Measuring Retail Success: Why Floorspace is a key data point?

Estimating the total retail floorspace across Great Britain has long been a complex challenge for stakeholders in the retail property sector. However, Green Street, following its acquisition of LDC’s granular POI dataset, has harnessed cutting-edge data science and analytical capabilities to model floorspace across 700,000 plus retail units across GB. This landmark development provides new opportunities for investors, occupiers, and public sector planners, offering deeper insights into retail provision and space utilisation.

Value proposition by segment

Investors – can gain a comprehensive understanding of retail provision surrounding assets and assess how they serve local catchments using retail floorspace per capita statistics. Additionally, Green Street’s floorspace data can be utilisied in underwriting, to estimate the sales productivity of an asset, using sales per square foot estimates. In addition, floorspace vacancy metrics will add context to physical vacancy rates, understanding average unit size of vacant space, as well as aligning more closely with REITs who report financial vacancy rates.

Occupiers – can support their tactical location planning strategies in local markets by using Green Street’s floorspace data to target specific unit sizes for upsizing or relocation opportunities in order to maximise sales densities. Understand competition levels and assess the impact of competitors based on their space usage rather than just the number of physical units.

Public Sector – can address the long-standing issue of retail oversupply in the UK. Green Street’s floorspace data helps identify locations with the largest challenge of retail space per capita but also to identify specific categories that are oversupplied within a catchment. Benchmarking similar locations using Green Street’s Health Index will help users determine the exact amount of space reduction needed to drive retail tension and support local regeneration.

Green Street’s floorspace model was developed using data from the Valuation Office Agency (VOA), matched with Green Street’s database via the Unique Property Reference Number (UPRN). This dataset was then enriched with Green Street’s proprietary metrics, including tenant information, business type, location, and tenant category and subcategory.

Data Accuracy: Average floorspace values were calculated for each metric using a hierarchical approach to ensure the most detailed and accurate averages. Strong outliers were excluded to enhance reliability. Vacant units were also evaulated based on their previous occupancy.

Regional Considerations: Areas with low data availability, such as Scotland and specific sectors like pubs, bars, and hotels, were modelled separately.

Retailer Comparison: The model distinguishes between multiple and independent retailers, ensuring that averages are calculated within comparable groups.

Validation: The final model was validated against VOA floorspace figures to ensure alignment within acceptable parameters. This process resulted in a robust dataset covering all GB retail floorspace, utilizing over 400,000 industry-recognised data points from the VOA combined with Green Street’s expert insights—the first dataset of its kind in the market.

Green Street’s Retail Analytics Pro unlocks new possibilities for investors, occupiers, and public sector stakeholders, supporting data-driven decisions that enhance retail performance and local regeneration. By combining advanced data science with extensive industry expertise, Green Street continues to set new standards for real estate insights, empowering stakeholders to make smarter, more informed decisions.

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Retail Analytics Pro