In 1990, researchers from Harvard Business School published an article, The profitable art of service recovery, that described how mistakes can be a company’s best chance to cement customer loyalty. The phenomenon they documented became known as the service recovery paradox (SRP). This refers to a situation in which a customer thinks more highly of a company after the company has corrected a problem with its service, compared to how they would feel if no service failure had occurred in the first place. In other words, an effective service recovery can potentially result in higher levels of customer satisfaction than a scenario where no service failure took place.
This phenomenon has been studied many times over the interceding decades. A meta-analysis of these studies reported that, “...the paradox is related to a secondary satisfaction following a service failure in which customers compare their expectations for recovery to their perceptions of the service recovery performance. If there is a positive disconfirmation, that is, if perceptions of service recovery performance are greater than expectations, a paradox might emerge (secondary satisfaction becomes greater than prefailure satisfaction). Otherwise, in the case of a negative disconfirmation, there is a double negative effect, as service failure is followed by a flawed recovery.”
Several key points underlie SRP including perceived justice, trust, memorability, and limitations.
Perceived justice is when customers assess the fairness of the recovery efforts. This can be thought of in terms of fairness of the process used to resolve the service failure or fairness of the outcome. Regarding trust, customers may feel that if a company handles service failures well, they can be trusted in future interactions. Recovery situations, especially when handled well, can be more memorable than ordinary service encounters, leading to stronger perceptions and memories of the event. It's essential to understand that the service recovery paradox doesn't mean companies should intentionally fail just to showcase their recovery efforts. Repeated failures can erode trust. The paradox might not always manifest, especially if the service failure is considered severe.
While often touted as a marketing tool, SRP should be considered larger than just marketing but inclusive of product and engineering as well. The straightforward case would be when a service interruption occurs or when a feature rollout doesn’t go as planned. Product and engineering should consider ways in which they can make it up to their customers. Can you provide some additional feature set for a period of time as a way to make it up to customers? This of course requires thoughtful consideration ahead of time to make things like this easy to wire on/off when needed.
We as product and engineering should also be thinking beyond just the case of a service failure but how can every interaction with customer support be a loyalty building event. I think excellent customer support should be considered a competitive differentiator. Companies have gone so far in trying to reduce costs by automating email responses and requiring phone tree manipulation, that we as consumers are taking this into account during our purchase decisions. If one company helps me resolve issues quickly and in a human-centered manner, I am more likely to purchase from that company than a competitor with equal product offerings who make any support issue a completely frustrating interaction.
How can we improve our company’s customer support interactions without significantly increasing costs? Enter generative AI and chatbots. A recent study compared chatbot responses to physician responses in almost 600 interactions. The chatbot responses were rated of significantly higher quality than physician responses. Chatbot responses were also rated significantly more empathetic than physician responses with 9.8 times higher prevalence of empathetic or very empathetic responses for the chatbot. Let me just repeat that last sentence, chatbots were 10x more likely to demonstrate empathy than physicians. If we could do this with our customer interactions and maintain a similar cost structure, that’s a huge win for both customers and our companies.
Chatbots aren’t new and while genAI has the potential to make them much better, they’ve been around for many years. The big difference that I’m advocating for is that companies see interactions with customers as opportunities for generating loyalty, future purchases, and higher conversions instead of just a necessary evil where the cost should be minimized. Change the customer support functions from just an expense into a P&L that has metrics and goals geared towards customer loyalty, lifetime value, repeat purchase rates, etc. that increase revenue.
It’s been reported that 93% of customers are likely to make repeat purchases with companies that provide excellent customer service, while 78% will stay loyal to a business after a mistake if the service is excellent. This retention is important as a study demonstrated that repeat customers spend 67% more than new customers. With no additional marketing we can achieve a significant increase in AOV (average order value) through great customer support resulting in more repeat purchases. This data all makes a case for investing in better customer support and we’re very fortunate to be at a time when we can achieve that mostly through the use of gen AI and chatbots.
If you don’t already have work being done to integrate genAI bots into the customer support flow, I highly recommend that you consider doing so. The way to justify this isn’t through cost savings and staff reductions but rather through increased revenue that can be generated with these efforts. The key is going to be having the goals and metrics set up to measure and credit customer support interactions with customer loyalty, repeat purchase rates, and higher AOV. Now is the time to start thinking about customer support as a differentiator for your business.
One of the projects I managed the year I was at Nike was an overhaul of their internal customer support knowledge base system. Getting a front row seat to their customer service approach was fascinating. No outsourcing to some budget call center. Every customer service agent was a full time Nike employee, seated at HQ in Beaverton. Because so much of Nike's value is tied up in their brand, they saw robust customer support as brand protection and a key competitive differentiation. Their goal was not to minimize spend on customer support as a loss leader, but to maximize the impact of what they were committed so spending on customer support as differentiation. I can only imagine that they are rapidly augmenting customer support with genAI as a quantum leap forward from the old knowledge base tools they previously relied on.
I've often thought that customer support and marketing should share the same budget given that they're both really in the customer LTV business. Does it make more sense to spend a dollar trying to acquire or reacquire customers through marketing or to invest in customer service in ways that will retain existing customers. Whenever I talk to folks in customer support they have tons of ideas for making customer support better, but they never seem to be able to obtain the budget to actually pursue these ideas, and the tradeoff with the marketing budget is the one that makes the most sense to me.