DELIVER Asia 2026 Conference Recordings

Retailers across the world are exploring artificial intelligence, but without reliable data foundations, AI cannot deliver meaningful results.

Speaking at DELIVER Asia 2026 in Singapore, Karen Chan, Chief Customer Officer at FairPrice Group, outlined how the organization is preparing its data infrastructure to enable scalable AI-powered retail experiences.

For FairPrice, the journey begins with one fundamental principle: without good data, there can be no good AI.

FairPrice Group operates one of Singapore’s most extensive retail ecosystems.

The organization spans grocery stores, convenience stores, pharmacies, food courts, and food service operations, alongside digital services including a partnership in Trust Bank. In total, the company interacts with customers through more than 500 touchpoints across the country.

Its loyalty programme, Link, includes 2.4 million members, many of whom engage through the FairPrice mobile application.

This scale generates enormous amounts of customer data — but historically, much of that data has been fragmented across different systems.

Like many long-established retailers, FairPrice has accumulated decades of data across multiple platforms.

With more than 50 years of operational history, the company found that its customer databases had grown far beyond the population of Singapore itself due to duplicated records and legacy data structures.

Different channels — including online platforms, in-store systems, and loyalty databases — often held separate customer records, making it difficult to generate accurate insights.

This fragmentation meant the company was data rich but insight poor.

To address this challenge, FairPrice began building what it calls a Golden Customer Profile — a unified view of each customer across all interactions.

The process started with data cleansing and deduplication. By applying deterministic business rules and probabilistic matching techniques, the company significantly reduced duplicate records and aligned customer profiles across systems.

The next step involved identity verification and integration with national digital identity infrastructure, enabling FairPrice to link loyalty accounts with verified demographic data.

This approach allows the retailer to build richer customer profiles that include household composition, shopping behaviour, and participation in government support programmes.

Even with a unified internal profile, retailers rarely see the full picture of a customer’s behaviour.

FairPrice therefore works with external partners to supplement its first-party data with aggregated third-party insights. These signals help the company understand broader lifestyle patterns, such as where customers shop outside its stores or how they allocate spending across food, dining, and other categories.

Combining internal and external signals allows the company to develop deeper insights into customer segments and purchasing behaviour.

With stronger data foundations in place, FairPrice can begin deploying more advanced AI-enabled capabilities.

These include real-time personalization in stores, targeted promotions based on purchasing history, and digital assistants that help customers navigate stores and discover relevant offers.

In experimental AI-enabled stores, customers can unlock shopping trolleys with the FairPrice mobile app, receive personalized product recommendations, and locate products through voice-enabled search features.

The goal is to create a connected omnichannel experience that seamlessly integrates digital and physical retail.

Despite its focus on technology, FairPrice emphasizes that AI is not intended to replace frontline retail workers.

Instead, the organization aims to use AI to improve employee productivity, provide real-time operational insights, and free staff to spend more time assisting customers.

The company is also investing heavily in training and upskilling employees to ensure that existing teams can confidently adopt new tools and technologies.

For FairPrice, the future of retail innovation lies in combining data-driven intelligence with human expertise.