Contextual Service
Starbucks is often cited as the epitome of a customer-focused business, inspired by Howard Schultz’s vision of fostering community around coffee. Sitting in Gail’s as I write this, I can’t help but reflect on how many of us equate good service with the cheery greetings and casual chats we share with baristas. However, good service isn’t universal; its quality is judged solely by the customer. A business’s self-assessment of its customer service is ultimately irrelevant.
Consider Sutton and Rafaeli’s (1988) study of 576 convenience stores. They uncovered a surprising negative relationship between employees’ displays of pleasant emotions and sales. Follow-up qualitative research suggested that store pace—measured by sales volume and queue length—dictated these emotional displays. In busier stores, neutral interactions were perceived as efficient and satisfying, whereas slower stores fostered norms favouring positive displays. The lesson? A smile and small talk may work when there’s no rush, but efficiency trumps cheerfulness during peak times.
Empowering Customers or Outsourcing to Them?
Self-service technologies (SSTs) have reshaped how we engage with businesses. When was the last time you called an airline to book a ticket? Likely years ago. Today, we embrace self-checkouts at supermarkets like Tesco, finding them quicker—until a barcode won’t scan and frustration sets in.
SSTs need careful management to avoid alienating customers. Even if user error occurs, the technology should be foolproof. Importantly, customers should still have the option for human assistance, especially when traditional service was the norm. By framing SSTs as an optional enhancement rather than a replacement, businesses give customers the freedom to choose, avoiding the perception of being forced into an inferior experience.
Service Failures and Recovery
A service failure doesn’t have to mean a lost customer. In fact, if a business manages recovery well, customers can leave more satisfied than if the issue hadn’t occurred.
Take my experience with Amazon: I once ordered a pencil to replace my habit of drawing graphs with a pen, only to receive a broken one. Despite the item costing just 49p, I was annoyed. But my frustration dissipated after hitting the refund button and receiving an instant refund. It wasn’t just about being reimbursed—it reassured me that future mistakes would also be rectified seamlessly.
Interestingly, Whiteside (2021) found that loyalty program members are more upset by service failures than non-members. In an era where loyalty programs are often a data-harvesting tool, businesses must prioritise robust service recovery systems to retain their most engaged customers.
The Pain of AI Customer Service Chatbots
Unfortunately, the rise of AI chatbots has eroded some businesses’ ability to handle service failures effectively—a trend I’d call “entshittification.” While we might live in an era of customer-centric rhetoric, dealing with AI bots often feels like a step backward.
When customers reach out, they typically need one of three things:
Information: Chatbots shine here. Acting as a conversational FAQ, they efficiently guide users to pre-existing answers, much like a Google search. This use case reduces company costs and serves customers swiftly.
Service Recovery: Here, chatbots falter. Effective service recovery relies on listening, empathising, and resolving complaints. Making it difficult for customers to voice dissatisfaction risks alienating them permanently. A complaint is an opportunity to rebuild trust; blocking that channel ensures the customer leaves, often for good.
Exceptional Circumstances: Contextual problem-solving often requires human nuance. Humans excel at switching gears and adapting to situations that don’t fit neatly into an algorithmic framework. In contrast, chatbots struggle to deviate from predefined pathways, leading to frustration when a situation requires flexibility.
AI chatbots may reduce costs, but they should never replace human interaction in scenarios that require empathy, creativity, or exceptional problem-solving. A bot might be fast and efficient, but it rarely feels personal—and customer service, at its best, is deeply personal.
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