The Secret to Elevating Customer Experience with AI: Start with the Right Insights

When it comes to building a better customer experience, AI is not just about quick responses or automating repetitive tasks (although it's good at that too). The real power of AI lies in unlocking the insights from every customer interaction, using them to create a seamless, proactive, and delightful customer journey. From onboarding to account management to ongoing support, AI can transform how you engage with customers—but only when you begin with the right foundation.

In this edition of Actionable AI Insights, we’ll explore the step-by-step process to use AI as a tool for extracting actionable insights, enhancing the customer experience, and positioning customer support as a strategic asset.

1. Start with the End in Mind: Define Customer Experience Goals

To make AI impactful, begin by defining what an improved customer experience looks like. Your goal shouldn’t be to “handle more tickets” but to create a process that reduces the need for support, increases satisfaction, and makes interactions seamless.

• Think Beyond Automation: Instead of asking “How can we use AI to answer more queries?” Consider, “How can we use AI to create a better experience where customers need less help in the first place?”
• Example Goal: “Decrease the volume of repetitive questions by 20% in six months through improved onboarding and proactive issue resolution.”

Starting with specific goals creates a clear vision that AI can support and provides metrics to gauge success.

2. Capture and Categorise Customer Needs

Your support interactions hold the answers to improving the customer experience—but only if you know how to capture and analyse them. Many organisations have data that’s messy, incomplete, or spread across different systems, making it hard to draw out the insights needed to inform meaningful changes. This is where AI comes in, offering two paths for making sense of customer needs:

• Option 1: Analyse Existing Data: Use your current ticket data to identify key contact reasons and patterns. Even if the data isn’t perfect, it can reveal helpful trends, such as frequently asked questions, repetitive requests, or common complaints. This basic analysis gives you a clearer picture of what your customers need most often.
• Option 2: Use AI to Go Deeper: AI tools can go through each ticket individually, pulling quantitative and qualitative insights. By tagging themes, tracking sentiment, and identifying pain points, AI turns raw data into an actionable format, highlighting the areas where changes will have the biggest impact. If your data needs attention, Erictron AI can help with mining these insights and shaping a strategy that addresses the core issues affecting customer experience.

Example: You are limited by the categories in your shared inbox or service-desk tool. Use AI to build a deeper picture that uncover those ticket types that had the most negative sentiment to help you focus on where the customer is the most frustrated.

3. Measure What Matters: Speed, Resolution, and Satisfaction

Once you know what customers are asking, the next step is to understand how effectively these issues are being handled. Three metrics—resolution speed, query efficiency, and satisfaction scores—give a well-rounded view of the support experience and help pinpoint areas for improvement.

Key Metrics:

• Resolution Speed: Track how long it takes to resolve each type of query.
• Interactions per Resolution: Monitor how many touchpoints each query requires; fewer touchpoints typically indicate a smoother experience.
• Customer Satisfaction (CSAT): After each interaction, ask customers to rate their experience. AI tools can perform sentiment analysis on feedback, helping you detect trends.

Example: If satisfaction ratings are lower for product support inquiries, explore using AI to provide agents with instant reference material for commonly asked product questions, reducing the time and frustration in these interactions. Work with your product or customer marketing team to understand and manage the root-cause in parralel.

4. Create Cross-Functional Feedback Loops

A feedback loop can be transformative. By sharing insights across teams, you’re not only improving customer experience but also building a more resilient, customer-centric culture. When done effectively, these loops turn customer support insights into actionable improvements for product, marketing, and beyond.

AI plays a crucial role here by enabling teams to act on insights they may not have the time or expertise to manage independently. AI can identify recurring issues and suggest root causes, empowering teams to resolve them proactively. When these insights are shared across departments, they create alignment, drive improvements, and reinforce a culture where every team is invested in the customer experience.

Steps to Build an Effective Feedback Loop:

• Identify Top Pain Points: Regularly review support insights to highlight high-impact areas for each department.
• Share and Act: Create a rhythm for sharing these insights, whether through monthly reviews, cross-functional meetings, or dashboards, and empower teams to implement solutions.
• Follow Up: Track the impact of changes on customer satisfaction and support volume, feeding these results back into the loop to create continuous improvement.

Example: Your team identifies (with the new data being monitored) that new customers frequently ask for help with a part of the onboarding process. Review the customer journey, improving or adding messaging that helps improve education around this aspect, as well as create materials for agents to use for faster resolutions. While AI can help accelerate this in various ways from copywriting to strategising to helping you dig deeper into the data, it's not a silver bullet.

5. Implement Quick-Win AI Tools That Support Your Team

You don’t need to dive into complex AI projects to see an impact. There are several ways to use AI in low-risk, high-reward applications that empower your team and streamline processes.

Quick-Win AI Applications:

• Agent Support Bots: Give agents access to AI-driven responses for quick answers to common questions, reducing their workload and response time.
• Enhanced FAQs: Use AI to analyse past queries and update your FAQ resources with the most relevant information for customers. Go beyond just making the information available, use AI to help write it for the appropriate reading level, and give feedback on its usefulness.
• Agent Training Simulations: AI can simulate challenging customer interactions, allowing agents to practice in a safe environment and improve their response to difficult questions.

Quick-Win Tip: Start by implementing AI for one or two frequently asked questions. Observe the impact, and use this data to inform larger AI projects as you gain confidence in the tool’s effectiveness.

6. Ready for Direct AI-Driven Customer Interactions? Start Small and Scale

If you’re ready to let AI handle direct customer interactions, approach it incrementally. Identify low-risk interactions, measure their success, and expand as you learn.

Steps for Success:

• Choose Simple Queries: Automate straightforward inquiries like “Where’s my order?” or “How do I reset my password?” These don’t require nuance and allow customers to receive fast responses.
• Always Offer a Human Option: Make it easy for customers to reach a human if their issue is complex. This builds trust and ensures customers feel valued, even when interacting with AI.
• Monitor and Adjust: Track metrics like handoff rates and customer satisfaction with AI-handled interactions. Use these insights to refine AI’s role and effectiveness over time.

By starting small, you maintain quality and control while gradually building AI into your support model.

Limitations of AI: Recognising Where Human Touch is Essential

AI isn’t a silver bullet. While it’s a powerful tool, there are limitations to consider. Here’s how to use AI effectively while ensuring a seamless experience:

• Expect Mistakes in Complex Scenarios: AI may misinterpret ambiguous queries or give overly broad responses. Monitor these areas and adjust as needed.
• Data Privacy and Compliance: For sectors handling sensitive data, ensure AI adheres to strict data governance policies, particularly with customer interactions.
• Hybrid Responses for Sensitive Issues: In regulated industries, consider having AI draft responses that human agents review before sending, especially for high-stakes queries.

By recognising these limitations, you ensure AI remains an enhancement rather than a liability.

The Road Ahead: The Future of AI-Enhanced Customer Experience

As AI advances, some of today’s limitations will diminish, opening new possibilities for customer experience. Here’s what’s on the horizon:

• Improved Accuracy and Nuance: AI will become better at handling complex inquiries, providing reliable responses without constant oversight.
• Real-Time Voice AI: Voice interaction capabilities will soon reach a level that can rival human agents in responsiveness, offering a cost-effective way to handle high-call volumes.
• Seamless Data Retrieval: AI’s ability to pull relevant information on-demand will improve, reducing reliance on manual lookups and allowing faster responses.
• Scalable, Affordable Solutions: AI-driven live chat and voice options will become accessible for companies of all sizes, enhancing support quality and reducing costs.

By staying adaptable and taking incremental steps, your organisation can leverage AI advancements to continually improve customer experience.

The Bottom Line: Start Today, Think Long-Term

The ultimate goal of AI in customer experience isn’t just efficiency—it’s building stronger, more positive relationships with your customers. By setting clear goals, capturing insights, and implementing AI thoughtfully, you lay the foundation for a responsive, proactive customer experience that benefits both customers and your business.

Prompt for the Reader:

Talk to your customer service team and ask “what is the single most time consuming or common question we get?” Can it be deflected? What’s the root cause (Use AI to walk you through the ‘5 whys’)? The likelihood is that it’s a different team that needs to help resolve the issue.

Top AI News This Week:

1. Anthropic Releases New Model Update and Computer Use Tool: While it's early days for 'AI Agents,' leading AI lab Anthropic's new computer use tool is a great demonstration of what allowing a computer to use AI can enable. Forget the complex integrations, at some point, an AI agent will be able to use a computer (or 1000s of computers) the same way a human can, with all the same software and access to the internet. (Both Google and OpenAI are rumoured to be working on similar products)
2. Ideogram.AI releases new canvas feature: The new feature adds new capabilities allowing users to upload and edit images with AI. It's hard to explain in words, so check out the demo here !
3. AI Policy & Empowering Innovation: I wrote a short post here on the importance of an AI policy, and using it to empower your team, rather than just restrict them.

About Erictron AI

At Erictron AI, we understand the complexities of customer operations firsthand. Having led customer experience teams across several industries, I saw the challenges that come with delivering consistent, high-quality service. One of the reasons I ventured into AI was because I recognised its potential to solve some of these core challenges—to not just support teams but to transform the way businesses understand and respond to their customers.

We don’t see AI as a one-size-fits-all solution; instead, we approach it as a powerful tool to help you reach your specific goals. Our mission is to enable you to turn data into insights and insights into action, driving a customer experience that’s both impactful and sustainable. Whether you’re looking to save time, increase revenue, or create a more resilient business, our tailored approach ensures AI supports your unique objectives.

Interested in discussing how AI can drive real results for your business? Reach out for a free consultation to talk about how data and AI can support a better experience for your customers.