Improving Your Self-Service Options Through Topic Analysis Insights

John Ortiz at MiaRec shows you how you can use Generative AI-powered Topic Analysis to uncover opportunities to improve existing self-service tools and even identify gaps that could be filled with new self-service options.

Did you know that 62% of millennials and 75% of Gen-Z customers almost always prefer self-service to contacting customer support?

But that doesn’t mean your contact centre can’t assist them in their customer journey. On the contrary! Using Voice of Customer (VoC) insights gleaned from your call recordings delivers valuable data to create the best self-service experience for them.

Why Use Your Contact Centre Insights to Inform Your Self-Service Tool Strategy

Let’s face it: modern contact centres are an endless fountain of data. To put it into perspective, if your contact centre has 100 agents taking calls for 2,000 minutes per month, they produce 384 GB of data per month.

Hidden within that data are valuable insights that tell you where your customers or buyers are confused or frustrated, where they need help, or which problems they prefer to solve independently.

It can also help you identify topics on which they always prefer to contact a human support agent rather than use a self-service tool.

For example, as you can see from the screenshot below, most customers call this contact centre to inquire about a price, place an order, or make payments. These insights are like gold dust for your self-service strategy.

Based on the data, we know we should create self-service options for:

• Pricing Inquiries: We can empower our customers by creating a pricing calculator that allows buyers to create customized pricing quotes. In addition, we should carefully audit the pricing page to clarify any sections that might be confusing.
• Order Placement: The second most common call topic is “Order placement,” which tells us we should create a system that allows customers to order through our website.
• Payment Made: Another popular call topic that presents a self-service option is “Payment Made”. Perhaps we should create somewhere within our website or customer portal that allows for making payments.

Remember, the primary goal here isn’t just to reduce call volume (although that’s a nice bonus). It’s about empowering your customers to solve their problems quickly and easily, using the medium they prefer.

Happy customers mean repeat business and positive word-of-mouth, which is how you contribute to the bottom line.

Using Gen AI-Based Topic Analysis to Identify Opportunities for New Self-Service Tools

Generative AI-powered Topic Analysis can analyze 100% of your calls using its contextual understanding and ability to discern conversation nuances to identify the primary and secondary topics the customer is calling about.

For example, this could be a problem with an order, a refund request, a pricing inquiry, a booking cancellation, and so much more.

By looking at your Topic Analysis dashboards and/or reporting, you can identify which topics your customers are calling about most.

If you have AI-based sentiment analysis, you can overlay this data to gain detailed insights into your customers’ struggles. For example:

• Are they confused by your pricing?
• Do they not understand a specific process?
• Are they frustrated about appointment scheduling?

Depending on your business need and industry, you can interpret that data to identify the need for new self-service tools. Let’s take a closer look at three self-service tool examples and what data could prompt you to create the tool.

You should create a pricing calculator if:

• You frequently handle or see a spike in customers calling to ask about pricing details or clarification on pricing,
• Customers are confused by your pricing structure or frustrated because they don’t understand product packages or discounts, or
• You get a lot of demand for tailored price quotes, which indicates that there could be a demand for a custom quoting tool that creates instant, personalized quotes.

You should consider creating a self-service scheduling or appointment-booking tool if you get many calls from customers who:

• Request the scheduling, rescheduling, and cancelling of appointments,
• Complain about limited availability or scheduling options, or
• Ask where to find the appointment booking tool on the website.

Finally, consider creating a self-service product configurator if you get a lot of calls from customers who:

• Ask about the possibility of customizing products or services to meet their needs,
• Are confused about your product packaging or have difficulty navigating the available options, or
• Request custom product quotes.

Of course, this will look different for every industry and business, but the examples give you a good idea of what you can look for.

Using Gen AI-based Topic Analysis to Solve Customer Challenges Proactively

Generative AI-based Topic Analysis is extremely helpful in detecting customer behaviors or trends. This allows you to create self-service content that addresses potential issues before they escalate.

Suppose you notice a sudden change, such as a spike in inquiries about a new product feature. You can quickly create an FAQ or video series to address common questions.

For instance, if customers are struggling with setup, build a step-by-step “setup wizard” or “video tutorial.” This proactive approach not only reduces future call volumes but also demonstrates to your customers that you’re on top of their needs.

Using Gen AI-based Topic Analysis to Improve Existing Self-Service Tools

Topic Analysis can also show you where your current self-service tools have gaps. Maybe your chatbot is great at handling simple queries but struggles with more complex issues.

Maybe your pricing page is confusing buyers even more. Or perhaps your knowledge base is comprehensive but difficult to navigate.

Topic Analysis can be used to improve these tools over time. For example, you can:

1. Improve chatbot performance: Use AI to identify where your chatbot is not providing helpful solutions. Use VoC insights from your Topic Analysis to identify the problem and update its scripts to be more relevant or precise.
2. Fill knowledge gaps: Discover gaps in your knowledge base, documentation, or help articles by identifying areas where customers cannot find information online. Use these insights to update your knowledge base.
3. Enhance navigation: If customers are struggling to find information, use AI insights to reorganize your self-service portal for better user experience.
4. Personalize content: Tailor your self-service content for different customer segments based on their behavior and preferences.

By continually refining your self-service tools based on real customer interactions, you’re not just reducing call volumes – you are creating a better, more satisfying customer experience.

Wrapping Up: The Bottom Line Impact

As a strategic-minded contact centre manager, you’re always looking for ways to add value to your organization. By leveraging Generative AI-powered Topic Analysis to enhance your self-service tools, you’re doing just that.

You’re not just reducing call volumes and operational costs (although that’s certainly a plus). You’re creating a better customer experience, increasing customer satisfaction, and ultimately driving customer loyalty, which truly impacts the bottom line today.

This blog post has been re-published by kind permission of MiaRec – View the Original Article

For more information about MiaRec - visit the MiaRec Website

About MiaRec

MiaRec is a global provider of Conversation Intelligence and Auto QA solutions, helping contact centers save time and cost through AI-based automation and customer-driven business intelligence.

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Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: MiaRec