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Support And Customer Development Go Hand In Hand

Prior to the emergence of ChatGPT, the customer experience (CX) industry had undergone massive shifts toward automation. When customers can assist themselves with online self-service or receive answers to queries through automated support, CX organizations have the opportunity to enhance their support strategy.

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Combining AI and automation enables CX teams to add value to customers in novel ways. In addition to resolving support issues, AI and automation can assist organizations in improving customer segmentation and driving robust analytics with meaningful customer data points.

In excess of Transactional Support

Customer service should not be viewed through the lens of transactions. Therefore, support teams should not be evaluated solely based on their ability to keep conversations brief. Too often, I observe customer support situations being handled as one-off situations in which you need to “get rid” of the customer as quickly as feasible.

I believe it’s time for CX executives to take a broader look at the ecosystem of customer support and to think creatively about the human element of establishing customer relationships.

When customers contact your brand with inquiries, concerns, or feedback, are you driving them away or deepening your relationship with them? What if your customer service team, rather than being transaction-focused “question answerers” who attempt to end each call as quickly as possible, could become brand advocates and loyalty builders?

Let’s examine how CX leaders can reshape the function of the support team and strategically drive customer engagement.

Alter the Metrics of Your Customer Support team.

New metrics can be utilized by CX executives to demonstrate the value of customer support. Traditional metrics such as average talk time, average handle time, and average speed of answer tend to place the wrong emphasis, and it becomes all about how quickly your agents can conclude a conversation with a customer.

These traditional customer support metrics date back to a time when phone calls and emails were the most common means of resolving customer issues. I believe that we need metrics from the next generation to demonstrate how effective customer support representatives are at fostering customer engagement and loyalty.

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What if, for instance, the CX industry developed a metric to compare the total engagement time to the customer satisfaction score? Your organization could measure the customer’s level of engagement and how they feel about your brand, as opposed to simply how swiftly your representative concluded the conversation.

By effectively implementing AI and automation using the steps outlined below, you can free up the time of your employees and transfer your focus to team metrics.

Utilize Technology to Offer Asynchronous, Low-Contact Problem Solving.

Customer support automation should not feel robotic; rather, it should be personalized and leverage contextual information and customer identity verification. It should also solve the customer’s problem promptly and to the customer’s satisfaction.

For instance, suppose a customer who is set up for auto-payment receives an unexpectedly large payment from your company. They call your customer service number and spend 45 minutes on hold, navigating menus, proving their identity, and transferring to different support teams before receiving the following response from your company: “Your monthly usage pushed you into a higher price tier.” We apologize, but the payment amount was accurate.”

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In the end, the company was required to expend resources in order to respond, and after 45 minutes, the consumer remained frustrated. What if there was a better method to provide support on the customer’s terms, in their time frame, and with a more satisfactory resolution?

Now, let’s suppose this brand had in-app messaging, AI automation, and pre-established business rules for dealing with important customers. When a customer discovers a billing discrepancy, they promptly contact support via messaging. Artificial intelligence analyzes the customer’s message and determines that the customer is concerned about an overpayment.

With an optimized system, the AI would be able to formulate the following response: “I see that you are apprehensive about overpayment. Based on your recent account activity and account utilization history, you were placed in the “high-usage” plan for the month.

This is a standard response for overpayment inquiries; the consumer is now aware of the situation without having to wait on hold. Nonetheless, this consumer continues to feel frustrated. They have been with the company for a very long time, and they desire action.

Customer: “Okay, but nobody informed me.” I may terminate my service.” Currently, the AI has been pre-trained to provide loyal consumers with special offers, such as a 5% discount.

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AI: “As a loyal customer, I am able to offer you a 5% discount on the new plan. Would you like this price reduction?”

Your customer support journeys can be asynchronous and mobile app-first as opposed to the conventional “hold music” method. Customers do not always require an immediate response; rather, they require support that accommodates their schedule. This approach to automated support can free up your customer service representatives to handle more complex or nuanced situations.

Increase Your Bets On The Human Element

Every customer service interaction is a chance to expand your relationship. When a customer contacts your support staff, they are frequently in a vulnerable state: they have an issue or question and are seeking assistance from your brand.

Are you utilizing this moment to develop and strengthen your relationship with your customers and encourage them to spend more time with your brand? Or, do you view customer service as a transaction that leaves no lasting impression on the consumer and even drives them away?

Stop providing customer support in an effort to lose customers. I urge you to encourage your support staff to utilize these opportunities as touchpoints to collect customer feedback and data, to better understand your customers, and to strengthen customer relationships.

Customer support organizations have a tremendous opportunity to demonstrate their worth as brand ambassadors who unearth valuable data insights that boost engagement and long-term ROI.

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