On March 28-30, we attended "Strategie Clients", a trade show aimed at the same goal: customer satisfaction.
Artificial intelligence was the main topic of discussion throughout the show, and the main issues addressed were related to its implementation and long-term success in customer service.
AI can be an invaluable tool for customer service agents, but it's important to remember that it is not a human being. This is why customers still need to interact with customer service representatives for a truly superior experience.
At our booth, we had discussions with around 130 companies of all sizes from different sectors. During our conversation, it became apparent we share many values: commitment to customer satisfaction and care, willingness to continually learn and improve, and openness and transparency towards our customers. We also discussed how to implement a successful customer experience chatbot that will deliver the promise of the happiest customers.
In fact, over the past decade, people have become accustomed to talking to chatbots, but many companies are now realizing that they cannot provide the same level of service and experience as a real person.
There are 3 types of chatbot
Chatbots can be broadly classified into three types – rule-based and AI-based and hybrid-based. Both have their uses and can be leveraged to enhance customer experience. But it is important to understand the limitations of each type of bot in order to implement them optimally.
Rule-based bots are best suited for straightforward dialogues. They are very simple to build and train. A rule-based chatbot poses questions based on predetermined options and the customer can choose from the options until they get answers to their query. The bot will not make any inferences from its previous interactions with the customer or other customers.
Let’s say you are building a bot that helps users file insurance claims. It asks questions like: Do you want to file a claim? Which car do you want to file a claim for? How much damage has been done? Is there any medical emergency due to the accident? etc. In this case, since there are set questions, responses and actions, a rule-based chatbot is best suited for such use cases as it’s very straightforward and there is no room for ambiguity in the responses.
Another example of a rule-based bot is if you want to book a flight, you can create a rule-based bot that will ask you the following questions:
1. From which city?
2. To which city?
3. Date of departure?
4. Date of return?
5. Number of passengers?
There is still a lot of demand for chatbots of this type, but they have a lot of weaknesses.
Customers don't have any control over them. Who has never talked to a chatbot and been blocked because the options do not match their expectations!
Based on this observation, more and more customer services are moving from a so-called basic chatbot to a chatbot powered by artificial intelligence.
Artificial intelligence based chatbots have a huge advantage, they are most of the time conversational.
They are able to say hello, goodbye, how can I help you, and especially able to understand with NLP (Natural Language Processing) your needs and answer them.
Conversational Chatbots are generally limited by the data available, so their usefulness is based on what they know. This is where artificial intelligence (AI) comes in.
GTP-3, for instance, is an open-source model that is known for enhancing chatbots and enabling them to respond almost immediately and without human intervention.
Although the technology seems perfect on paper, it meets yet another huge gap.
Here also, it is sufficient to use your own experience to explain the limit.
Has anyone ever been conversing with a chatbot and found himself asking, "Are you a human?”
Again, it all comes down to the knowledge base, training, and machine learning.
Ultimately, it all boils down to customer satisfaction or dissatisfaction.
Note that bots are not only text-based there are also voice-based bots like Siri or Amazon Echo.
The perfect hybrid chatbot:
In a utopian world, you could create a chatbot to answer all your customers' questions.
But this is not the case.
Because even if you create the most elaborate chatbot with a database of a million answers, it will never be able to respond to all the questions of your customers. This is why most of the time you need to have agents in the loop.
Hybrid chatbot or chatbot with humans in the loop is a combination of both AI-based and human-based systems to provide efficient customer service. It allows the agent to leverage their capabilities.
As explained by the SP2C during the "Strategie Clients" that took place less than a month ago, "In companies, it is time for artificial intelligence to reconcile with humans."
It's time to use artificial intelligence to transform your agents into "Superagents" instead of letting an AI interact with customers 110% autonomously.
Let's dive into a classic example of how artificial intelligence can assist Customer Service Agents.
Imagine that the agent is receiving an email ( or a message on Facebook Messenger… ), he will have to read the message in order to understand what it is about, then starts typing an answer.
By using a knowledge base backed by an AI, he will be able to click on “answer a mail” for instance, and the AI will compose his response. In one click, he will send back an email with perfectly drafted text!
Agents can focus on resolving issues and creating positive experiences rather than focusing on typing responses into a chatbox.
Employees first, customers second
A business adage says that customers should be at the center of everything.
A company would be nothing without customers, of course.
Nevertheless, your business is certainly doomed to failure without loyal, happy employees working together towards one common goal: Customer Satisfaction.
As Vineet Nayar, former CEO of HCL Technologie, explains in his best-selling book, "Employees first, customers second".
Based on the notion that those closest to the customer create the most value, it is necessary to provide a fulfilling work environment, as well as reduce stress to the maximum possible level.
AI and customer support go together like PB&J. One of the best ways to achieve "Customer satisfaction" is to implement AI-powered customer support.
As AI seamlessly integrates with major CRM platforms such as Salesforce or Dynamics360, your agents can be better served with AI than ever before without even having to change their daily routine.
Almost instantly, AI can find out the history of a customer, the nature of his request, and recommend a response that is appropriate for them so the agent can just "check and send"
Thus, AI enhances the efficiency and satisfaction of customer service, which itself becomes more productive and more customer-oriented.
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“We are not building a tool that replaces people but something that augments them.”
The purpose of Emailtree is to improve customer satisfaction while freeing up customer service representatives' time.
Humans and artificial intelligence work in tandem to handle hundreds of thousands of customer requests in more than 25 languages.
Our human-centered artificial intelligence helps customer agents by providing contextual information about conversions like sentiment, intent, or previous interactions.
Last but not least, our AI can integrate into any chatbot or ticketing tool and suggest the most appropriate answer to customer questions.
The "Smart Reply" feature uses machine learning to generate replies based on data from your knowledge database, as well as from previous conversations in order to serve a human-like response in a matter of seconds.
Our chatbot reply technology is designed to learn from your agents and your customers. The more interaction it has with your customers, the smarter it becomes.
In other words, your agents can respond to any customer request through any channel and delight customers with instant responses.
It’s all about Customer Happiness
In conclusion, AI can be used in many ways, from transforming customer service to automating it.
Implementing AI with humans in the loop is indeed a disruptive shift in many ways, but it is definitely not replacing human efforts. Instead, it is upping the ante on them to deliver the most accurate and relevant answers to customers' queries at their convenience without any hassles.
The key point is that the solutions must be adapted to the requirements of each company according to their needs and expectations.
We met many fast-growing companies at this event that are interested in getting into AI. However, perhaps the best way to do so is to think about how you can combine human interaction with AI systems to deliver better results without sacrificing human interactions.
Because at the end of the day, it's all about human to human relations.