The future of defining catchment areas

Choosing the correct catchment area for a land use strategic plan is crucial. The catchment area defines the scale and scope of the customer base for retail development and, therefore, the likely local job and floorspace demand. The more accurate the catchment area, the more likely the plan will reflect reality and, consequently, become a useful document.??

?

Until now, mapping catchment areas for retail land use planning has relied on travel-time analysis. This calculates the time it takes for people to reach a retail destination by car and usually assigns residents to their nearest centre. Sometimes we improve accuracy by adjusting for the scale of each centre (this is the gravity model approach), which means someone may not be assigned to their nearest centre. Occasionally, we go even further by validating our assumptions with a visitor survey.??

?

At its base, though, this travel-time method assumes catchment areas are geographically contiguous, generally disregards other modes of transport and ignores potential barriers such as natural features or urban infrastructure. The result is a catchment area that may not reflect actual consumer movement patterns.??

?

With the availability of spatial bank transaction data, like Spendmapp, there is simply no need to do this. The bank data gives us precise information about where customers are located and where they purchase their goods and services. Comparing this data with the traditional travel-time catchment area mapping often reveals significantly different boundaries. The following maps illustrate this problem. They contrast what the actual consumer behaviour data tells us versus what travel-time analysis produces.??

In Figure 1, 70% of the drivetime catchment area is not in the actual retail catchment for Aldinga Beach. In Figure 2, it is 11%. Residents of these areas clearly and regularly choose somewhere else to make their purchases.??

?

Errors of this scale can result in significant financial repercussions. It misallocates millions of dollars in expenditure and will lead to flawed estimations of job creation and floor space demand by hundreds of full-time equivalent jobs and thousands of square meters.?

?

Considering we have access to data that gives us far more precise measures, there is no reason to tolerate these errors. Using transaction data enables more informed decision-making in land use planning. It will strengthen the defensibility of proposals before planning panels, and it will simply make us better retail and land use planners.?