Ever since businesses have existed, there have been customer service agents. Whether the owner themselves, a team member, or an outsourced agent, customers often need help, and companies try to give it to them (try being the key word here because it’s not always great!)
As we all know, customer service can be a mixed bag. The best customer support agents are beneficial and thoughtful and help you quickly navigate challenges using the product. On the other hand, there's almost nothing worse than a wrong customer support agent who is ill-equipped to solve your problem.
We've all had that experience of banging our heads against the wall as we wait on hold, or holding back frustration as an agent seems to be unsure what to do or need to pass this along to their manager yet again.
But with the rise of artificial intelligence, a whole new suite of tools is suddenly available to help agents and customers have a better service experience.
One category of technology that's very hot right now is real-time agent assistance.
With real-time agent assistance, you can ensure that your customers have the best possible experience since your agent is backed up with lots of additional information, context, and cues and constantly suggests and proposes optimizations for their work.
But is this actually the best way to provide the optimal customer experience?
Let's dive in!
The way things are
When we think about the history of agent assistance, we might picture a basic CRM displaying the customer's information, details of their complaints or issues, and some other demographic information.
Sure, this adds more context for the agent, but it's insufficient to help them truly address the user's unique meet. That means that customers are asked a lot more clarifying questions, and agents and supervisors spend way too much time making discoveries rather than providing solutions.
That's why the development of AI-powered real-time aging assistance technologies has been huge over the last year. As the large language models that power popular AI tools like ChatGPT and Perplexity have improved, they've been applied in a wide variety of business use cases, none more so than in generative AI tech.
And no industry is better suited than perhaps customer service.
For example, because these AI models can understand human language inputs from your users, they can keep up with the conversation and provide contextual help in real time.
If it recognizes the user is facing an issue seen elsewhere, it can suggest to the agent a resolution that seems to work in other cases.
Or, if it notices your agent going off script, it can correct them and offer cues to get back on script.
It can also assist with time-saving the call, for example, in providing a summary of the call's content and recommended course of action to improve resolution and speed.
It can also help organize your support team, for example, by routing calls and organizing tickets more efficiently and ensuring that your supervisors have their eyes and ears across the entire team in real time. This gives agents immediate and contextual help when they're on calls and in chat and provides a better experience for agents and customers.
Imagine that a customer has called in with an issue about a new feature. As they asked questions, perhaps the real-time agent assistant linked to the agent a couple of Articles from the knowledge base to help them and questions live.
There are a lot of use cases here. But what are the actual benefits?
Benefits of real-time agent assistance
So, this technology seems pretty cool, but why does it matter to you and your users?
The first and most obvious answer is speed. As the real-time agent assistant operates in the background and not only provides your agents with lots more information, it allows them to answer questions quicker, moving through more tickets and providing a lower time to resolution for users.
This, in turn, increases user satisfaction and happiness, as they're not left waiting around on hold.
Plus, it means that they're getting more accurate information more consistently and reducing your follow-up tickets or reopening.
All in all, this creates happier agents and customers. Everyone is working more efficiently and more smoothly.
Key features of effective real-time agent assist systems
So, how do you set up your real-time agent assistant system effectively?
Well it's really important that you have great help documentation in the first way. If your sources of truth aren't truthful, your agents will be getting information that is not great.
Once you connect the assistant to your existing technology stack, you can begin to experiment with the tool and see what it is. Remember that getting going might be friction, so testing is key.
But once it's live and operational, it should consistently improve and improve. Your agents can give feedback on the agent assistant and impact the evolution and Improvement of the agent assistance itself. Remember, this can be a two-way street.
How do you actually implement a real-time agent assistant?
Before you jump in and purchase software, it's essential to think through how it incorporates into your overall customer service strategy.
Ask yourself:
- Why are we interested in this technology?
- How will it work with our agent?
- What does success look like?
- What metrics will be used to determine that success?
Having a clear and shared vision and strategy is essential before choosing technology.
Once you're ready to evaluate providers, choosing a software product that incorporates your existing stack and fits your specific needs is essential. For example, the needs of a chat-only support team versus that of an omnichannel chat, voice, email, and ticketing team might differ in scope, size, and complexity.
Now, even if you're excited about a tool, you must remember that all your agents need to be onboarded and educated about this tool. That will be a true deal-breaker and how effectively this will be incorporated into your CS teams.
Does the product have easy-to-understand features and onboarding resources to help you bring your employees up to speed?
Are you being offered a testing period to trial it with some of your agents?
If not, it might be a red flag. You'll want to thoroughly test how agents and users respond directly and indirectly to the changes impacted by your agent assistant.
If successful, you can bring this real-time agent assistant to your entire support team, but that doesn't mean your evaluation has ended. Rather, you should constantly look for ways to improve your operation.
One note
It's a turbulent time to be a support agent. On one hand, there are more software users than ever to help.
On the other hand, AI-powered tools are beginning to endanger the livelihoods of millions of support agents. When you introduce this real-time agent assistance to your team, it's crucial to have clear messaging about how their roles are still important in the company and how this assistant is there to empower them, not replace them!
What’s better than real-time agent assistance? A user Copilot
Real-time agent assistance is great. I can't argue against that.
But it's important to mention that as great as it is, it would be even better to deflect that conversation or ticket in the first place. It's vital to have a first line of defense, or a first line of support, for your users to interact with. Not everything needs to be elevated to an agent.
The days of having to call in or chat with a support agent every single time are over.
There are plenty of situations where it is actually better for the user to interact with an AI agent first to get a quick answer and then move on with their day.
This has resonated with our customers who have deployed our Copilot product. It acts as an assistant for the user, as the first point of support/contact in the product.
When users have questions, they click on the bottom right and can chat with Copilot. Because Copilot is connected to all of your help documentation, knowledge base, and other data sources, it's fast, responsive, and always up to date (as long as you keep your help docs up to date!)
Plus, it's integrated with our other nudges, product tours, and checklists, which can launch directly from the copilot. That's helpful, because sometimes a text answer isn't the best way to show them a workflow or a feature, it's rather to more explicitly walk through it or call it out in product.
This provides the fastest and smoothest experience for users because many questions can be answered in seconds, not minutes, with no waiting for an agent.
Conclusion
If you want to empower your agents to provide the highest quality support and give your users the best possible experience, you should deploy both a real-time agent assistant tool to help your agents be their best selves AND a front-end user Copilot which can assist users themselves and deflect tickets from being created in the first place.
