AI and the Customer Support Life Cycle
Customers are increasingly turning to digital channels as their first choice for customer support interactions, with studies showing that 81% of customers attempt to resolve issues themselves before reaching out to a service representative. To meet this growing demand for digital support, many organizations are exploring the use of AI-powered solutions that can improve the customer experience and increase satisfaction while delivering greater engagement. In this post, we’ll explore some of the ways that companies are leveraging AI to enhance customer support and provide a more personalized and efficient experience for their customers.
Before we dive into the key benefits of AI-powered customer support solutions, it’s important to understand the driving forces behind their adoption. For many companies, COVID-19 was a wake-up call that highlighted the need for a “digital first” approach to business and customer support. In addition, the purchasing power of millennials and Gen Y, who make up 20% of the U.S. population and are comfortable with digital channels, is driving the need for do-or-die digital adoption. For those companies that have embraced AI-powered solutions to deliver faster, more personalized support, the financial and customer upsides are significant. As McKinsey notes, “AI-enabled customer service can increase engagement, reduce cost-to-serve, and generate cross-sell and upsell opportunities. In fact, the research estimates that AI technologies could potentially deliver up to $1 trillion of additional value each year in global banking alone.”
“AI technologies could potentially deliver up to $1 trillion of additional value each year in global banking alone.”
This article shared these stats associated with bad customer experience . . .
78% of customers have backed out of a purchase due to a poor customer experience.
65% of customers said they have changed to a different brand because of a poor experience.
After more than one bad experience, around 80% of consumers say they would rather do business with a competitor.
and the positive impact of it . . .
Bain shared that increasing customer retention rates by just 5% can increase profits by between 25% and 95%.
90% of customers rate an “immediate” response as essential or very important when they have a customer service question. 60% of customers define “immediate” as 10 minutes or less.
For 86% of customers, good customer service turns one-time clients into long-term brand champions.
“The estimated cost of poor customer service ranges from $75 billion to $1.6 trillion per year”
AI Is Enhancing the Entire Customer Support Life Cycle
If you’ve ever used a chat or messaging app on an e-commerce or B2B site, chances are you’ve interacted with Intercom’s customer support tools without even realizing it. Recently, Intercom integrated advanced generative AI-powered features into its existing toolkit for businesses. As explained in a detailed post on Econsultancy, these features are designed to improve both support agent productivity and the customer experience. For instance, “Intercom now offers a conversation summarization tool that automatically condenses customer interactions into key bullet points, making it easier for agents to hand over cases to their colleagues. Generative AI can also help adjust the tone and wording of responses to better suit each customer. Another notable feature is Expand, which can turn a short note from a support agent into a full-fledged reply using AI-generated language.”
Consider how each phase of the customer life cycle can be augmented by AI:
Pre-purchase support: When a potential customer has questions or concerns about a product or service before making a purchase, an AI feature can proactively answer questions about the product, its features, pricing and availability.
Purchase support: AI support can facilitate activating a product or service, or address any issues with a purchase, such as billing or shipping issues.
Product support: During the product use phase, customers may need assistance with troubleshooting, maintenance, or repair. AI support can help with installation, configuration, or software updates.
Billing support: Customers may need help with their bills or payments, such as billing inquiries, disputes, refunds, or cancellations. AI can expedite these tasks that would normally require a customer support representative.
Post-purchase support: After the customer has used the product or service for a while, they may need support for additional features, upgrades, or customization. AI can help with this as well as with warranty claims or returns.
Elevating the Role of the Support Agent
It was reported here that the estimated cost of poor customer service ranges from $75 billion to $1.6 trillion per year.
AI can have a significant impact on the customer support life cycle, providing faster and more personalized support to customers. For example, AI-powered chatbots can provide 24/7 customer support, answering common questions and resolving simple issues, freeing up human agents to handle more complex queries. AI can also analyze customer data to identify patterns and trends, allowing companies to proactively address potential issues before they arise. In addition, AI-powered voice assistants can help customers with technical issues or provide product recommendations, making the customer experience more seamless and convenient.
Here are some of the key benefits of using AI in customer support and how they can improve the customer experience:
Faster response times: AI-powered chatbots and virtual assistants can provide customers with instant support and answers to common queries, reducing wait times and improving response times.
24/7 availability: AI-powered chatbots and virtual assistants can provide 24/7 customer support, enabling customers to get assistance at any time of the day or night.
Personalization: AI can analyze customer data to provide personalized support and recommendations. For example, AI can use past purchase history or browsing behavior to recommend products or services that are relevant to the customer’s interests.
Proactive support: AI can analyze customer data to identify patterns and trends, allowing companies to proactively address potential issues before they arise. For example, AI can flag potential billing issues or product defects and notify customer support teams to take action.
Improved self-service: AI-powered chatbots and virtual assistants can guide customers through self-service options, helping them to quickly resolve simple issues on their own without the need for human intervention.
Reduced costs: By automating certain customer support tasks, such as answering common queries or providing basic troubleshooting assistance, AI can reduce the workload on customer support teams, freeing up human agents to handle more complex issues.
Striking the Right Balance Between Human Agent and AI-Powered Customer Support
AI-powered customer service needs to go beyond just automation. While chatbots, for example, can simplify customer interactions and reduce costs, customers typically use multiple channels.
As shared in the previously mentioned McKinsey post, “An estimated 75% of customers use multiple channels in their ongoing experience. A reimagined AI-supported customer service model therefore encompasses all touchpoints—not only digital self-service channels, but also agent-supported options in branches or on social-media platforms, where AI can assist employees in real time to deliver high-quality outcomes.
For example, the system might flag that the customer’s credit-card bill is higher than usual, while also highlighting minimum-balance requirements and suggesting payment-plan options to offer. If the customer calls, the agent can not only address an immediate question, but also offer support that deepens the relationship and potentially avoids an additional call from the customer later on.”
For companies to compete and meet the digital demands of today’s customers, they will need to strike the right balance between a human agent and AI-powered customer support solutions for improving the customer experience across all touchpoints. The financial and business impact of AI on the customer support life cycle can provide faster and more personalized support to customers while freeing up human agents to handle more complex queries, all while converting one-time customers into long-term brand champions and potentially increasing profits by between 25% and 95%.
Questions? Please email me here. As always, thank you for reading.