If you had to pick a single, universal villain for every book, movie, and TV show, who (or what) would you choose?
Here’s one that’s sure to resonate: slow customer service.
Hold music, chat queues, and delayed responses are the bane of the customer experience. (And they’re not much fun for agents either.)
Of course, slow resolutions are also bad for business. And that’s why so many support leaders fixate on metrics related to support speed and efficiency. Not only does it help keep customers happy, but it makes the whole operation run more smoothly.
One critical metric involved is Average Handle Time (AHT)--or, how long agents spend resolving each ticket in the queue.
It’s really a no-brainer. Lowering AHT can lead to:
It’s important to realize that while average handle time can give us some indication of the efficiency of support operations, it’s not a success metric, per se. Having a lower AHT won’t necessarily mean good things in every case. There are many ways for teams to artificially lower the AHT or do so in a way that actually leads to worse service and support.
You shouldn’t sacrifice quality of service in order to make your agents “faster.”
If your organization is on a quest to reduce the average time spent on each support request, first take stock of how your operation is structured and what opportunities exist for improvement.
There are many strategies that can be used to reduce the AHT while maintaining a high level of service--even improving the overall customer experience.
Nothing kills the efficiency of support like requests ping-ponging between teams or agents.
If your operation consists of different types of agents or support teams, it’s absolutely critical to develop a clear strategy for how to route and handle different types of calls. Especially with omnichannel support growing in popularity, it’s not always as simple as having an IVR that sends customers to support or billing.
Instead, you need to have a way to understand the type and severity of the request, route it to the correct type of agent, and ensure that they have all of the necessary information and context to solve the problem.
There are different strategies and approaches for different types of support.
But, at a high level, requests can generally be categorized/routed according to a simple series of qualifications:
The more sophisticated and optimized this process (e.g., categorizing specific agent skills and routing them the most appropriate requests), the better the results.
We hear a lot about how technology is chipping away at the role of human agents. But, the truth is that, at least for the foreseeable future, we’ll need people to answer difficult questions and solve complex problems.
But that doesn’t mean technology can’t still play a role.
One of the best ways to use technology to improve service and reduce average handle time is to use AI to augment human capabilities--equip agents with AI tools that help them solve more problems in less time.
The benefit here is straightforward. Human agents can team up with AI to retrieve answers and resources instantaneously, and then use human judgment to provide the most accurate or relevant information to the customer.
In 2017, the research firm Aberdeen found that support agents spend, on average, about 15% of their time finding relevant information in response to a request.
So, theoretically, AI alone could help reduce the average handle time by as much as 1/6th.
In lieu of entirely automating common requests, another simple way to reduce time and effort spent on tickets is to develop a catalog of responses to the most frequent questions.
If your agents are facing a huge number of requests for the same kind of issues--resetting a password, changing a setting, signing up for a service, etc--then a simple solution is to develop and distribute responses for these particular cases.
While it may not be the optimal solution, this can even be implemented with limited technology. A simple spreadsheet or database with specific issues and pre-written responses could dramatically cut down on the time spent answering repetitive questions.
More sophisticated strategies use bots and AI to analyze a request and automatically generate a response for the agent to send.
While support leaders often think of omnichannel in terms of creating a unified experience, customers are often most focused on simply having support options and being able to choose them freely.
A study from ICMI made this clear. Of those surveyed, 87% said that they expect companies to simply point them toward the support channel that will get their issue resolved the fastest.
For companies, of course, there’s the challenge of making the process seamless.
Without the right technology, moving requests from one channel to another actually becomes an impediment to service. If you’re not able to translate a previous chat request into documentation on a phone call, then you’re only providing multichannel support--not a unified, omnichannel experience that customers want and expect.
In most cases, the barrier to this reality is technical. Companies need the right tools and technology for it to happen.
With an omnichannel experience, customers won’t have to repeat themselves. Agents will have broad context about that customer’s previous points of contact and be able to more quickly understand and resolve issues. This reduces the amount of time spent on individual tickets.
Although there are many technological solutions that can help reduce AHT, it can’t help in every case.
Many times, the way an agent interacts with the customer plays a huge role in the direction of the conversation and the efficiency of the interaction.
One of the most important skills for agents to learn is how to use closed-ended questions to guide the conversation and understand the problem more quickly.
Open-ended questions can sometimes lead to wandering or unclear responses, which make it more difficult to solve the problem at hand.
Training agents on a series of progressive, closed-ended questions can help them understand the problem more quickly and get to the right solution. This alone can dramatically reduce how long it takes to resolve tickets.
Although improving your AHT is a noble cause, it’s not the end-all, be-all metric for measuring customer support.
In fact, many ways that you can improve your overall customer experience may lead to an increase in the average handle time.
That might seem contradictory, but it’s not.
One simple example: Using chatbots as a front-line support tool helps customers resolve simple questions more easily. But if simple inquiries get handled by bots, that means the requests your agents will receive are likely to be more complex and time-consuming. The average time spent on each ticket may increase for the requests that get routed to a live agent because, on average, they are more difficult to solve.
On paper, this looks like a decrease in efficiency. But, with context, it’s clear that this is exactly what should happen as you deploy new tools to improve your service and support.
Remember that above all else, the goal should be to provide the highest level of service.
Often, expediency is the result of a smart and efficient support system that helps people quickly resolve their questions and issues.But that isn’t always the case.In order to truly provide the best customer experience, you must have a clear strategy and framework. Understand the metrics within the context of that strategy. Then focus on making improvements that matter to the customer, not the ones just meant to pad the stats.
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