Retail Tracker | Prime
our complimentary monthly view of performance for the largest and most dominant shopping centres in Australia.
Only 27 shopping centres with gross-lettable-area over 100,000 square metres qualify for inclusion in our Retail Tracker | Prime. These shopping centres dominate the Australian retail landscape, serving nearly 1 in 2 people from across the country over the course of a year. Tracking the performance of these retail destinations is therefore a valuable exercise to understand how Australians are interacting with physical retail. Providing valuable insights not only for the owners and investors of this asset class, but for the broader retail community.
We trust you find the Retail Tracker | Prime a valuable contribution to the property sector. If you would like deeper
insight on a portfolio, asset class or asset then please explore our product offering or contact us directly
to discuss how we can help.
The expected retail sales metric is created using a machine learning model that transforms unique customers, frequency of visit, dwell time, price, and consumption changes to produce an estimate of sales growth by
centre.
Customer interactions are presented as an average of the 27 shopping centres included in the report. These are the levers that asset teams have to work with to drive visits to their shopping centre for the tenants to convert. For the sake of clarity, customers are the unique people seen in a shopping centre at least once over the prior 12-month period. loculAI detects and removes staff working within the centre and any residents living overhead. Frequency of visit is the average number of times customers have visited a shopping centre over the prior 12-month period. Shopping trips are the total number of visits to the shopping centre over the prior 12-month period. A shopping trip could be for any purpose, including lifestyle and entertainment, medical or other. A customer can have a maximum of one visit per day. So if they leave and come back, they will be counted only once. This is a key differentiation from traditional beam or camera people-counting systems. Dwell minutes is the time between the first and last mobile signal detected from a customer. Finally, shopping hours is a composite metric of shopping trips and dwell time, a strong indicator of centre performance.
We profile lifestage using our loculCustomer model, which profiles each ASGS SA1 into 60 customer segments based
on lifestage, family structure, and income quintiles. We then use shopping trips originating from these ASGS SA1s to
construct a weighted profile to understand the customer types that are visiting a shopping centre. Context profiles are
built using mobile data signal patterns to understand where shopping trips originated. The day part analysis is based
on the time of the first mobile signal detected during a shopping trip.
This report is powered by de-identified consent-based mobile signal data from Azira.
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The data in this report is based on mobile signal data and proprietary models, and while efforts have been made to ensure accuracy, we do not guarantee its completeness. This report is for informational purposes only and should not be considered investment advice. We are not liable for any decisions or actions taken based on the report. Third-party use of this report must include proper attribution to Loculyze and is not permitted for commercial purposes without prior consent. The report is provided 'as is' without any warranty.
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All content in this report is the intellectual property of Loculyze. Redistribution or commercial use without written permission is prohibited. Proper attribution is required if the report is cited or referenced. By using this report, you agree to indemnify Loculyze against any claims arising from its use.