Generative AI could improve customer service chatbots
‘Human touch’ needed
Traditional chatbots are supposed to provide a convenient and efficient way for customers to get the help they need. However, several studies have shown that a high number of customers find the experience to be unsatisfying.
Yamkela Mdaka - Chatbots have become an essential part of customer service in the modern world.
They are supposed to provide a convenient and efficient way for customers to get the help they need - but, despite their prevalence, a lot of chatbots are still quite limited in their capabilities. It often frustrates customers with unhelpful responses, particularly when the query is complex.
Several studies have shown that a high number of customers, who interact with chatbots, find the experience to be unsatisfying and would prefer to talk to a real person instead.
A US survey, by UJet, based on data collected from nearly 1 700 customers over 12 months, found that 80% of consumers who had interacted with a chatbot said it increased their frustration level.
The same survey found that 63% of their interactions with chatbots did not result in a resolution, 54% believed that a phone call with a live agent provided the fastest resolution, and 73% believed that businesses could significantly improve their customer experience by ensuring problems are resolved on first contact.
"Brands cannot provide great customer service through simply adopting automation," said lead researcher Juston Robbins.
"Our findings highlight the challenges brands face with implementing automation to decrease wait times, improve first contact resolution, and increase customer satisfaction and loyalty."
Generative AI
While people may find themselves wishing for chatbots to be completely scrapped, out of pure frustration, according to Gartner, chatbots will become the primary customer service channel by 2027.
It's clear they are here to stay, but it is a small relief to know that they'll be getting better as a result of new advancements in generative AI.
Generative AI, which has been all the rage this year, is a type of AI that uses deep learning algorithms to generate new responses based on data provided.
The incorporation of generative AI into a customer service chatbot will give it the ability to not only respond in more natural and conversational ways, but it will also be able tailor its responses to the specific needs of each customer.
While the concept is not completely new, with voice assistants like Apple's Siri and Amazon's Alexa using similar technology for a while now, it will be game-changing potential for chatbot innovation.
What exactly is it that makes generative AI so different from traditional chatbots?
A report by Laivly, an AI platform for contact centres, answers this best.
It says: “The potential lies in pairing the natural language capabilities of a generative AI model, like ChatGPT, with an AI solution that can also learn and perform actions.
"Compared to chatbots, which simply present information available elsewhere before transferring more complex cases to an agent, a generative AI solution could facilitate an entire interaction with a customer - even a highly complex problem or an issue that is not well defined by the customer."
Interaction
In this regard, generative AI solutions will have more of a "human touch" in the way that they interact with customers, something that is sometimes glaringly missing from the traditional chatbots that customers have had to engage with in the past.
This is pivotal to a customer's experience of a product or service business, according to a report by PwC.
"New technology tools are tantalising and sometimes necessary, but the human touch remains enormously important," the report said. "64% of US consumers and 59% of all consumers feel companies have lost touch with the human element of customer experience. 71% of Americans would rather interact with a human than a chatbot or some other automated process."
In a piece for Harvard Business Review, Wharton professors Nicolaj Sigglkow and Christian Terwiesch write that a key benefit of generative AI for chatbots is that the knowledge base of generative AI models are able to grow with every interaction with a user.
"With any interaction that a company has with a customer, there should be some new learning about the customer, so that in the next interaction, the firm can do an even better job at recognising, requesting and responding to a query [and] large language models are inherently good at learning from prior experiences," they write.
Game-changing models
Both Google (BARD) and Microsoft (ChatGPT) have made their chatbots available to software developers from other companies to integrate into their own systems through an API (application programming interface).
This means that companies from all industries, not just the big tech companies, can now have access to these game-changing large language models.
With all this said, there are still going to be cases where a human needs to get involved.
The human role will mostly likely develop into dealing with extremely complex queries - but, for now, while the technology is still being further developed, humans will be involved in vetting generative AI systems' responses, which have the capability of being biased, incorrect, completely made up, and inaccurate. – Fin24
They are supposed to provide a convenient and efficient way for customers to get the help they need - but, despite their prevalence, a lot of chatbots are still quite limited in their capabilities. It often frustrates customers with unhelpful responses, particularly when the query is complex.
Several studies have shown that a high number of customers, who interact with chatbots, find the experience to be unsatisfying and would prefer to talk to a real person instead.
A US survey, by UJet, based on data collected from nearly 1 700 customers over 12 months, found that 80% of consumers who had interacted with a chatbot said it increased their frustration level.
The same survey found that 63% of their interactions with chatbots did not result in a resolution, 54% believed that a phone call with a live agent provided the fastest resolution, and 73% believed that businesses could significantly improve their customer experience by ensuring problems are resolved on first contact.
"Brands cannot provide great customer service through simply adopting automation," said lead researcher Juston Robbins.
"Our findings highlight the challenges brands face with implementing automation to decrease wait times, improve first contact resolution, and increase customer satisfaction and loyalty."
Generative AI
While people may find themselves wishing for chatbots to be completely scrapped, out of pure frustration, according to Gartner, chatbots will become the primary customer service channel by 2027.
It's clear they are here to stay, but it is a small relief to know that they'll be getting better as a result of new advancements in generative AI.
Generative AI, which has been all the rage this year, is a type of AI that uses deep learning algorithms to generate new responses based on data provided.
The incorporation of generative AI into a customer service chatbot will give it the ability to not only respond in more natural and conversational ways, but it will also be able tailor its responses to the specific needs of each customer.
While the concept is not completely new, with voice assistants like Apple's Siri and Amazon's Alexa using similar technology for a while now, it will be game-changing potential for chatbot innovation.
What exactly is it that makes generative AI so different from traditional chatbots?
A report by Laivly, an AI platform for contact centres, answers this best.
It says: “The potential lies in pairing the natural language capabilities of a generative AI model, like ChatGPT, with an AI solution that can also learn and perform actions.
"Compared to chatbots, which simply present information available elsewhere before transferring more complex cases to an agent, a generative AI solution could facilitate an entire interaction with a customer - even a highly complex problem or an issue that is not well defined by the customer."
Interaction
In this regard, generative AI solutions will have more of a "human touch" in the way that they interact with customers, something that is sometimes glaringly missing from the traditional chatbots that customers have had to engage with in the past.
This is pivotal to a customer's experience of a product or service business, according to a report by PwC.
"New technology tools are tantalising and sometimes necessary, but the human touch remains enormously important," the report said. "64% of US consumers and 59% of all consumers feel companies have lost touch with the human element of customer experience. 71% of Americans would rather interact with a human than a chatbot or some other automated process."
In a piece for Harvard Business Review, Wharton professors Nicolaj Sigglkow and Christian Terwiesch write that a key benefit of generative AI for chatbots is that the knowledge base of generative AI models are able to grow with every interaction with a user.
"With any interaction that a company has with a customer, there should be some new learning about the customer, so that in the next interaction, the firm can do an even better job at recognising, requesting and responding to a query [and] large language models are inherently good at learning from prior experiences," they write.
Game-changing models
Both Google (BARD) and Microsoft (ChatGPT) have made their chatbots available to software developers from other companies to integrate into their own systems through an API (application programming interface).
This means that companies from all industries, not just the big tech companies, can now have access to these game-changing large language models.
With all this said, there are still going to be cases where a human needs to get involved.
The human role will mostly likely develop into dealing with extremely complex queries - but, for now, while the technology is still being further developed, humans will be involved in vetting generative AI systems' responses, which have the capability of being biased, incorrect, completely made up, and inaccurate. – Fin24
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