The number one cost driver in any call center is labor expense, and its also the one you can best manage and control.

Here we'll discuss the two best ways to deploy Contact Center AI to reduce staffing requirements and your cost-per-call.

And for the interactions that do require a call center agent, handle those with as few agents as possible while still providing an exceptional customer experience.

Automate Voice Interactions with Natural Language IVR

Despite efforts to move customers to self-service options, such as using a knowledge base, sometimes they are still going to pick up the phone and call. The industry standard cost-per-call is in the range of $5-$8 per call.

The best way to reduce call center costs is through voice automation and conversational AI. Typically, the cost of an automated voice interaction is 10-15% compared to live agent costs. If you can voice automate calls and reduce the number of agents required to handle the remaining calls, then you can significantly reduce your call center expenses.

Traditionally this is done through an Interactive Voice Response system (IVR), most of which do not support advanced speech recognition. Until recently, a natural language IVR was limited to handling simple interactions, such as having a customer speak their account number, and then returning basic information such as account balances. On premise IVRs are also expensive and time consuming to deploy, which also limits your ability to handle call volume spikes.

However, with the rapid adoption of cloud based telephony and new innovations in natural language processing, call centers can often deploy a cloud based conversational IVR within a few days. If you currently do not have any IVR self-service capabilities, then deploying an AI IVR will be a giant step forward for you.

If you have an existing dialogue-directed IVR today, then a platform such as Xaqt's Cognitive Voice Automation Suite will improve your self-service effectiveness by automating more call types.

As an example, a typical speech recognition IVR does not let customers ask open-ended questions, such as "what is your return policy?". With Conversational IVRs powered by Artificial Intelligence, you can map commonly asked questions to a knowledge base and handle interactions that would have otherwise required a live agent.

Now, instead of handling 15-20% of your overall voice interactions in an IVR, you can automate a much higher percentage. With our Cognitive IVR platform, we're seeing IVR success rates about 85% on many call types.

Reducing Staffing Costs with Improved Forecasting and Scheduling

Let's face it, as much as we may try, not all calls and interactions can be automated. Which means most companies are still going to require human agents to answer the phone. Creating efficient staffing plans for your agents is critical to managing your labor expense.

Call Center Optimization and Workforce Management products that generate call volume forecasts with staffing requirements and agent schedules have been around for decades, but new advancements are making them more automated and affordable.

By integrating new data sources and using machine learning, we can create more accurate call volume forests than previously possible. Now, instead of using historical call volume alone and rolling averages to forecast the future, you can use a call center data warehouse and data science to predict call volume arrival patterns and demand with higher degrees of accuracy.

When you have more accurate plans, you prevent periods of over-staffing and avoid being understaffed. By optimizing your call center operations and scheduling, you will reduce your staffing requirements and cost-per-call while improving your customer experience.