Unlocking super agents with the power of data & AI

Unlocking super agents with the power of data & AI

Imagine spending your entire day fielding calls from strangers, each one angrier than the last—frustrated about problems you didn’t cause and can’t solve. Welcome to the life of a customer service agent. 

Given these challenges, it's no surprise that contact center agent burnout is a top concern in customer service—88% of professionals agree, according to a 2023 survey. With 30% of calls addressing unresolved issues from previous interactions and 14% involving direct complaints, it’s no wonder half of all agents consider quitting, worn down by the relentless wave of dissatisfied customers.

Fortunately, artificial intelligence (AI) is helping ease customer service burnout by transforming agents into super agents. 

However, AI is only as effective as the data it relies on. By consolidating customer data into a unified source of truth, businesses can power AI-driven insights that deliver more accurate predictions, smarter automation, and seamless self-service experiences. This not only improves resolution times but also reduces agent workloads by handling routine tasks—allowing human agents to focus on high-value, complex interactions that require empathy and expertise.

In this blog, we'll explore the rise of AI-powered support and how it's shifting the focus from reactive problem solving to proactive engagement. We'll see how AI enables support teams to provide seamless care across channels and how Twilio’s tools can help you build a team of AI-assisted super agents.

The rise of AI-powered tools

Two categories of AI-powered technology are making the biggest waves in customer service: analytics forecasting tools and natural language generation (NLG) software, such as virtual assistants and chatbots. 

Together, these technologies are reshaping customer care, making it more efficient and proactive.

AI-powered forecasting and analytics

Analytics leverages statistical analysis to spot patterns within data. In customer service, this can mean deep insights into current customer behaviors while also helping forecast future trends.

Analytics can provide key performance indicators like customer satisfaction rates, first response time, and total time to resolution. With these insights, you can pinpoint areas where your team may be struggling and highlight opportunities for AI intervention.  For example, if first response times are lagging, you can introduce AI support to reduce customer wait times.

You can also analyze support ticket data to uncover the most common customer concerns so you can promptly and more effectively address recurring issues that burden your team.

Also, by examining data from your customer journey map, you can predict the actions customers are likely to take after encountering a specific service issue or touchpoint. For example, you might find that customers who don't complete onboarding within a set timeframe are more likely to churn. With this intelligence, you can set up automated workflows to alert a support agent when a customer's data indicates a high churn risk, allowing for timely intervention.

Virtual assistants and chatbots

Virtual assistants and chatbots both use NLG to enable seamless interaction with AI through everyday speech. While these two technologies share similarities, virtual assistants handle broader inquiries and generic tasks, while chatbots focus on specific types of questions and actions. Both play a crucial role in enhancing customer service delivery.

NLG technology is particularly effective at handling routine queries, such as frequently asked questions that don't require human creativity or complex problem solving. For example, lost password requests are a common customer service issue that automated workflows can efficiently resolve. By assigning these straightforward tasks to AI, customer service teams can focus on more nuanced customer needs that demand personalized support.

Virtual assistants and chatbots can immediately begin gathering information from customers, determine if human assistance is required, and route the ticket to the appropriate representative. This approach shortens response and resolution times, reducing call volume and, ultimately, boosting customer satisfaction.

Understanding the reactive vs. proactive paradigm

AI-powered tools are driving a shift from reactive customer support to a more proactive approach. Rather than waiting for support tickets to pile up, teams can use AI to anticipate customer needs and reduce ticket volume before issues arise.

Defining reactive operations

Traditional customer service follows a reactive paradigm. Customers reach out for help only after self-service options have failed, often arriving at the support stage feeling frustrated. This approach tends to result in a backlog of tickets from already dissatisfied customers, creating a high-pressure environment for support staff. The constant influx of issues can negatively affect team performance, customer satisfaction, and agent morale.

Introducing proactive engagement

A proactive customer care strategy, on the other hand, uses analytics data to gain a comprehensive, real-time understanding of customer needs. By mapping the customer journey, support teams can preempt common issues before they escalate and predict when direct assistance will be needed. This also allows for tailored support communications through the customer's preferred channels and an opportunity to up-sell or cross-sell.

You can also use Agent Assist, which deploys AI and uses a centralized knowledge base  to provide real-time agent assistance. Agent Assist provides step-by-step guidance to agents based on customer intent, provides answers to common questions, and generates responses for agents to use with customers. This increases productivity and uplevel skills during customer interactions. 

How AI and customer data empower super agents

AI increases the effectiveness of customer service agents by offering insights into customer profiles, supporting skills development, and automating workflows to boost productivity. Realizing these benefits depends on securing agent buy-in, helping them see the true value of AI in their daily roles.

Holistic customer profiles

AI-driven analytics enable support teams to serve customers with a complete, holistic view of their interactions—combining data from chat, email, phone calls, and account history. These insights allow contact center agents to deliver more personalized and timely support, tailoring their approach based on data-driven recommendations.

Skill enhancement and training

AI accelerates agent training by offering realistic simulations, helping agents gain experience with both common scenarios and specialized issues. With continuous feedback loops from AI analytics, agents receive targeted guidance, so they can adjust and improve their performance over time. This makes AI an effective coaching tool, allowing agents to develop their skills more quickly.

Automated workflows and task management

AI enhances agent efficiency by automating routine tasks. Simple inquiries like password resets, billing questions, and delivery updates can be handled directly by AI. For more complex issues, AI can assist through fully or partially automated workflow integrations, providing support where it's needed the most. 

Leveraging AI to automate routine tasks allows agents to focus on customers who truly need human assistance, boosting overall productivity and maintaining consistent service quality.

Getting agent buy-in

To fully unlock the benefits of AI-powered customer service, it's essential to engage customer service agents in the process. Consider these key strategies for fostering agent buy-in:

• Involve customer service agents in conversations and decision-making from day one.

• Use generative AI to enhance ticket summaries with tools that are tailored and user friendly. 

• Streamline daily workflows to allow agents more time for meaningful customer interactions.

• Gather continuous feedback from agents to identify opportunities for improvement.

• Offer professional development opportunities that help agents effectively adopt and leverage AI.

By implementing these strategies, organizations can empower agents to see the value of AI tools and maximize their use in their daily tasks.

8 key benefits of AI-powered super agents

What advantages can an AI-powered contact center team bring to your brand? 

AI offers a powerful array of benefits, from increasing productivity and cutting costs to improving satisfaction for both customers and agents. These make AI a worthwhile investment.

1. Better agent productivity

AI promotes agent productivity in several ways. By automatically managing routine issues, AI reduces the workload on support teams. For tickets that need human input, AI simplifies information retrieval, helping agents save valuable time. 

An integrated AI platform provides a fully customizable, omnichannel contact center that allows agents to manage multiple communication channels—like chat, email, SMS, voice, and text—from a single interface. This minimizes time spent switching between systems and looking up customer data, reducing the need for call transfers. Additionally, AI tools can efficiently retrieve answers from knowledge bases, sparing agents from having to consult with colleagues.

2. Faster resolution times

Conversational AI tools can handle routine inquiries, allowing agents to focus their time on more complex interactions. This leads to faster resolution times, significantly reducing average handling time (AHT). 

For example, technology consultancy Stratosphere Networks reports that AI-powered customer service can cut average handling time by 40%. And in a case study reported on by LevelAI, a B2B tech provider reduced AHT by 50% while boosting customer satisfaction.

3. More interactions per agent

Improved productivity and faster resolutions allow contact center agents to handle more interactions per hour. With AI managing initial requests and automating follow-up tasks, agents can efficiently manage more inquiries in less time. This increases overall contact center capacity, resulting in a higher return on investment per agent.

4. Lower labor and training costs

By increasing efficiency and streamlining training, AI helps organizations reduce costs. When AI takes on routine tasks, fewer agents are needed to manage high call volumes, resulting in lower payroll expenses. Additionally, AI-driven assistance provides real-time guidance, speeding up the onboarding process and helping new agents get up to speed faster.

5. Enhanced customer experience

By increasing agent efficiency and enabling faster, more personalized responses, AI boosts customer satisfaction scores. It elevates the overall customer experience by shortening wait times through automation. 

AI can begin handling inquiries right away, leading to lower first response times. Also, AI equips agents with contextual information and real-time recommendations, which improve first contact resolution rates. This means fewer repeat calls, making customers more likely to report positive experiences and remain loyal to the brand.

6. Personalized engagement

AI enables agents to offer more personalized interactions. By automating routine tasks and powering self-service tools, AI frees up agents to focus on complex issues that require human intervention. 

AI also provides a full 360-degree view of customer data, improving agents' ability to deliver tailored support that efficiently addresses customer issues. Instead of reacting to customer frustration, agents can anticipate why customers are reaching out and be ready with solutions, in turn creating more satisfying experiences for customers.

7. Increased revenue generation

AI tools help customer service teams drive revenue growth. AI analytics enable contact center agents to identify upsell and cross-sell opportunities and offer personalized recommendations. AI can also support outbound sales efforts by highlighting sales opportunities, freeing up agents to focus on outbound calls.

Additionally, higher customer satisfaction and retention driven by AI lead to increased brand loyalty, repeat business, improved customer lifetime value, higher Net Promoter Scores, and greater referral revenue.

8. Improved agent satisfaction and retention

AI increases productivity and reduces costs by improving agent satisfaction and retention. By taking over mundane, repetitive tasks and minimizing customer complaints, AI reduces stress on agents and helps prevent burnout. 

This shift allows agents to focus on more engaging, meaningful work, boosting motivation and morale. When burnout rates are low, companies can more effectively reduce turnover, lower recruitment and training expenses, maintain consistent productivity, and close gaps in skills and experience.

Providing customer care anywhere

Technological enhancements have unlocked new possibilities, driving customer-centricity by meeting customers wherever they are. Mobile technology enables customer support teams to assist not only from traditional contact centers but through mobile engagement in stores or on the field. Integration via open APIs allows smartphones to become powerful tools, accessing customer data and essential communication resources. This ensures agents remain connected and efficient, no matter their location.

For customers, mobile support means convenient access to representatives, like financial advisors, without waiting in call center queues, fostering personalized relationships. Additionally, these advancements empower customer experience enhancements through omnichannel communication on preferred platforms like SMS and WhatsApp, ensuring support is as accessible and flexible as customers demand.

Build a team of AI super agents with Twilio

AI can transform your support team into AI super agents by empowering them to deliver superior customer care. By using AI-powered analytics and  virtual agents, your team can shift from a reactively playing catch-up to proactively anticipating customer needs and consistently exceeding expectations.

Twilio Flex's omnichannel engagement center now brings AI's transformative potential to your support team with tools like Agent Copilot, ConversationRelay, and Unified Profiles. 

• Agent Copilot uses AI to analyze customer interactions and provide valuable insights, helping agents better understand customer intent. 

• ConversationRelay uses voice AI to create personalized self-service options for customers. It enables dynamic conversational experiences by integrating real-time speech recognition and synthesis into your applications.  

• Unified Profiles delivers a complete 360-degree view of each customer, consolidating real-time activity across channels, mobile and web platforms, CRM systems, and warehouse data. It offers seamless first-party identity resolution without needing a separate Segment account. 

This setup enables intelligent routing, minimizes transfer rates, allows virtual agents to handle routine inquiries, and delights customers with tailored support.

Ready to explore how AI can transform your agents into super agents? Connect with our sales team to learn how Twilio Flex can help you harness the power of AI-driven customer service.