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Through natural language processing (NLP) and machine learning algorithms, AI can comprehend and respond to customer inquiries and concerns with remarkable accuracy and speed. Gone are the days of lengthy waittimes or generic responses. Businesses have started adopting Duplex for handling customerbookings.
With AI, bots can also improve their responses over time based on customerconfidence in their answers. Depending on need, these requests can include booking meetings, capturing contact details, or registering attendees for upcoming events.
I’d bet that you have at one time or another called a company for support and heard the recording that goes something like this: “We’re sorry. Due to an unexpected call volume, you may experience longer than normal waittimes.” Some customers dread calling customer support. Your call is very important to us.
Scheduling Complexities: Managing agent schedules to match peak call times is a challenge that plagues most contact centers. Too few agents mean long waittimes and frustrated customers, while too many agents during off-peak hours lead to underutilization and wasted resources.
With AI powering their responses, bots can improve their responses over time based on customerconfidence in their answers. This is known as machine learning, since the bot can develop stronger answers over time according to real-world feedback. Direct customers to relevant pages for answers. Book meetings.
To be responsive, you need to study where, when, and how often customers contact you, then have staff in place to answer them. Not having enough people on the schedule to handle the contact volume will lead to long waittimes, cranky customers, and burned out employees. Read some of our favorite customer service books.
In other words, the standard customer experience paradigm misses the depth and breadth of the customer’s lived experience, which is why it’s time for a paradigm shift. So, what is the customer experience? I am guessing here, but waittime probably has 5X the impact of personalization.
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