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            © 2025 NiCE
            How the Increasing Popularity of Bots Is Making Customer Service More Complex

            How the Increasing Popularity of Bots Is Making Customer Service More Complex

            by Nick Martin
            March 28, 2023
            Share

            Bots have officially gone mainstream. Nearly 8 in 10 (78%) people surveyed recently said they have interacted with a bot in the past 12 months, and 40% of millennials report chatting with bots on a daily basis, according to Forbes. Usage within customer-focused organizations is only expected to increase, with Gartner predicting that chatbots will become a primary customer service channel within five years.

            Fundamentally, bots are software programs intended to imitate an employee, either by voice or text communication, and expedite customer service needs. A growing number of organizations are leveraging them to engage with customers alongside classic customer service channels like phone, email, and chat. They offer a wide range of benefits for customer service teams, including 24/7 availability, faster response times, the ability to handle a large volume of interactions, proactive as well as reactive service, and lower costs. In fact, AI trained by subject matter experts to analyze contact center interactions can allow companies to reduce support ticket volume by up to 80% and cost by over 90% per customer contact, according to VentureBeat.

            And bots keep getting smarter: While early chatbots lacked flexibility and could only answer known questions, advances in artificial intelligence and machine learning are fueling bots capable of addressing a customer’s sentiment or determining when to redirect someone to a live agent to get a more personal touch.

            Just as you wouldn’t look to your workforce management (WFM) system to plan employee schedules around interactive voice response (IVR) success rates, there’s no need for a WFM system to plan employee schedules around bot success rates. But because there’s no need to schedule a bot, WFM teams often fail to take into account the impact bots have on their processes; this can be a mistake. Bots remove work items—specifically, easier-to-handle customer requests and interactions—from the queue, which can have a significant impact on scheduling.

            As bots handle simpler work items, the interactions that do make it to a customer service agent are more complex. Perhaps the bots handle simple items like general information or account details, but a customer inquiry about a disputed charge is routed to an agent. When interactions are more complex, it typically takes longer to understand the issue, conduct research, and communicate steps to resolution—all of which increase handle time.

            Because of this, WFM teams need to consider how well they can manage long handle times and what tools they need to ensure truly optimal scheduling. Long handle times pose a particular challenge for WFM teams using traditional WFM solutions, which operate well when average handle time (AHT) is shorter than the planning interval. If, for example, the back-and-forth of an interaction occurs across two hours but the planning interval is 30 minutes, traditional WFM solutions force the time into a single interval, skewing staffing requirements. Newer tools offer a solution by decomposing work items into the activities occurring in each interval, improving forecasted staff requirements.

            Bots continue to evolve, and they’re here to stay. The digitization of today’s contact center has changed the nature of work, and businesses need a WFM solution that breaks the chains of traditional WFM paradigms to stay competitive. Learn more about how NiCE WFM is helping contact centers meet the new requirements of the increasingly bot-driven, flexible blended digital office. 

            About the Author

            Nick Martin

            Nick Martin is the Director of Product Management for CXone WFM. He brings more than 6 years of experience in software product management specifically around WFM solutions and has worked on feature across the entire WFM lifecycle. Nick is credited as an inventor on several patent-pending and two granted-patents pertaining to WFM. Additionally, Nick has previously held roles involving multiple business functions with P&L responsibility. Prior to his corporate experience, Nick served as a Military Intelligence Officer in the U.S Army. Nick graduated with a B.S. in Human Factors Engineering from the United States Military Academy at West Point. Additionally, Nick earned his M.B.A. from Southern Methodist University and professional certificate in Data Analytics from Cornell University.

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