Customer service is currently going through its second technological revolution: moving towards AI and a strong reliance on automation.
All this is happening for agents, managers, support QAs, and customers alike.
So we’re taking a look at how new trends and innovations are impacting the future of customer support for everyone.
Let’s start with what you should be expecting from the future of services in the next 2 to 5 years.
Real-time customer engagement will surge
88% of people had at least one conversation with a chatbot last year.
This said, expect chatbots to dominate the future of customer service.
A chatbot that’s set up properly can even recognize when a customer is taking a long time to complete an action, and can provide assistance (e.g. instructions, tips, resources, links) if needed. This allows the customer to fix an issue in real time or get an agent to intervene if necessary.
Additionally, you’ll be able to mitigate unexpected issues faster and reduce the number of tickets your agents get for basic questions like finding a feature or changing a purchase.
Kaitlin Pettersen, Leading Customer Engagement at Vanta, emphasizes the value of a chatbot or knowledge base to filter out repetitive work, leaving only the complex work that requires empathy or extra research to your agents:
“The repetitive, pretty objective, simple questions can be answered automatically with chatbots or you can use a knowledge base.”
Self-service support should be a part of your future customer service funnels
70% of customers have used self-service channels at some point during their research process. That’s because people want to get their questions answered as quickly as possible without having to wait for an agent to be live.
Simultaneously, more customers will expect a multichannel service experience. Offering a self-service resource center can help with speeding up support and offering that initial help they need to reduce the number of channels they have to turn to.
Kaitlin Pettersen highlights how important it is to diversify your support funnel and make sure it reunites this self-service aspect:
“Proactive support is a huge step-change for customer support and a necessary shift. The funnel is simple but powerful. It combines proactive, self-serve, and human support capabilities.”
Offering proactive support through self-service resources also has its fair share of benefits for agents. They’ll have fewer tickets to deal with so they can focus on more complex issues.
So let’s get to some more future of customer service trends, this time for agents, support QAs, and team leads.
Support professionals are expected to become more empathetic
Late last year, we had an enlightening talk with Oleg Krasnov, Head of Customer Support at Manychat, where he revealed he prioritizes one core trait in prospective support employees:
“Empathy. I want to see people who are excited about helping people.”
Oleg asks for examples of empathetic behavior to assess candidates during an interview. He further noted that the responses to this question are very telling, as naturally empathetic people will be able to readily provide multiple examples of when they have helped others without being asked.
He also adds that it’s important to challenge these examples to gain a better understanding of the intrinsic or situational factors that enabled the person to respond with empathy.
But why is empathy so important?
Let’s just say you can use your agents to better understand customers’ perspectives and experiences. This provides them with the ability to adjust their responses accordingly, pinpoint areas of improvement, and provide excellent customer service.
Businesses can use sentiment and empathy analysis to their advantage by proactively addressing customer issues and pain points. This will further improve customer satisfaction by allowing companies to focus on areas that need attention.
Kaizo’s Agent Empathy Score automatically evaluates and measures empathy levels displayed by agents during interactions.
This AI-powered feature provides an impartial measure of empathy, guaranteeing consistent ratings during different customer engagements and agents. This eliminates any subjectivity that could be introduced through manual scoring.
As a bonus, your QA team will be able to identify specific areas where agents succeed or challenges they’re experiencing that might require additional training.
Kaizo’s AI capabilities automatically highlight negative sentiment and empathy in messages. With this feature, you can improve your grasp on how customers interpret information, given the non-empathetic agent tone. Use this insight to craft future messages that avoid sounding negative to customers.
We aim to make interactions between customers and agents as transparent and clear as possible.
To do this, we opted for an AI model that detects which parts of the responses and messages (from both the customer and agent) are negative. By taking note of and reviewing these sentences, you’ll gain a better understanding of how customers view their interactions and can take the necessary steps to address any worries or problems.
AI will help professionals, not replace them
Customer service decision makers report an 88% increase in the use of AI, going from 24% of respondents to 45%.
AI is here to free up agents so they can focus on the tasks that only humans can do.
Machines are not equipped with the technology to create a response when the issue is complex. However, they can help route, organize, structure, and analyze data so that humans can ultimately be more productive.
Raúl Garreta, Senior Director Data Science at Medallia and General Manager at MonkeyLearn, recommends starting by automating repetitive, boring tasks to free up the time of support staff and make their day more enjoyable.
Machines may make mistakes, but they make consistent mistakes that can be easily identified and avoided.
At Kaizo, we come in to help support managers and agents every step of the way.
QA raters and team leads are tasked with the crucial responsibility of assessing tickets, understanding their context, and providing valuable feedback. However, the sheer amount of tickets can often be overwhelming, leading to time constraints and information overload.
Our AI Summary for tickets allows users to quickly understand the main points of a ticket without having to read the whole thing. This feature places the most important details into a short conversation summary, providing QA raters and team leads with a comprehensive overview in a fraction of the time.
New technology will create new customer service positions
The future of AI in customer service also means you’re looking at new roles and skills on your support teams.
On one hand, team leads and recruiters are looking for soft skills more than ever when bringing on new agents to their teams. That’s because these are the very traits that AI can’t replicate.
On this point, like Oleg, Chelsea Baker, Director of Customer Experience and Adoption at Trakstar, also emphasizes how she pays attention to empathy:
“I can teach you how to use our product but I can’t teach you how to be empathic by nature or be continuously curious and wanting to learn.”
Other traits to keep an eye on with candidates include how well they respond to stress, if they’re receptive to feedback, or, as Petra Hageman puts it, if they “have a customer service heart.”
Beyond recruitment, expect new roles to appear at all experience levels.
As many as 75% of companies are planning to have a Chief Customer Officer (CCO) on board. Their role is to ensure that all customer touchpoints are aligned with the company’s strategy and goals.
The CCO works with various departments and stakeholders in the organization to identify and implement strategies that will improve customer service. They’re also in charge of developing customer-centric processes and ensuring that customer feedback is used to drive decisions.
And since we mentioned departments…
Here’s a bold estimate from our observations and talks with companies:
Every large organization with over 150 agents should have a QA team.
With such a big support team, it’s normal to expect a big flow of tickets coming in. Team leads have other things to focus on, so a new role should be created specifically for this — one that works not only on agent service quality but also for spotting business-related issues customers mention.
If we’re talking about 50-150 agents, usually the QA team’s tasks can also be distributed between team leads or trainers. This means that the same person who does the QA reviews will have other tasks and responsibilities. However, as there’s still a lot of data to go through, usually a specific Data Analyst or QA Admin is hired to maintain an overview, aggregate, and provide the QA insights from the QA ratings team leaders or trainers did.
Note: Don’t shy away when it comes to outsourcing or using virtual assistants. More companies opt for this to reduce costs or increase efficiency. And it’s not just small businesses. New projects or busier sales seasons demand extra agents. Read more on how Rui Chaves, Global Director of Customer Support at Bolt, used outsourcing at Facebook to keep up with language requirements as Facebook was exploding throughout Europe and the rest of the world.
Next steps for handling the customer service challenges of the future
We recommend prioritizing making the innovative changes above based on your current challenges. For instance, if you’re uncertain about your agents’ performance in terms of empathy, try Kaizo’s Agent Empathy Score to get a complete look at how they’re handling cases.
This is also a good first step for investing in AI and seeing how it can free up your time. Additionally, consider bringing in tools like chatbots, virtual assistants, and AI-powered recommendation engines that can help scale customer interactions and automate routine requests.
With the ever-changing role of the support agent, it’s a good idea to focus on agent enablement technologies. Tools like knowledge bases, AI assistance, and workflow automation can boost your agents’ efficiency and effectiveness.
