A version of this post, co-authored by Mark Smith, Zendesk content marketing manager, originally appeared on Zendesk's blog. Learn about how to use a Zendesk + Guru integration to create a centralized Zendesk knowledge base.
Despite all the doom and gloom about AI replacing human jobs (there are over 44.5 million results on Google for “AI replacing jobs”), the most immediate application of artificial intelligence comes in making humans better at their jobs – not replacing them. One area in which AI can augment the human workforce is in human-to-human customer service interactions. When a customer is agitated and needs an answer quickly, sticking an AI-powered chatbot between them and an empathetic human rep is not the best idea. Instead, AI can be used by the human rep to get the answers they need to solve the customer’s problem faster.
An AI-powered knowledge base creates better experiences for both reps and customers by:
Centralizing knowledge from disparate sources and improving the quality and accuracy of rep responses
Helping keep content accurate and relevant
Getting new agents up-to-speed quickly with ongoing training and contextual coaching
1. AI can centralize knowledge from disparate sources and improve the quality and accuracy of rep responses
When a rep has all the knowledge they need to answer customer questions delivered right at their fingertips, they can spend less time searching for an accurate answer and pass that time savings on to their customers. A customer won’t know whether a rep is being aided by AI or not, but they will know the difference between an immediate answer and an “I’ll have to get back to you on that.” When reps are served knowledge proactively by an AI system, they don’t have to go searching for the answers they need.
A customer will also know the difference between “Let me find that answer for you,” and “Let me transfer you to my colleague who will have that answer for you.” When AI can operationalize a knowledge base and make information from different departments available instantly, reps don’t have to pass customers from department to department when a question is out of their purview. Customers don’t care which department they’re speaking to, they just know that they’re speaking to your company and they expect an answer. Using AI to unify and activate knowledge from across an organization helps reps deliver faster answers and saves customers the frustration of having to wait around or repeat their question to multiple reps.
Per Kate Leggett at Forrester, these inflections point in a call – when a rep doesn’t have to put the customer on hold or transfer them to another department to find an answer – are where a company can actually grow and nurture the customer relationship: “An agent has to be empowered with all the right data and knowledge to be able to answer a customer's question as quickly as possible. Again, because customers say that valuing their time is the most important thing. And that's a really difficult proposition. And if you get it right, these are the rare moments when you can nurture and grow the relationship that you have with customers."
2. AI helps keep content accurate and relevant
Beyond serving content to reps so they can quickly resolve customer issues, AI can ensure that a company’s knowledge base actually stays relevant —and studies have shown that companies with an agile approach to updating content have higher self-service ratios and better search results. In this era of complex products and services, curating a help center can be surprisingly difficult, but support teams can lean on AI to make that process run smoothly.
For example, AI can flag content for review at regular intervals, leveraging machine learning to identify articles that need updated titles, new content, and better search labels. Yet perhaps the most powerful feature of an AI-powered knowledge base is its ability to suggest new content based on what customers are asking for in support requests. That empowers internal subject matter experts to focus their contributions on what will impact customers the most — and in turn, that frees up agents to focus on white-glove service.
3. Pushing knowledge to agents in-context with AI helps them onboard faster and learn while on the job
Given all the knowledge support reps need to know or have access to in order to answer customer questions, it can take new reps weeks to ramp up and be comfortable navigating a hefty knowledge base. While a seasoned rep may know exactly which piece of knowledge she needs to send a customer to answer a particular question, a newer rep will have to spend precious time searching for that knowledge while the customer sits on hold.
When a knowledge base is augmented with AI, those reps can be served knowledge instead of having to go searching for it. Based on the context of an ongoing conversation, AI solutions like Guru’s AI Suggest can surface relevant knowledge for reps to choose from, eliminating the need to search altogether. By helping all reps, regardless of experience level, access the same knowledge in the same time frame, AI levels the playing field and empowers even the newest of reps to answer questions just as quickly as their veteran colleagues.
Being served knowledge in the moment also helps with contextual coaching. Gordon Ritter and Jake Saper, partners at Emergence Capital, have explored this concept at length and developed a thesis around what they call coaching networks, which use machine learning to coach workers on how to do their jobs better as they do them.
Rather than relying on training a rep before or after a customer interaction, (“Here’s the knowledge you’re going to need for this particular use case” or “Here’s the knowledge you should have used for this particular use case”), AI can coach reps while that use case is still occurring.
In the moment, if a rep doesn’t know the answer to a particular question and doesn’t have an AI-powered knowledge base to suggest the correct answer, they’ll have to the best they can with what they have to answer the question. Even the most comprehensive training won’t help in that situation if the rep can’t remember what they were trained on. And after-the-fact training will help them respond better the next time that question comes around, but does nothing for the current interaction they need help with. It’s that just-in-time training that comes from in-context coaching that helps reps learn best. And, the customer doesn’t suffer as a result of a learning curve.
AI also gets smarter over time and has the ability to capture, learn from, and leverage the creativity of individuals to make the collective organization smarter. According to Emergence Capital:
“The key ingredient of coaching networks is software that gathers data from a distributed network of workers and identifies the best techniques for getting things done.”
Imagine a rep is asked a complicated security question by a customer and his AI-powered knowledge base serves him up potentially relevant knowledge to answer that question. The rep may use a piece of that knowledge, but what happens if he then still searches and pulls up a different piece of knowledge to use to answer the customer’s question? Without any AI involved, that learning moment would happen in a vacuum. With AI, the system can capture the creativity and success of that one rep’s actions, and the next time a rep receives a similar security question, the AI can serve that rep the additional knowledge it didn’t serve the first rep that ended up making the difference.
“What's cool about coaching networks is because you have sensor data, you can actually understand what is a rep saying and what is the actual outcome, and what is the creative thing the rep has done to make a close happen. You can capture that creativity, and you can spread it to everyone else in the network. So the concept here is really, really powerful. By one person anywhere in the world doing their job, and just by doing their job, they can inadvertently be training everyone else in the network.” –Jake Saper, Emergence Capital'
AI powers better experiences for agents and customers alike
Leveraging AI to help frontline reps do their jobs better is a win-win: customers are happier when they get the help they need quickly and efficiently, and reps feel more confident and empowered when they can onboard quickly and perform to the best of their abilities.
A version of this post, co-authored by Mark Smith, Zendesk content marketing manager, originally appeared on Zendesk's blog. Learn about how to use a Zendesk + Guru integration to create a centralized Zendesk knowledge base.
Despite all the doom and gloom about AI replacing human jobs (there are over 44.5 million results on Google for “AI replacing jobs”), the most immediate application of artificial intelligence comes in making humans better at their jobs – not replacing them. One area in which AI can augment the human workforce is in human-to-human customer service interactions. When a customer is agitated and needs an answer quickly, sticking an AI-powered chatbot between them and an empathetic human rep is not the best idea. Instead, AI can be used by the human rep to get the answers they need to solve the customer’s problem faster.
An AI-powered knowledge base creates better experiences for both reps and customers by:
Centralizing knowledge from disparate sources and improving the quality and accuracy of rep responses
Helping keep content accurate and relevant
Getting new agents up-to-speed quickly with ongoing training and contextual coaching
1. AI can centralize knowledge from disparate sources and improve the quality and accuracy of rep responses
When a rep has all the knowledge they need to answer customer questions delivered right at their fingertips, they can spend less time searching for an accurate answer and pass that time savings on to their customers. A customer won’t know whether a rep is being aided by AI or not, but they will know the difference between an immediate answer and an “I’ll have to get back to you on that.” When reps are served knowledge proactively by an AI system, they don’t have to go searching for the answers they need.
A customer will also know the difference between “Let me find that answer for you,” and “Let me transfer you to my colleague who will have that answer for you.” When AI can operationalize a knowledge base and make information from different departments available instantly, reps don’t have to pass customers from department to department when a question is out of their purview. Customers don’t care which department they’re speaking to, they just know that they’re speaking to your company and they expect an answer. Using AI to unify and activate knowledge from across an organization helps reps deliver faster answers and saves customers the frustration of having to wait around or repeat their question to multiple reps.
Per Kate Leggett at Forrester, these inflections point in a call – when a rep doesn’t have to put the customer on hold or transfer them to another department to find an answer – are where a company can actually grow and nurture the customer relationship: “An agent has to be empowered with all the right data and knowledge to be able to answer a customer's question as quickly as possible. Again, because customers say that valuing their time is the most important thing. And that's a really difficult proposition. And if you get it right, these are the rare moments when you can nurture and grow the relationship that you have with customers."
2. AI helps keep content accurate and relevant
Beyond serving content to reps so they can quickly resolve customer issues, AI can ensure that a company’s knowledge base actually stays relevant —and studies have shown that companies with an agile approach to updating content have higher self-service ratios and better search results. In this era of complex products and services, curating a help center can be surprisingly difficult, but support teams can lean on AI to make that process run smoothly.
For example, AI can flag content for review at regular intervals, leveraging machine learning to identify articles that need updated titles, new content, and better search labels. Yet perhaps the most powerful feature of an AI-powered knowledge base is its ability to suggest new content based on what customers are asking for in support requests. That empowers internal subject matter experts to focus their contributions on what will impact customers the most — and in turn, that frees up agents to focus on white-glove service.
3. Pushing knowledge to agents in-context with AI helps them onboard faster and learn while on the job
Given all the knowledge support reps need to know or have access to in order to answer customer questions, it can take new reps weeks to ramp up and be comfortable navigating a hefty knowledge base. While a seasoned rep may know exactly which piece of knowledge she needs to send a customer to answer a particular question, a newer rep will have to spend precious time searching for that knowledge while the customer sits on hold.
When a knowledge base is augmented with AI, those reps can be served knowledge instead of having to go searching for it. Based on the context of an ongoing conversation, AI solutions like Guru’s AI Suggest can surface relevant knowledge for reps to choose from, eliminating the need to search altogether. By helping all reps, regardless of experience level, access the same knowledge in the same time frame, AI levels the playing field and empowers even the newest of reps to answer questions just as quickly as their veteran colleagues.
Being served knowledge in the moment also helps with contextual coaching. Gordon Ritter and Jake Saper, partners at Emergence Capital, have explored this concept at length and developed a thesis around what they call coaching networks, which use machine learning to coach workers on how to do their jobs better as they do them.
Rather than relying on training a rep before or after a customer interaction, (“Here’s the knowledge you’re going to need for this particular use case” or “Here’s the knowledge you should have used for this particular use case”), AI can coach reps while that use case is still occurring.
In the moment, if a rep doesn’t know the answer to a particular question and doesn’t have an AI-powered knowledge base to suggest the correct answer, they’ll have to the best they can with what they have to answer the question. Even the most comprehensive training won’t help in that situation if the rep can’t remember what they were trained on. And after-the-fact training will help them respond better the next time that question comes around, but does nothing for the current interaction they need help with. It’s that just-in-time training that comes from in-context coaching that helps reps learn best. And, the customer doesn’t suffer as a result of a learning curve.
AI also gets smarter over time and has the ability to capture, learn from, and leverage the creativity of individuals to make the collective organization smarter. According to Emergence Capital:
“The key ingredient of coaching networks is software that gathers data from a distributed network of workers and identifies the best techniques for getting things done.”
Imagine a rep is asked a complicated security question by a customer and his AI-powered knowledge base serves him up potentially relevant knowledge to answer that question. The rep may use a piece of that knowledge, but what happens if he then still searches and pulls up a different piece of knowledge to use to answer the customer’s question? Without any AI involved, that learning moment would happen in a vacuum. With AI, the system can capture the creativity and success of that one rep’s actions, and the next time a rep receives a similar security question, the AI can serve that rep the additional knowledge it didn’t serve the first rep that ended up making the difference.
“What's cool about coaching networks is because you have sensor data, you can actually understand what is a rep saying and what is the actual outcome, and what is the creative thing the rep has done to make a close happen. You can capture that creativity, and you can spread it to everyone else in the network. So the concept here is really, really powerful. By one person anywhere in the world doing their job, and just by doing their job, they can inadvertently be training everyone else in the network.” –Jake Saper, Emergence Capital'
AI powers better experiences for agents and customers alike
Leveraging AI to help frontline reps do their jobs better is a win-win: customers are happier when they get the help they need quickly and efficiently, and reps feel more confident and empowered when they can onboard quickly and perform to the best of their abilities.
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