Research & Publications
The Bayfield Retail QuiltTM is a data visualisation approach to retail property portfolios and shopping centres.
Retail Quilts communicate relative size of occupancy and tenant mix within a retail portfolio. The retail portfolio may comprise all the units within a shopping mall, shops on a single high street or even non-adjacent and geographically diverse retail portfolios.
The quilt benefits visual appreciation of the tenant mix by spatial representation of the retail units uncomplicated by the highly heterogeneous geometric features such as design, position, communal and other ancillary areas. Consequently, the quilt allows a visual analysis of tenant mix speeded up to around two minutes reduced from around thirty minutes when looking at architectural drawings or unit layout.
A sample study publication will review the method using twenty shopping centres over ten UK cities. The tenant mix of each shopping centre will be observed in relation to their regional economic climate, local demographics as well as their relationship to one another.
This sample publication aims to get across the speed with which an understanding of retail property portfolios can be appreciated using the Retail Quilt. The sample publication will be available on the 2nd of December. Request a sample.
A full publication due for launch in May 2017 will demonstrate how this method can include other dimensions such as sales and footfall. The publication will also demonstrate fragmentation and clustering analysis and how the geometric features, removed from the unit layout plans, contribute to value both independently and in combination with other factors. The full publication will include over 200 shopping centres in total drawn from all major cities in the UK.
Full publication available soon. Price £695+VAT
This and other data visualisation methods are demonstrated on our Introduction to Shopping Centre Investment course and used comprehensively on our Retail Property Appraisals course to help retail property investors quickly predict and benchmark value.
Media or Press enquiries please contact Sonia Martin-Gutierrez +44 (0)1223 517851