Dynamic footfall

     1. Analysis Objective 

The dynamic footfall analysis shows the evolution of pedestrian traffic in front of an address or the footfall in a specific location (store, shopping centre and shopping area) over a certain period of your choice. 

This analysis allows you to understand the history and trend of a specific location, measure the impact of internal and external changes on your asset, and compare it with up to 3 other locations.

     2. Methodology and Computation

• Based on mobile application GPS data: 200bn+ of GPS points per year in all our countries 
• We work with more than 100 partners mobile apps
• 65,000 field counts in Europe to adjust raw data

💡The data is updated once per month, on the 8th, for the last month.

When the last calendar week of the month overlaps with the following month, it will be visible on the platform when the following month is updated (for example: in October 2024, the last calendar week was from 27 October to 2 November. The first 3 weeks were available in the 8 November update, while the last week was available on 8 December).

Counting methods
Address	Total number of visits per person per day within a radius of 16 metres of the GPS point: a person is counted as many times as he or she passes in front of the address.
Store and shopping centre	Total number of unique visitors per day: a person is counted if he or she stays in the zone for more than 10 minutes. Weekly and monthly view: A person is counted only once per day (pedestrian and vehicle) even if he or she enters and leaves several times. We exclude employees for shopping centres and stores.
Shopping area	Total number of unique visitors per day: a person is counted if he or she stays in the zone for more than 10 minutes. Weekly and monthly view: A person is counted only once per day (pedestrians only) even if he or she enters and leaves several times.

💡More information about our methodology: Quantification algorithms

     3. How to use it

Features: 

• Compare up to 3 different zones or addresses with each other
• Add events markers
• Filter on a weekly or monthly view
• Export in PDF or Excel

To start an analysis: 

• Select your asset (you can analyse a unique location).
• For comparison mode (1): add a second asset by clicking on the box below the main one.
• Define a period (2): choose a start and end time.
• Dwell time (3): you can display it for polygons on a monthly basis or compare it to a previous year by checking the box.
• Compare to a previous year (4): display the comparison by checking the box.
• Time period (5): define the granularity on a weekly or monthly basis.
• Events markers (6): create some markers.

Showcase your analysis on a graph or a table (7):

• By clicking on the icon in the upper right corner. 
• In the table version, you will see the footfall evolution compared to the previous week in percentage.

Important: Comparing different types of assets (address vs shopping centre) is not always relevant. Because of the lack of relevancy and the different methodologies behind the footfall computation., comparisons are available only between assets that can be compared:

• An address is comparable only to another address. 
• Stores or shopping centres can be compared between them.
• A shopping area is comparable only to another shopping area

     4. How to read it

Example: If we look at footfall in Paris Rivoli Centre zone (red line), we see a drop in traffic in August 2023 (summer period), then an increase from September, corresponding to the start of the school year, followed by a peak in December (end-of-year festivities).

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

• Carry out impact studies by observing seasonal peaks, tourist or shopping periods.
• Identify irregular periods and implement action plans.
• Compare your footfall with previous years or before COVID.
• Use the data to promote your addresses or areas to potential customers.
• Strengthen your arguments with retailers and give them figures to compare with their view of the situation on the ground.

     5. Frequently Asked Questions

Why can I not access the analysis?

You may not have access to the analysis because the average pedestrian traffic of your address may be below the minimum thresholds that guarantee data reliability.