How AI Can Aid in First Call Resolution

First call resolution is an important term. It’s also a somewhat muddy one.

But organizations that can get FCR right stand to clean up big time from meeting this key performance indicator.

Service Quality Measurement Group suggests that for every 1 percent improvement in FCR an organization can reduce its operating expenditures by 1 percent, increase its customer satisfaction by 1 percent, and drive 1 to 5 percent greater employee satisfaction. Improved FCR also is linked to increased upsell opportunities and reduced customer churn, according to SQM Group.

Mike Desmarais, the company’s founder and CEO, last year reported “our research shows that for the average call center, 72% of calls are resolved on the first call, which means 28% of customers have to contact the organization back because their issue was not resolved on the first call. Of the 500 leading North American call centers SQM has conducted an FCR benchmarking study, only 5% of the call centers are at the world class FCR performance standard of 80% or higher.”

There are several challenges related to FCR. One is figuring out what constitutes first contact resolution.

As Bill Price of customer service consultancy Driva Solutions notes in this piece, since so many customers now begin looking for answers online you could argue that those who start there and then need to reach out to a call center are already beyond the FCR stage. He suggests the same could be said of anyone who has to use an IVR before reaching an agent and getting an answer.

Different channels like websites and multi-channel contact centers do give customers greater choice. But if all that does is give them more jobs to do, it’s only a recipe for more customer frustration and higher costs for the business.

These complexities, costs, and and FCR challenges can be attributed in large part to the fact that different channels and customer touchpoints of commonly managed by different parts of an organization. And often there’s little or no coordination among those departments (like marketing and support) and channels (like the website and the contact center).

Another complexity is in how to track FCR. Desmarais says these are a few common methods companies use to do that:

• Repeat call tracking (Did the customer call back?)

• Quality assurance (For which a quality assurance analyst listens and determine if a request was resolved on the first call.)

• A post-interaction customer survey. (So you need to contact the customer again to see if you already had too many interactions with them!)

However, there is some good news here. Artificial intelligence can help organizations address FCR by identifying problems and prescribing solutions.

Price says that “using AI you can find the cause and effect of probably drivers for FCR such [as] redesigned web support pages, new training, simplified knowledge sharing pages, and feedback to the agents…. You can also begin predicting which customers and and issues are likely to snowballs, enabling workforce management to route them to more specialized agents with proven skill to melt snowballs.”

Speaking of using AI to address business requirements and customer service, Technology Marketing Corp. (which published this story) is launching a new event called The Future of Work Expo that focuses on just that.

The Future of Work Expo will address how artificial intelligence, automation, machine learning, and natural language processing are changing, challenging, and improving business communications and collaboration, contact centers and customer service, HR, marketing, and sales.

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