AI Appreciation Day: Eagle Eye execs discuss personalisation, retail and loyalty
In the retail and loyalty sector, Artificial Intelligence (AI) promises significant changes to personalisation and customer value creation. However, this transformation raises important questions around ethical data use, integration challenges, misconceptions about AI capabilities, and the practical realities of implementation.
Executives at AI-powered personalisation and SaaS loyalty platform Eagle Eye have been navigating these changes firsthand, and have taken the timing of AI Appreciation Day to offer insights on both the opportunities and challenges ahead.
Common misconceptions about AI and retail personalisation
Jonathan Reeve, Vice President APAC at Eagle Eye believes there are significant misunderstandings about what AI can actually do for retailers.
Reeve points to a particular issue with how companies approach personalisation, noting that grouping customers based on broad data segments does not lead to effective customer experiences.
“Many retailers think they’re doing personalisation when they’re actually just doing sophisticated segmentation,” he says. “True personalisation means moving beyond grouping customers into segments and instead creating genuinely individual experiences, like tailoring specific reward thresholds based on each customer’s unique purchase history and preferences.”
Aaron Crowe, Regional Director Asia at Eagle Eye agrees. He approaches the misconception from a different angle, focusing on the relationship between AI and human workers rather than AI replacing them entirely.
“AI augments, not replaces, human expertise; speeding data analysis while preserving human judgment and local market insights,” he says.
Ethical considerations and data handling
When it comes to ethical issues, the executives share some common concerns but each brings a different perspective to the discussion.
Jean-Matthieu Schertze, Chief AI Officer at Eagle Eye, identifies three areas that businesses need to focus on to ensure responsible AI implementation.
“Bias and fairness: ensuring AI systems do not perpetuate or exacerbate social, cultural or economic biases,” he says. “Next is transparency and accountability: making AI decisions explainable and ensuring that there is clear accountability for outcomes driven by AI systems. Third is privacy and data protection: safeguarding personal and sensitive data from misuse, breaches or exploitation.”
Cédric Chéreau, Managing Director at Eagle AI, emphasises privacy as particularly relevant to their retail personalisation business.
“In our business (personalisation in retail) it is key to respect the choice of customers, making sure retailers collect the opt-ins and respect them. GDPR in Europe is the model to follow.”
He also highlights the social impact of AI acceleration, noting that workforce adaptation will be necessary.
“With AI acceleration, many employees will have to adapt,” he says. “They need training; they need to be eager to learn. They need to understand that AI will code better and faster than any developers in the world.”
So, how can retailers adopt ethical considerations into the way they manage customer data? Aaron Crowe offers practical steps that retailers can implement to ensure responsible data handling.
“Obtain explicit customer consent, anonymise or pseudonymise personal data, enforce role-based access controls and conduct regular privacy audits,” he says.
Similarly, Schertzer encourages retailers to adopt a sensible framework covering a few key areas.
“Grocery retailers can ensure ethical use of AI in customer data handling by limiting data usage strictly to what is necessary for improving customer experience and operational efficiency; ensuring robust data security measures are in place to protect customer information; and communicating openly with customers about how their data is being used,” he says.
Overcoming integration and fragmentation issues
The executives identify several significant obstacles that businesses face when trying to implement AI practically.
Jonathan Reeve highlights two particular disconnects that he believes will become more problematic as AI adoption increases. The first relates to how AI systems will discover and evaluate business offers.
“The biggest disconnect is between AI capability and discoverability,” he says. “Companies are building AI systems, but they’re not preparing for how AI agents will find and evaluate their offers. If your program’s benefits can’t be found and understood by an AI assistant, you’ll be excluded from consideration when customers ask where they can access certain benefits or products.”
He continues by explaining how traditional mass marketing approaches may become unsustainable in an AI-driven environment.
“Another major disconnect is between mass market thinking and AI optimisation,” he says. “Blanket promotions available to all customers become financially unsustainable when AI agents are built to identify and exploit the most generous public offers. This cherry-picking approach will render mass offers increasingly unprofitable. The solution requires rebuilding underlying technologies for an age where AI intermediaries might evaluate thousands of offers per second to find the best fit for their users.”
Aaron Crowe identifies more operational challenges that need to be addressed for successful AI adoption.
“Businesses need to overcome data silos, close talent gaps in AI/ML skills, and secure frontline buy-in through training and change-management to ensure AI adoption delivers value,” he says.
Zyed Jamoussi, Group Chief Technology Officer at Eagle Eye, emphasises the importance of moving past excitement to focus on practical business value.
“It’s about getting away from the hype, understanding what integrating AI into their operations means practically and making sure that whatever usage they are preparing is meaningful for the business and fits smoothly into business priorities,” he says.
Impact of agentic AI on customer experience
Jean-Matthieu Schertzer believes Agentic AI opens up a new way of interfacing systems.
“Agentic AI is about making systems easily accessible, not just to humans, not just to other systems through APIs, but to AI Agents with a degree of autonomy to interact with the system,” he says. “This represents a new paradigm for both system-to-system and human-to-system communication.”
Cédric Chéreau sees the potential for completely new customer experiences that go far beyond current personalisation efforts.
“AI is just getting started,” he says. “Real one-to-one offers, using shopper individual behaviors, personal potential, delivered at the right moment with the adapted image through the preferred channel will completely change the way customers interact with retailers.”
He also places AI in historical context alongside other transformative technologies.
“Like steam engines, electricity, or the internet, AI is a real revolution,” he says. “We need to celebrate it as a massive innovation that will change our environment.”
Opportunities for Australian retailers
Reeve sees particular potential for Australian retailers to benefit from global learnings without having to repeat the experimental phase.
“The most exciting opportunity is that Australian retailers can learn from global successes and implement proven strategies quickly,” he says. “The technology exists to deliver personalised experiences at scale, with implementation possible in weeks rather than months.”
He notes that Australia has good foundations but faces a particular challenge around digital engagement.
“Australia has the right ingredients: an established digital consumer base and significant opportunity for growth that could accelerate with increased personalisation,” he says.
“However, the key challenge is digital engagement. Most retailers only connect with a small fraction of their customer base through apps and websites. If only one in 20 customers are on the app, most customers miss out on the benefits of personalised reward programs.”
Why AI Appreciation Day matters
Crowe sees the day as serving multiple educational and developmental purposes.
“AI Appreciation Day is important for reflection, showcasing real-world value, sparking future development conversations, and promoting education among experts and customers around innovation,” he says.
When considering the broader implications of AI’s rapid development, Reeve reflects on both personal and professional transformation.
“I’ve been thinking about AI advancement a lot lately as we watch AI and automation start to reshape our working lives,” he says.
“Like many others, I’ve invested years developing particular skills and expertise. It’s not easy to imagine large parts of my work being automated, but I recognise I need to start asking: What problem do I solve for people? Could that problem be solved differently? And how might I evolve to stay relevant and valuable? It’s challenging, but it also gives us a chance to step back, reimagine, and maybe evolve to improve our prospects.”
On the question of why AI Appreciation Day matters, Reeve casts his mind back to retail and notes the importance of tracking AI progress, especially as it has already moved from experimental to practical application for some retailers.
“For the first time, retailers can start measuring real returns on AI investments rather than just talking about potential. We’re seeing early adopters like Tesco and Carrefour overseas already achieving measurable results from predictive AI in personalised marketing. Celebrating this acknowledges the transformation that’s already happening while pointing out the leaders who are lighting the way.”
