Effective Retail Chain Expansion Through The Use of Location Analytics

Effective Retail Chain Expansion Through The Use of Location Analytics

Location has always been a key consideration for retailers but with the changing habits and demands of today’s consumers’ many more elements need to be analysed for success.

For established retailers, location has always been important with careful consideration of the local demographic and accessibility. With an increasingly mobile consumer, location planning and customer insight departments have further analysis to make when analysing their customers.

In order to be able to make more accurate expansion decisions retailers need to be aware of their current and potential customers shopping habits, current and future locations, daily routines, preferred outlets and what is influencing all this behaviour.

As an example, the change in location and outlet size of UK supermarkets from large out of town locations to convenience outlets with smaller footprints and more locally situated. This is especially interesting from a strategy point of view, as retailers are increasing the store density, forming business clusters that reach customers at every corner and are more cost effective to manage or close.

Location is considered to be one of the main factors that influence shop performance. It is very important in making strategic decisions that minimise production/distribution costs and can provide competitive advantage in the face of other retailers.

How can Location analytics help?

Location analytics can help retailers to set up the ideal branch, since it enables them to track relevant factors such as:

  • Areas where online/offline sales have been high or low
  • Ideal customer concentration with pinpoint precision
  • Client lifestyle profiles
  • Competitors’ locations
  • Mapping loyalty card location data
  • Available real estate opportunities
  • Local business densities
  • Accessibility of the outlet

Cross-referencing these variables can provide retailers with accurate customer demographic and psychographic profiles. As a basic example, retailers might be interested in women within a certain age range, of a high socioeconomic level that have shopped for certain kinds of items online.

By locating this specific profile within an area and then being able to visually assess patterns retailers can predict potential size of their market, allowing them to make accurate strategic location decisions.

This maximises retailers` revenue and decreases the risk of investing in unnecessary expansions and instead target less promising areas through digital efforts.

Location analytics is a tool that can provide far greater insight into what influences customers’ behaviour thus providing more evidential support for business expansion, revenue maximisation and more informed strategic planning.

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