Retail is a dynamic industry, where even successful companies must consistently optimise their operations to maintain profitability and adapt to changing market conditions. Every year, retail executives, including Real Estate Directors, face the daunting task of reviewing non-performing stores. While closing a store is a last resort, it’s an expensive and high-stakes decision that requires evaluating multiple factors—operational challenges, data inaccuracies, and the human impact of potential job losses.
In this case study, we explore how a retail business employed a Location Analysis App powered by AI to streamline this decision-making process, minimise stress, and unlock actionable insights for better strategic planning.
The AI Model
The AI-powered model built into the Location Analysis App transformed the way the Real Estate Director approached store reviews. Using existing footfall data from operational stores, the AI system learned patterns to predict commercial potential more accurately. It provided comprehensive assessments and actionable reports, making the review process less stressful and more efficient.
The AI provided an objective analysis of location potential, removing uncertainty from decision-making.
The annual review process, which previously involved hours of manual research, now took significantly less time.
The Rental Negotiation Report empowered the director to secure better lease terms for stores in areas with fluctuating foot traffic.
The AI flagged operational improvements that could be made to boost performance before considering closures.
How it Works?
Users can access real-time geographic and demographic data through an interactive map, offering insights into nearby foot traffic, population trends, and competitor density.
The retailer’s historical footfall and sales data trains the AI model, allowing it to generate predictive insights specific to the retailer’s unique conditions.
The platform offers short instructional videos on key features, including generating reports, adjusting parameters, and interpreting the data for actionable results.
Case Results
By using the Location Analysis App, the Real Estate Director was able to:
This tool allowed the executive team to feel more confident in their decisions and significantly reduced the stress of evaluating underperforming stores. As the AI model evolved, it became a valuable asset—almost like an additional team member—helping the leadership team make smarter, more proactive decisions.
Location Analysis Apps are transforming retail strategy by providing actionable insights. For Real Estate Directors, these apps reduce the risk of making costly mistakes and offer a structured way to optimise operations. The AI model doesn’t just evaluate a store’s current performance—it provides a roadmap for maximising the commercial potential of every location.
With tools like these, retailers can identify missed opportunities, negotiate smarter leases, and close stores only when necessary, ensuring they remain profitable and competitive in the long run.
