1. AI-powered personalisation in physical retail
As digital and physical retail converge, AI is playing a central role in transforming in-store experiences to rival the personalisation of e-commerce. Retailers are increasingly deploying sensors, cameras, and mobile apps to collect real-time behavioural data, which AI then analyses to tailor promotions, product recommendations, and even store layouts. Smart shelves may suggest complementary items, digital mirrors could display personalised outfit combinations, and AI-powered kiosks can guide shoppers based on their preferences and purchase history. This level of contextual engagement turns the brick-and-mortar store into a dynamic, intelligent environment that feels uniquely tailored to each shopper.
2. AI-driven decision support for store managers
Flooid is investing in AI to support store managers with real-time, data-informed decision-making tools. These systems will enable managers to interact with analytics and reports through natural language, allowing them to quickly understand operational trends without needing to interpret AI will suggest optimised actions for staffing, stock management, and scheduling by analysing historical sales data in combination with external variables like weather or local events. This shift from passive reporting to proactive, AI-guided management empowers leaders to respond faster and make smarter, more strategic decisions at the store level.
3. A natural language and no-code development tools
A bold vision outlined in Flooid’s roadmap is the use of AI to radically simplify how retailers customise their tech stack. Product managers and retail teams will soon be able to describe desired features in natural language and receive working, interactive mock-ups generated on the fly. Through conversational iteration, these mock-ups evolve into ready-to-integrate micro frontends, without traditional coding. This no-code approach streamlines the development lifecycle, accelerates time to market, and democratises innovation across teams. It’s a transformative shift that positions AI not just as a tool for analytics, but as a creative partner in building retail experiences.
4. AI for real-time loss prevention and fraud detection
Loss prevention is getting smarter and more proactive, thanks to AI-powered monitoring at the point of sale. Flooid’s system observes transactions across all store devices in real time, identifying potentially fraudulent behaviour using dynamic rule engines and behavioural pattern recognition. For example, if a self-checkout scan occurs without the customer ever being detected near the corresponding product aisle, via cameras or Bluetooth beacons, an alert can be triggered instantly. This level of AI-enabled surveillance doesn’t just prevent losses; it also enhances overall store security, reduces false positives, and helps retailers adapt to evolving fraud tactics with precision and speed.
5. AI-enhanced associate training and performance coaching
In the next decade, AI will redefine how retail associates are trained, supported, and developed on the job. Flooid is leveraging behavioural data from POS systems to personalise training paths, surfacing targeted coaching based on how employees interact with customers and technology. Associates will gain real-time access to knowledge bases through natural language queries, while store managers will receive AI-generated insights into employee performance and growth opportunities. This approach transforms training from a static, one-size-fits-all experience into a dynamic, responsive system that nurtures talent, improves service quality, and builds a stronger, more capable frontline workforce.
Flooid works with the largest retailers in the world. If you want to learn more about the capabilities of Flooid, contact us.
Flooid travaille avec les plus grands détaillants du monde. Si vous souhaitez en savoir plus sur les capacités de Flooid, contactez-nous.
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