Shared visitors

     1. Analysis Objective 

We calculate the proportion of common visitors between two assets to give an idea of the cannibalisation existing between them. You will learn more about the affinity and the shared visitors between them. It is available for an address, store, shopping centre, or shopping area.

This analysis will enable you to compare shared visitor's evolution for 2 addresses or areas, evaluate the level of competition in your catchment area, and measure the impact of your action plan.

     2. Methodology and Computation

• Shared visitors = number of visitors who visited two locations during the same period / number of visitors to the resource analysed.
• For addresses and shopping areas: we take into account both pedestrians and vehicles.
• For stores and shopping centres: we take account of pedestrians only.
• The data is updated once per month, on the 8th, for the last month.

💡More information about our methodology: Shared visitors algorithm

     3. How to use it

Features: 

• Compare up to 3 different zones or addresses with each other
• Monthly comparison
• Dynamic map
• 2 views: same week & same month
• Export in PDF or excel

To start an analysis: 

• Select your asset 
• Compared asset (1): add a second asset to compare.
• Analysed period (2):  define a start and end period.
• Shared visitor frequency (3): The time interval can be "Week" or "Month". e.g. if you select "Same month", the indicator will only count visitors passing through the two selected assets in the same month.

Tips: Move your mouse over the graph and select a specific neighbourhood to see the percentage of residents going to your asset and to the compared one.

Please note: For address objects, this analysis takes into account all visitors to the address's neighbourhood. So if you analyse 2 addresses in the same district, you will obtain 100% of visitors in common.

     4. How to read it 

Example: On average, 7.24% of visitors to Agen Centre also visited Montauban Centre in January 2024.

Here are some use cases and advice on how to use this analysis effectively.

• Analyse the proportion of joint visitors between 2 zones.
• Identify trends over a long period.
• Observe cannibalisation effects between 2 zones.

     5. Frequently Asked Questions