AI-Powered Retail: Elevating Customer Support Amidst Holiday Rush

At this point, doing one's holiday shopping at the mall feels almost like a nostalgic throwback — not far removed from listening to music on vinyl or taking pictures with a disposable camera. The records for online holiday shopping are broken on what seems like a yearly basis, with last year's $9.12 billion representing the highest number yet. That said, delivering packages to their destinations presents challenges. Obstacles such as reduced vessel passage in the Panama Canal due to drought and unpredictable weather conditions, like the U.S. winter storm last year, persistently disrupt various industries, impacting not only retail but also manufacturing and travel.

These issues are, to some degree, unavoidable and out of the control of brands. What is in the control of brands is how they handle the inevitable barrage of queries to a contact center from customers who are upset about their delayed holiday gifts.

The solution to overburdened fully human staffed call centers is self-evident and growing more popular by the day: the next-gen, generative and conversational artificial intelligence-powered customer support chatbot.

What Companies Are Getting Wrong About Customer Support

Our current supply chain infrastructure hasn't yet caught up with the post-pandemic explosion in online shopping. And when we consider the fact that U.S. parcel shipping volume is up by almost 9 billion parcels since 2016 — or the fact that product returns are today nearly double their pre-pandemic levels — it comes as no surprise that customer complaints are surging.

Customer service agents are aware that some companies are not monitoring any of their customer conversations and, thus, aren't learning how to improve contact center agent training. In a recent study, 83 percent of agents cited a lack of data and/or appropriate tech tools as the largest barrier to resolving customer issues. And in a sense, it's not these companies' fault; there is simply a limit to the number of calls a fully human-staffed contact center can handle. The average call center has 4,400 calls in a month and misses 48 of them; meanwhile, the average agent can handle about 20 calls per day, spending about 31.8 minutes per activity hour on each one.

Customers Are More Fickle Than Ever — and Only AI Can Help

There's a reason Gartner predicted in 2022 that chatbots will become the primary customer service channel within the next five years. With relatively minimal upfront set-up work, brands can use AI-enhanced chatbots to drastically reduce or outright eliminate most of the problems they witness at their call centers — and create new benefits in the process.

Customers highly value AI-driven improvements in customer service. An 80 percent majority of U.S. consumers, as per a recent PwC report, prioritize speed, convenience, knowledgeable assistance and friendly service. They back this preference with action; 59 percent of U.S. customers would permanently abandon a business after just one negative experience, as outlined in the same report.

Why Generative and Conversational AI-Powered Chatbots Are Crucial for Excellent Customer Support

AI-powered chatbots can now serve as the first line of defense for contact centers, handily taking care of the kind of routine, mundane tasks that once occupied the majority of human agents' attention. And most importantly, these chatbots can interact with customers at any time, 24/7/365, and in multiple languages. Accordingly, human agents are freed to spend their by-necessity limited working hours tackling the kinds of complex issues that only they are capable of handling.

Furthermore, AI helps these human conversations, too. Instead of having to put customers on hold while they frantically seek out this or that bit of relevant information — thus putting customer satisfaction on the line — human agents can now rely on chatbots to quickly and automatically aggregate customer and company information, which streamlines assistance and allows for more robust, contextual recommendations.

So let's turn back to the holiday season for a moment. Let's say a customer ordered a gift and that gift has failed to arrive in time. In the first scenario, a customer calls customer support and faces immediate hold times. An agent finally answers but faces difficulty finding the customer's purchase history. Another extended hold follows, potentially resulting in permanent loss of their business.

With AI-powered chatbots, the customer explains the issue, gets the update on their order status, and is offered alternate solutions which might include personalized offers to compensate for delays, ensuring a satisfied customer who is eager to return. Crucially, they don't endure long wait times on calls and receive instant convenience. Furthermore, consider a scenario where a customer has an item in their cart but hasn't made the purchase. The chatbot takes action by sending a text prompt encouraging payment completion. It also offers a time-sensitive holiday discount tailored to the specific product, aligning with pre-set backend rules to entice customers to finalize their purchase within a set timeframe.

With unprecedented levels of online shopping, tough competition between brands, and unavoidable delay in delivery, only businesses that integrate generative and conversational AI into their customer support will come out on top. Those that don't will risk losing customers. For that reason, there has never been a better time for company leaders to look into third-party vendors that can help automate customer support to reduce service interactions, speed up resolution times, offer next-level personalization, and increase customer satisfaction.

Raghu Ravinutala is the CEO and co-founder of Yellow.ai, the world’s first dynamic automation platform built on multi-LLMs to deliver personalized conversational experiences.