Eric Vermillion is the CEO of Helpshift.
Even before the rise of ChatGPT, the customer experience (CX) industry has been making huge shifts in the past few years toward automation. When customers can help themselves with online self-service or get questions answered via automated support, this gives CX organizations an opportunity to increase the sophistication of their support strategy.
The combination of AI and automation is opening new ways for CX teams to add value for customers. Beyond just solving support problems, AI and automation can help organizations improve customer segmentation and drive robust analytics with meaningful data points about customers.
Beyond Transactional Support
Customer support shouldn’t be viewed through a transactional lens. Therefore, support teams shouldn’t be measured solely on how short they can make their conversations. Too often, I see customer support situations get treated as one-off moments where you need to “get rid” of the customer and get them off the line as fast as possible. I believe it’s time for CX leaders to take a broader look at the ecosystem of customer support and think creatively about the dynamic human element of building customer relationships.
When customers contact your brand with questions or issues or feedback, are you driving them away or creating deeper engagement? What if your customer support team—instead of being transaction-oriented “question answerers” who try to end each call as fast as possible—could become loyalty builders and brand ambassadors?
Let’s see how CX leaders can transform the support team’s role and strategically drive your customer engagement.
Change Your Customer Support Team’s Metrics
CX leaders can use new metrics to demonstrate the value of customer support. Traditional metrics like average talk time, average handle time or average speed of answer tend to put the focus on the wrong things, and it becomes all about how fast your representatives can end a conversation with a customer.
These traditional customer support metrics come from a time when phone calls and emails were the primary way to solve customer problems. I believe that we need next-generation metrics to show how effective customer support reps can be in building customer engagement and loyalty.
For example, what if the CX industry could develop a metric to evaluate the total engagement time versus a customer satisfaction score? Your organization could measure the depth of engagement and how that customer feels about your brand instead of just how quickly your representative ended the conversation. By effectively setting up AI and automation using some of the steps I outline below, you can free up your employees’ time and shift your approach to support team metrics.
Use Tech To Provide Asynchronous, Low-Touch Problem Solving
Automation for customer support shouldn’t feel robotic; it should feel personalized and leverage contextual information and customer identity verification. It should also solve the customer’s problem quickly in a way that delights the customer.
For example, say a customer is set up for auto-pay and gets surprised by a higher-than-expected payment to your company. They call your customer support phone number and spend 45 minutes on hold, navigating menus, proving their identity and transferring between support teams before finally getting an answer from your company: “Your monthly usage bumped you into a higher price point. We are sorry, but that payment amount was correct.”
In the end, the company had to devote resources to respond, and after 45 minutes, the customer still ended up frustrated. What if there was a better way to provide support on the customer’s terms, on their time, and with a happier resolution?
Now let’s assume that this brand had in-app messaging, AI automation and pre-established business rules for handling important customers. When the customer realizes the bill discrepancy, they contact support immediately via messaging. The AI parses the customer’s message and realizes that the customer is concerned about an overpayment.
With an optimized system, the AI could formulate a reply: “Sorry, I see that you are concerned about an overpayment. Looking at your account history, based on how you’ve used your account recently, you were placed in the “high-usage” plan for the month.”
This is a standard reply for overpayment concerns; now the customer knows what happened without having to wait on hold. However, this customer still feels frustrated. They’ve been with the company for a long time, and they want something to be done.
Customer: “OK, but no one told me. I might cancel my service.” Now the AI has been pre-trained to offer long-time customers special offers, including a 5% discount.
AI: “As a long-term customer, I can offer you a 5% discount for the changed plan. Would you like this discount?”
Instead of a traditional “hold music” approach, your customer support journeys can be asynchronous and mobile app-first. Customers don’t always need the answer immediately; they just need support that suits their schedule. This approach to automated support can free up bandwidth for your customer support people to deal with more complicated or nuanced situations.
Double Down On The Human Element
Every customer support interaction is a larger opportunity to deepen your relationship. When a customer contacts your support team, they are often in a moment of vulnerability: they have an issue or a question, and they are reaching out to your brand for help.
Are you using this moment to build and deepen that customer relationship and make them want to spend more time with your brand? Or are you treating customer support as a transaction that leaves no big impression on the customer—even drives them away?
Stop driving customer support to get rid of your customers. I urge you to let your support team embrace those moments as touchpoints to gather feedback and customer data, to know your customers better and to deepen your customer relationships. Customer support organizations have a huge opportunity to show their value as brand ambassadors that uncover valuable data insights that drive engagement and long-term ROI.
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