of right assistance.
In situations like this, a chatbot should understand Maria’s tonality and recognize it’s important to perform a human handoff. Or else, people like Maria will be left with a bad customer experience.
The above examples highlight a common challenge that businesses face when deploying a chatbot. While chatbots are excellent first line support agents, they can’t interact with customers the way a human does. Contact centres and service desks should therefore configure their chatbots to better recognize when the conversation gets too complex to handle and a human agent is needed.
When a customer sounds unhappy, frustrated, angry and annoyed, the chatbot should proactively provide the option to talk with a live agent. This requires chatbots to have NLP & sentiment analysis capabilities to detect the tonality of the user using keywords or emotional triggers.
Chatbots should detect critical situations which involve sensitive conversations, high-value transactions or a customer at the risk of churning and hand over the conversation to a agent for maximum end user experience.
A chatbot should triage a user’s request, capture their information and analyze if it can handle the issue at hand. It should be smart enough to recognize if it can’t and suggest the “Talk to a Human Agent” option.
At times customers might be in a rush and want to resolve the issue quickly. A chatbot should always include the “Talk to an agent” option in its main menu.
When a human handoff occurs, the agent should receive the full history of the chatbot-user conversation. This should include details about context and sentiment scores. This way customers don’t have to repeat their information and problems again to the agent. Also there has to be a seamless transfer of Human Agent back to the chatbot.
The chatbot should clearly highlight when the human agent is participating in the conversation and when the chatbot is back into the conversation.
The chatbot builder platform should integrate seamlessly with live agent softwares like LiveChat, LivePerson, Salesforce, etc.This enables your agents to continue using the existing software without having to let go of current functionality and workflows in your contact center or service desk support software.
When your customers are spread across multiple geographies, the bots should translate their queries for the human agents while routing the communication. This is instrumental in ensuring customer satisfaction.
Using NLP and sentiment analysis, bots should gauge the mood of the user and ascertain if they need to talk to a live human agent.
At times, support agents intend to monitor bot conversations instead of completely taking charge. In such cases, the bot can privately take agent authorization for the prescribed solution before actually suggesting it to the user. For example, consider a help desk scenario where a bot is interacting with a user to prescribe a solution to a computer problem. With its machine learning model, the bot detects the cause of the issue. However, before advising the solution to the user, the bot can privately consult a human agent and request authorization for its diagnosis. The agent can then click a button and the bot will provide the solution to the user. The bot still does all the legwork, but a human agent controls the final decision.
As chatbots become a key part of customer support, it’s imperative to upgrade them with new capabilities. A seamless chatbot-human handoff is critical not only to improve customer experience but also drive user adoption. With rules or failure conditions, chatbots can be trained to easily escalate a customer issue to a human agent.
If you’d like to learn more about this topic, please feel free to get in touch with one of our enterprise chatbot consultants for a personalized consultation. You may also be interested in exploring our enterprise chatbot builder platform (BotCore).