AI customer feedback analysis: A complete guide

Customers are the lifeblood of any business, and what they say, think, and feel about your brand should be a top priority. But understanding what they want is difficult—and it proves even more so when factoring in the amount of daily interactions and enquiries you may face. The good news is that you don’t need to be a mind reader to understand them—you just need artificial intelligence (AI).

AI customer feedback analysis can help businesses gather feedback effectively, understand it, and act on it faster—helping them to deliver a better customer experience (CX) and improve agent performance. Below, we highlight some key benefits, challenges, and strategies so you can build long-term customer loyalty and drive profitability.

More in this guide:

• Why AI customer feedback analysis is important
• Benefits of AI customer feedback analysis
• Challenges of using AI to collect customer feedback
• Ways to gather and interpret customer feedback with AI
• Frequently asked questions
• Improve your AI customer feedback analysis with Zendesk

Why AI customer feedback analysis is important

AI customer feedback analysis is important because it helps you provide an outstanding CX and delight your customers at scale.

If you have a small business or startup, manually collecting and monitoring customer feedback might not be too difficult. But as your operation grows, so does the number of customer interactions. Without AI, customer feedback can overwhelm your operation, leaving you consistently one step behind. Not only that, but you can’t predict customer needs and act on them quickly.

AI customer feedback analysis can help you cultivate an AI customer experience. This approach blends artificial intelligence, automation, and actionable data to provide personalised and proactive experiences. With it, you are always one step ahead of your customer base, ensuring you always meet their needs—whether you have 10 customers or 10,000.

Benefits of AI customer feedback analysis

AI customer feedback analysis can improve your organisation in several key areas. Here are a few of the most impactful.

Improves the customer experience

When harnessing AI for feedback, businesses can consistently identify trending customer needs, pain points, and preferences to improve their customer experience. For example, AI-powered QA tools can flag negative sentiment in real time and identify areas where support agents are underperforming.

AI customer feedback can also contribute to a wider Voice of the Customer program—helping businesses collect and analyse customer feedback about their brand, products, services, and customer experience. With it, teams can review conversations across every channel to ensure they are consistently meeting customer expectations.

Provides faster, more accurate insights

AI customer feedback analysis allows organisations to identify and respond to customer information quickly. Rather than manually sorting through customer surveys or reviewing support tickets, AI can deliver actionable insights in real time. This allows businesses to respond to trending customer feedback rapidly, helping to address short-term issues or lapses in service before they become bigger problems.

Review a larger volume of data

Manually reviewing customer feedback is inefficient, especially for large or growing businesses. AI customer feedback analysis can gather information from 100 per cent of your customer interactions across agents, bots, BPOs, and languages. This helps you get an instant, full-picture view of customer sentiment that isn’t possible by hand.

Improve customer loyalty and retention

AI customer feedback improves customer loyalty and retention by helping you understand their needs and deliver a better CX. For example, maybe you adopted a new software for support interactions, and consumers are finding it more difficult to connect with your support team. AI customer feedback can analyse support tickets and alert you to this trending sentiment so you can correct the issue before it turns into a bigger problem.

According to the Zendesk AI-Powered CX Trends Report 2024, 80 per cent of consumers expect chat agents and support representatives to assist them with everything they need. So, when you deliver on those expectations and stay one step ahead of customer needs, you’ll naturally create the type of CX that customers want to interact with long-term.

Challenges of using AI to collect customer feedback

While using AI to collect customer feedback can bring several benefits, you need to be mindful about how you interpret the data. When conducting AI customer feedback analysis, be aware of challenges related to:

• Data quality: You need access to high-quality data for accurate AI analysis. Ensure you can gather information from quality sources like customer satisfaction (CSAT) surveys, verified customer comments, and support tickets.
• Context: Not all AI models are alike—some may have difficulty interpreting context and nuance when analysing customer feedback. Look for AI partners with sophisticated intent identification who are trained in customer service interactions.
• Integrations: AI customer feedback analysis will be difficult to perform if it doesn’t mesh with the tools you use every day. Ensure all your technology can coexist to make the most of your systems.
• Data security: AI feedback analysis interacts with extensive customer and business data. Look for AI partners that comply with industry regulations and have the capabilities to keep your information safe.

Remember these challenges to ensure you get the most out of your AI feedback analysis efforts.

Ways to gather and interpret customer feedback with AI

Now that you know how to overcome common missteps when leveraging AI for customer feedback, let’s dive into how to gather it effectively. Here are four ways you can use AI to get customer feedback and use it to your advantage.

Automatically send surveys after interactions

A perfect time to collect feedback is directly after a customer support interaction—and you can facilitate that with artificial intelligence and workflow automation tools that can automatically send surveys after interactions to help you collect data and understand your customers. An example of this is Love, Bonito, a womenswear brand that uses Zendesk to automatically issue CSAT surveys to their customers and deliver exceptional service. By doing this, they can measure team performance and identify areas where they can improve the CX.

Equip agents with tools to help them understand and resolve feedback

Businesses can use agent-facing tools to help their support team understand customer feedback and respond to it faster. These resources can deliver insights into customer intent and what they need at that moment. For example, AI can summarise long tickets for agents so they can understand what the customer needs straight away.

Additionally, tools like agent copilots can help agents respond better to customer feedback by guiding them through interactions in real time. AI-powered copilots can suggest relevant responses tailored to the customer’s needs so agents can act more effectively on them. This also empowers them to navigate feedback without assistance from their manager.

Harness customer sentiment analysis

Customer sentiment analysis captures and assesses how consumers feel about your business and service experiences. This process harnesses AI to review customer feedback, comments, reviews, complaints, and more to help you understand how your buyers feel about their experience with your company.

From a customer service perspective, sentiment analysis can help support agents anticipate customer feelings to offer better service, power better workflows, and stay on top of customer trends. An example of this is Motel Rocks, an online fashion retailer that uses Zendesk Advanced AI to perform sentiment analysis and better understand customers. This resulted in a 9.44 percent increase in CSAT and a 50 percent ticket reduction.

Lean on AI QA tools to get ahead of churn

Quality assurance (QA) is an AI customer feedback method that can help evaluate all support interactions to improve the CX and spotlight churn risks, outliers, and escalations. For example, managers can use Zendesk QA capabilities to evaluate 100 per cent of support tickets. From there, they can assess customer feedback, pinpoint areas of improvement, and schedule training sessions to ensure support agents are operating at peak performance. Liberty knows the benefit of this firsthand; the luxury goods company uses Zendesk QA to evaluate customer interactions and achieve an 88 per cent CSAT.

Frequently asked questions

Improve your AI customer feedback analysis with Zendesk

AI customer feedback analysis can help you better understand your customers, boost agent performance, and continuously optimise your service operations. That said, you can’t just partner with any AI tool—you need the right one. Zendesk AI is trained on over 18 billion real customer service interactions and is purpose-built for CX. Whether you’re looking to automatically send customer surveys after interactions with Zendesk AI Agents, anticipate customer sentiment, or help support agents better understand and act on feedback with Agent copilot, Zendesk equips you to capture and respond to customer feedback more effectively. Not only that, but you can also use Zendesk QA to evaluate 100 percent of customer interactions and identify areas for improvement.

Learn more about how our AI capabilities can help you understand your customers.

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