Zendesk: How AI Chatbots can Transform Customer Service

We speak with Matthias Goehler, Zendesk’s EMEA CTO, about how AI-powered virtual assistants are providing fast, personalised service at scale

The world of customer service is being transformed by AI. Leading companies are increasingly turning to virtual assistants and conversational AI chatbots to improve the customer experience. These cutting-edge technologies, powered by large language models and generative AI (Gen AI), allow businesses to provide fast, personalised service at scale.

From retail to finance, travel to healthcare, virtual assistants are the new frontline brand representatives. Customers can open a chat window and have natural dialogues to get questions answered, receive recommendations, troubleshoot issues and complete tasks without waiting on long hold queues.

With advances in natural language AI, these assistants are becoming adept at handling complex queries and tasks that previously required human expertise – from data analysis to coding to writing. When combined with automation, companies can offload many routine workflows to AI, freeing employees for higher-value work.

Matthias Goehler, Chief Technology Officer of Zendesk in the EMEA region, understands the importance of implementing AI chatbots effectively. Technology Magazine sat down with Matthias after the company’s flagship Relate conference to discuss the benefits – and challenges – of AI chatbot adoption.

Businesses must address barriers to AI chatbot implementation

Ranked #1 for Digital Customer Service by Gartner, no less, Zendesk is a service-first CRM company that builds software designed to improve customer relationships. 

As its EMEA CTO, Matthias’ role involves engaging with customers and partners to develop strategies for achieving their customer experience (CX) goals, while also working with product and engineering teams to meet market demands.

“We should always start by thinking about the customer we’re serving, their requirements and demands,” he says. “When we reach out to a customer service team, we probably have a question, problem, or complaint – and we want an answer or help. Fundamentally, we want it fast, and that has never changed. We want the answer on the first call; we hate repeating ourselves or going through endless processes with handovers.” 

According to Matthias, failing to address barriers to AI chatbot implementation can put businesses at a significant disadvantage. “As companies start using technology more, we – as customers in B2B or B2C environments – understand technology better and want more personalised engagement,” he notes. Here, chatbots offer an elegant solution for handling simple, repetitive queries such as ‘Where's my bill? Where's my delivery? I want to return an item.’

“There is high potential for automating these types of questions with chatbots that can understand the query, look up the information in a knowledge base, and provide the right answer quickly,” Matthias explains. “This matches the customer's desire for a fast, correct, personalised response on the first interaction.” He cites examples of Zendesk customers seeing “up to 30% cost savings by automating these simple queries” and increased customer satisfaction scores.

However, Matthias cautions that businesses must manage risks associated with chatbot implementation. “You need to ensure the technology can achieve the desired outcome, provide accurate information to customers, understand intent correctly, and give the right answer without bias,” he warns. “We've seen cases where this hasn't happened properly, leading to lawsuits. But if you manage these risks, we believe there is a huge business potential.”

AI agents continue to impact CX

What’s clear is that AI agents will have a profound impact on CX. But while AI agents will play a significant role in shaping the future of customer experience, businesses must strike a balance between automation and human interaction. By leveraging AI for simple queries and preserving human involvement for complex cases, companies can achieve cost savings, improved productivity and enhanced customer satisfaction.

While Matthias doesn't believe that 100% of all interactions will be fully automated in the future, he sees “huge potential, let’s say about 80%” for the automation of simple questions and processes.

Automating these interactions can provide significant advantages for businesses. “That obviously gives you a big advantage in terms of cost savings, but also in terms of customer satisfaction.” He draws a parallel to the shift towards e-commerce, which initially led to an increase in interactions.

However, Matthias acknowledges that human interaction will still be desired and required in certain cases. “There will still be cases where human interaction is wanted and needed. It could be that I, as a customer, want it. It could also be a very complicated or sensitive case where customers would prefer to interact with humans.”

Despite the potential for extensive automation, Goehler believes that human interaction will still be needed – at least to some degree. “We need to ensure that for those cases where you're handing it over to the agent, you're providing the full context so there's no repetition,” he says. “You're empowering the agent with the necessary information to pick up the case and answer in the most personalised way."

Seizing the opportunity of AI

The world is, of course, still in the early stages of the AI revolution, particularly in the realm of Gen AI. Matthias expects that “for the next couple of years, we will still have a lot of opportunities with AI – in terms of automation and using Gen AI in the right way.”

While chatbots have been a key focus in recent months, Matthias also emphasises the potential of AI to enhance the productivity of human agents. “There is a lot of potential in how we can make the life of human agents more productive using AI,” he states, from leveraging AI for forecasting and scheduling to ensuring the right number of agents are available during peak times and across various channels and languages.

Matthias envisions AI acting as an “agent co-pilot,” similar to how chatbots interact with customers. “The AI can understand the intent, suggest next steps, bring up relevant information and potential answers and guide the agent through processes - while the agent remains in control to focus on customer communication, show empathy for difficult cases.”

In addition to enhancing agent productivity, AI can play a crucial role in quality assurance. Matthias cites the example of Klaus, an AI-powered quality management platform recently acquired by Zendesk, which can perform automated quality assurance on 100% of interactions, filtering out only those that require closer review. Interestingly, these systems can also assess the quality of chatbot and Gen AI outputs, ensuring they meet defined standards and allowing for adjustments to the algorithms if necessary.

Looking to the future, Matthias sees a “very broad spectrum with a lot of opportunities still to fully adopt and embrace over the next couple of years.” 

“[AI] will remain a major theme,” he concludes, “driving better customer experiences through automating simple tasks while enhancing human agents' performance on more complex interactions.”


Make sure you check out the latest edition of Technology Magazine and also sign up to our global conference series - Tech & AI LIVE 2024


Technology Magazine is a BizClik brand


Featured Articles

Sophia Velastegui: Overcoming Enterprise AI Challenges

AI Magazine speaks with AI business leader Sophia Velastegui as she offers advice for businesses seeking to advance their AI use cases responsibly

Bigger Not Always Better as OpenAI Launch New GPT-4o mini

OpenAI release new GPT-4o mini model designed to be more cost-efficient whilst retaining a lot of the same capabilities of larger models

Why are the UK and China Leading in Gen AI Adoption?

China and the UK are leading the adoption of Gen AI, which although sounds surprising to begin with, becomes clearer as you dig into their state strategies

Moody's Gen AI Tool Alerts CRE Investors on Risk-Posing News

Data & Analytics

AWS Unveils AI Service That Makes Enterprise Apps in Minutes

Data & Analytics

Jitterbit CEO: Confronting the Challenges of Business AI

AI Strategy