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If you’re a customer calling into a contact center for support, few outcomes are worse than hanging up without a resolution to your issue.
While an abandonment rate around 5% was once considered average, with the typical contact center hovering around 6% in 2021, that number has undoubtedly increased in the years since as high agent attrition rates and rising call volumes have made it more difficult to resolve every call in a timely manner.
As a result, reducing abandonment rates has become a higher priority for many contact centers to not only enhance customer satisfaction but also boost operational efficiency. Here’s how organizations can use AI to tackle the root causes that lead to high abandonment rates:
1. Optimize agent allocation
Appropriate staffing is essential to manage incoming call volumes efficiently. But as many contact centers struggle to hire and schedule enough agents to handle unpredictable demand, simply adding headcount is no longer a viable strategy.
Instead, contact centers should focus on optimizing how agents spend their time by identifying which call types can free up the most time by being automated end-to-end using an AI-powered solution. After deploying AI to automate patient scheduling calls, Southwest Medical Imaging improved their agent answer rate and reduced their abandonment rate by 20%
2. Ditch clunky IVRs
Interactive Voice Response (IVR) systems are not intuitive and commonly lead to callers pressing the wrong number, zeroing out, or abandoning a call altogether before they even get to where they need to go.
Instead, conversational AI can provide a personalized, natural and accurate experience that not only prevents frustration-driven hang-ups, but resolves a high volume of requests without ever requiring an escalation.
No matter the request type, AI offers a significantly more modern experience than IVRs that reduces customer frustration every step of the way.
3. Reduce handle times
When customers have to repeat information to multiple automated solutions and agents, frustration builds and calls take longer for agents to complete.
With AI, even calls that require agents are significantly shortened through intelligent handoffs that provide agents with a call’s full context and allow them to pick up right where it left off.
This significantly reduces abandonment rates and frees up even more time for agents to spend assisting callers. In one case, risk management leader CorVel deployed AI to automate new patient registrations and achieved a 50% decrease in average handle time.
4. Optimize queue management
Another drawback of IVRs and queue monitoring tools is that they treat every call the same. In reality, many calls that end up in a queue could be easily resolved by AI, and urgent or complex requests that should be prioritized fail to reach the appropriate agent and end up seeing higher abandonment rates.
With AI, every customer request is understood with full context, allowing calls that should be escalated as soon as possible to be routed first and requests that AI can complete to be resolved with no wait.
5. Improve omnichannel experiences
Improving your contact center’s automated experience across channels can alleviate pressure on voice calls and give callers another option when they’re unable to keep talking over the phone.
With AI, customers can receive a consistent experience across every channel and even seamlessly switch between channels when they lose connection or are in a situation where they can no longer talk.
AI can proactively send a text message or chat to continue a conversation and ensure requests are resolved even when interactions are unexpectedly interrupted.
6. Reduce frustrating experiences
There are endless reasons why a customer may get frustrated during a call, but they all increase the likelihood they hang up in the middle of a request. Many AI solutions were purpose-built to eliminate a significant number of these friction points.
AI can eliminate wait times, speak to customers in every language, accurately understand intents even through background noise, repair conversations when customers correct themselves, and much more.
As a result, brands like ECSI, a global financial services leader, have been able to automate tens of thousands of calls per month with CSAT scores on par with even the most experienced agents.
Where to start
The antidote for high abandonment rates boils down to one simple idea: resolving more calls end-to-end. To resolve calls at scale with AI, a solution must combine many layers of machine learning, integrations, telephony and human design to achieve a resolution rate that can truly impact your most crucial metrics.
To learn more about how to evaluate the growing market of AI solutions and take action to begin resolving customer service requests at scale, download the free Ultimate Guide to Using AI for End-to-End Customer Service.
