Introduction

In a world where digital transformation is no longer optional, understanding how artificial intelligence (AI) can enhance customer satisfaction is critical. This blog post is inspired by the master’s thesis of Jolien Devliegher and Ine Keuller, graduates of Ghent University, who explored the impact of AI tools on customer centricity in a B2C context.

Their research, titled “De impact van artificiële intelligentie op customer centricity: De klanttevredenheid in een B2C-context”, provides valuable insights into how consumers perceive and interact with AI-driven tools like chatbots, personalized recommendations, and autocomplete functions. You can access the full thesis here 

Why This Research Matters

Customer centricity is more than a buzzword—it’s a strategic imperative. As AI becomes more embedded in digital experiences, understanding how it affects customer satisfaction is essential for:

• E-commerce leaders aiming to improve conversion and loyalty
• Marketing teams designing personalized journeys
• CX strategists seeking scalable, human-like interactions

This study bridges the gap between theory and practice by analyzing how real consumers in Belgium perceive the usefulness and ease of use of AI tools—and how that perception influences their satisfaction.

Key Findings: What Drives Customer Satisfaction with AI Tools

The research used the Technology Acceptance Model (TAM) to explore two main questions:

1. What factors influence the perceived usefulness of AI tools?
2. How do perceived usefulness and ease of use affect customer satisfaction?

🔍 1. Trust Is the Foundation

Consumers who trust AI tools to deliver useful outcomes are significantly more likely to find them valuable. This is especially true for autocomplete features, which scored highest in both trust and perceived usefulness.

Takeaway: Build trust through transparency, reliability, and clear value communication.

🔍 2. Simplicity Wins

Autocomplete tools were rated the easiest to use and most helpful. Chatbots, while promising, were seen as less intuitive—especially for complex tasks.

Takeaway: Prioritize intuitive design and user-friendly interfaces. Start with simple use cases.

🔍 3. Ethics and Privacy Matter

Consumers who are more concerned about data privacy tend to rate AI tools as less useful—especially recommendation engines.

Takeaway: Address ethical concerns proactively. Communicate how data is used and protected.

🔍 4. Demographics Influence Perception

• Younger users trust AI tools more than older users.
• Men show more interest in technology than women.
• Non-working individuals surprisingly found recommendation tools easier to use than working professionals.

Takeaway: Segment your audience and tailor onboarding and messaging accordingly.

From Insight to Action: How to Build Customer-Centric AI Experiences

Here are four practical strategies to apply these insights:

✅ 1. Start with High-Impact, Low-Complexity Tools

Autocomplete features are a great entry point. They’re easy to implement and deliver immediate value.

✅ 2. Invest in Education and Onboarding

Don’t assume users will “just get it.” Provide tooltips, demos, and support to guide users—especially older demographics.

✅ 3. Make Ethics a Competitive Advantage

Use privacy as a selling point. Highlight your compliance with GDPR and explain how AI decisions are made.

✅ 4. Measure What Matters

Track not just usage, but perceived usefulness and ease of use. These are leading indicators of satisfaction and loyalty.

Conclusion: AI Is a Tool—Customer Centricity Is the Goal

This research confirms what many forward-thinking leaders already suspect: AI can enhance customer satisfaction—but only when it’s trusted, easy to use, and aligned with customer needs.

As you build or refine your AI strategy, remember: the goal isn’t just automation—it’s human-centered innovation.