Technological advancements have pushed nearly every industry to evolve over the past decade, and customer service is no exception. While technology such as artificial intelligence (AI) has helped streamline processes and eliminate the need for labor, there is an argument to be made that companies should still prioritize human agents.
In customer service, the human element remains a crucial component to the customer experience. While AI has given companies the opportunity to cut agent costs and implement practices such as automated responses and chat bots, relying solely on technology has created new and sometimes frustrating challenges for customers.
While converting to solely an AI-powered customer service model might not be the most beneficial, parts of it can still be effective if implemented the right way. When it comes to customer service, it's all about the balance of technology and empathetic human agents.
According to the National Retail Federation (NRF), retail sales during 2021's November-December holiday season grew 14.1 percent over 2020 to $886.7 billion, surpassing the NRF&r's forecast and setting a new record despite challenges from inflation, supply chain disruptions, and the ongoing pandemic.
With the uptick in online sales, companies experienced an uptick in customer service inquiries. As a result, retailers started 2022 with a hefty backlog of inquiries from the 2021 holiday season. When companies are working hard to keep up with a rise in customer service inquiries, customers can experience underwhelming service. When balanced correctly, AI can complement agent efforts by flagging inquiries that need human intervention vs. those that can be solved through digital prompts, which have the added benefit of sometimes reducing human error.
An example of this is the process of price adjustments, which naturally occur around the holidays or any big sale where customers want to return items and re-purchase them for the sale price. During the process of making a price adjustment, an agent would have to return a product, manually calculate the sale percentage and sales tax, refund the customer the money they saved and then re-purchase the item for the sale price. This process can be tedious and leaves room for error when done manually. However, when coupled with AI, a software platform can automatically adjust the price for the agent at a faster and more accurate rate. This leaves time for the agent to provide quality conversation with the customer while completing more customer tickets.
More Data, Less Error
The other main function of AI in customer service lies within the valuable data it collects for companies. Without AI, companies would typically have agents input data manually into spreadsheets and other outdated tracking sources. This not only leaves room for human error, but makes companies rely heavily on agents to complete this task. With a structured AI software system, specific customer actions, decisions, and inquiries can be automatically recorded for companies to later reference. This helps companies gain insight, feedback, and customer behavior on specific products or services, which can in turn help improve business practices.
If a company has a pair of activewear pants that are a best seller and has recently seen an influx in returns, not only will the retailer be able to tell how many pairs of pants were returned and when, but they can also answer why, whether it's a defect, sizing issue, or something else that needs to be properly addressed. A direct, accurate look into customer insight is valuable information that companies should be leveraging to improve practices, products, and more.
Technology like AI, overlaid with human intelligence, enables accurate data sharing and smarter business decisions when it comes to customer service. Not only is this a win for companies being able to combat backlog, but it is also a win for customer service agents as they can complete their jobs more efficiently, and a win for customers who will in return receive quality customer service.
Liz Tsai is founder and CEO of HiOperator, provider of a customer service-as-a-service solution that allows businesses to handle client tickets faster and more accurately through human and artificial intelligence.