Why Most Personalisation Feels Robotic— and How to Fix It

AI has made personalisation easier but not better. Explore why most efforts still feel robotic, and what it really takes to connect with customers in a way that feels human.

In the race to personalise, many brands have lost the plot. The goal isn’t to appear personal, it’s to be personal. For many customers, the reality of personalisation often feels like a broken record: Predictable. Robotic. Forgettable. It’s a default loop.

The approach to the now possible AI-driven strategy has honestly become predictable, robotic, and ultimately forgettable. Despite powerful AI capabilities at their fingertips, many brands are still stuck in an outdated mindset. 

Dennis Wakabayashi, Global Voice of CX, rightly says, “Personalisation should feel human, not robotic.” In pursuing seamless and personalised interactions, companies often flood customers with too many touchpoints, unnecessary follow-ups, and constant notifications. 

This leads to what Dennis calls CX Fatigue where customers disengage, ignore outreach, or even develop negative perceptions of the brand. The solution is not more engagement, but more meaningful engagement.

Five Signs Your Personalisation Strategy Isn’t Working

• Open rates are falling despite more emails
  
• Customers are opting out of communications
  
• Recommendations feel irrelevant
  
• Repeat purchases are declining
  
• NPS is flat or declining

The Fundamental Misunderstanding

This robotic cycle of personalisation reveals a deeper issue: many brands misunderstand what personalisation truly means considering the AI-enabled world we live in. Muss Haq, Head of Customer Experience and Insight at RU CX, highlights this common trap: “Many businesses mistakenly believe that AI tools like chatbots and recommendation engines will automatically enhance experiences, which is far from the truth.”

Basic personalisation reduces customer experience to isolated interactions without building deeper connections or considering the customer’s long-term journey. As Muss explains, this transactional mindset, “it “misses the opportunity to leverage data and insights to anticipate needs, build emotional loyalty, and create significant experiences.”

When companies treat CX as isolated moments rather than an ongoing relational journey, they severely limit AI’s value and the true potential of personalisation.

Why This Matters: Data-Backed Evidence

A recent report by Apply Digital highlights that retailers who leverage AI-driven personalisation see a 15% increase in customer engagement and a 20% boost in conversion rates compared to those using traditional methods. This demonstrates that when done right, AI-powered personalisation drives tangible business results without alienating customers.

How to Make It Work: 5 Principles of Meaningful AI-Driven Personalisation

To break free from generic, robotic personalisation, brands should embrace these strategic principles:

1. Prioritise Meaningful Engagement Over Volume
   Focus on quality, not quantity. Avoid overwhelming customers with excessive touchpoints or notifications that lead to CX Fatigue.
   
2. Leverage AI to Anticipate, Not Just React
   Use AI to predict future customer needs and preferences, delivering proactive, relevant experiences rather than reactive, transaction-based offers.
   
3. Integrate Personalisation Across the Entire Customer Journey
   Design personalisation as a continuous, relational experience—not just a series of disconnected interactions.
   
4. Blend Automation with Human Empathy
   Use AI to empower employees and support human connections, not replace them. Human insight remains essential to creating emotional loyalty.

“Balancing automation and personalisation is key to supporting our clients effectively and efficiently. The foundation to doing this successfully is understanding the client’s goals, operations, and communication styles. We work both with our proprietary tech and Customer Success tools such as Gainsight, which allows our teams across all levels of the business to obtain a 360 view of our customer base at the click of a button,” says Clara De Rosa, Head of Customer Success at Adform.

1. Use Data Responsibly to Build Trust
   Apply customer data thoughtfully to enhance products and services, respecting privacy and avoiding overuse that leads to distrust.

“Rather than using personalisation for everything, brands can profit from a lighter touch. By taking steps to ensure that data is only used to refine products, enhance services, and create positive customer experiences, they can win the customer’s trust,” says Benjamin Fine, Co-Founder and CEO of Formsort.

Consider Netflix. It moves beyond simple “because you watched this” suggestions by leveraging AI to analyse viewing habits, time of day, and even device type, combined with creative curation teams who craft personalised thumbnails and recommendations. This blend of data and human insight helps Netflix deliver a personal experience that feels intuitive and engaging rather than robotic—building deeper emotional connections with viewers.

Starbucks also uses AI-driven insights from its loyalty app to tailor offers not just based on past purchases, but also on location, weather, and time of day. By combining data with real-time context, Starbucks creates a warm, timely experience that feels thoughtful and relevant, turning simple transactions into meaningful moments of connection.

Ultimately, AI-driven personalisation isn’t broken, it’s simply being misused. The opportunity isn’t in sending more messages or tracking every click; it’s in creating relevance that feels intuitive, respectful, and human.

Sarah Hackett, SVP of Growth at Apply Digital, said: “Today’s consumers expect engaging experiences, but personalisation isn’t just about engagement. One to one experiences drive revenue, repeat purchase, and long-term growth. That’s why the retail brands that combine AI with empathy and trust won’t just meet customer expectations – they’ll define them.”

Brands that succeed will be those who shift from chasing transactions to building relationships where every interaction is less about the algorithm and more about the individual. It requires restraint, context, and the humility to know that just because we can personalise something, doesn’t mean we should.

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