How AI is Shaping In-Mall Experiences

The Evolution of Retail & Imperative for AI Technologies

Shopping malls are evolving, and this whitepaper reveals how Artificial Intelligence (AI) and Machine Learning (ML) are the keys to a retail revolution. The document dives into how these technologies, especially advanced Large Language Models (LLMs), can transform traditional shopping into a dynamic, personalized journey for every customer.

Inside, you'll discover how AI can:

• Enhance customer interactions by providing hyper-personalized recommendations, guiding shoppers to specific products and stores, and even suggesting promotions based on their preferences or loyalty points.
• Provide actionable data insights that allow mall operators and retailers to understand shopper behavior, optimize operations, and create new revenue opportunities.
• Offer a flexible and accessible solution that works for everyone, from large shopping mall portfolios to smaller retail spaces, without requiring extensive digital infrastructure.
• Ensure robust data privacy by integrating with existing platforms to build on established consent frameworks and foster trust with shoppers.

This isn't just about technology; it's about fundamentally redefining the personalized shopping experience.

What the whitepaper covers

The paper looks at what changes when a shopping centre runs its own AI assistant, built on a large language model and the centre's loyalty data. It covers three areas: how shoppers find what they want, what operators learn from the questions shoppers ask, and how offers reach the right person.

Key takeaways

• Shoppers ask in plain language. A question like "Which stores have dresses on sale today, and can I use my points?" gets a direct answer: the stores, the offers and the points available to spend.
• Every question is a data point. If many shoppers ask about vegan food, sustainable brands or accessible toilets, that is demand the centre can act on through events, leasing or facilities.
• Loyalty data makes answers personal. The assistant can use a member's visits, purchases and points to suggest a relevant store or offer, instead of a generic directory result.
• You can start small. A QR code at the entrance gives a centre anonymised insight into its most common shopper questions before any CRM integration. Deeper tiers connect loyalty and CRM data through APIs.
• Control stays with the operator. Building on existing, consented loyalty data keeps responses, data use and brand voice in the centre's hands.

Three examples from the paper

The paper works through three illustrative scenarios. A shopper scans a QR code to find which store stocks football shirts and when it opens. A centre notices a rise in questions about sustainable fashion and runs a pop-up in response. A loyalty member asks for gift ideas and is pointed to an electronics offer they can pay for with points.

The answers get better with data from the sector itself. Coniq's covers 188 malls and outlets and 107 million shoppers.

Who it's for

Marketing, leasing and digital teams at shopping centres and outlets who are weighing up an AI assistant for shoppers, and anyone who wants to know what it takes to start.

Coniq's AI Concierge is built on this approach. See how the AI Concierge works or book a demo.