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The download button allows to download data in CSV form. Selecting the date range followed by the level of granularity required, will allow to receive data for:

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Data type Description
Footfall For all walls and areas
Reidentification For all walls and areas
Media For screens and spots
Roadshows For viewer, visitor, engaged visitor and buyer metrics relating to roadshows

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After opening, the downloaded file will appear in the following format. In this example, the download for walls is illustrated:

column type example comment
start_date timestamp 2024-10-01 00:00:00 Start hour for the footfall record
end_date timestamp 2024-10-01 23:59:59 End hour for the footfall record
wall_id int 1 ID identifying the point-of-interest in the shopping mall (the POI is located at a specific floor)
wall_name string example_wall_name_1 Name of the wall in digeiz database
wall_type string CELL Multiple values are possible : CELL, KIOSK, GATE, RETAILER_GATE, ...
wall_external_identifier string wall_external_identifier_1 Rental unit name from the shopping mall owner, i.e. how the cell is identified in thier rent database
subcategory_id int 1 ID identifying the subcategory of the brand associated with the wall if the wall type is relevant (CELL=store, KIOSK). A subcategory is the activity of the brand in the wall. For example, women fashion for Zara.
subcategory_name string example_subcategory_1 Name of the subcategory for the brand
subcategory_external_identifier string subcategory_external_identifier_1 Identifier from the shopping mall owner, i.e. how the subcategory is identified in their database
brand_id int 1 ID identifying the brand in the wall for this specific date
brand_name string example_brand_1 Name of the brand
brand_external_identifier string brand_external_identifier_1 Identifier from the shopping mall owner, i.e. how the brand is identified in their database
floor_id int 1 ID identifying the floor
floor_elevation float -1 Floor level of the wall in the shopping mall. This is a float since there can be some mid-levels (ex: 0.5)
floor_external_identifier string floor_external_identifier_1 Identifier from the shopping mall owner, i.e. how the floor is identified in their database
people_in int 0 Total number of people entering the wall in the time interval [start_date, end_date]
people_out int 0 Total number of people leaving the wall in the time interval [start_date, end_date]
people_window_flow int 77 Total number of people in the surroundings of the wall in the time interval [start_date, end_date]. In most cases, the surrounding is a counting zone inside the shopping mall.
people_bounce int 0 Total number of people entering and leaving immediately the wall in the time interval [start_date, end_date].
gender_classification string man Gender classification (man, woman, unknown)
group_classification string group Group classification (single, couple, group)
age_from int 0 Age classification (minimum age for the record), for unknown, the age_from=0, age_to=100
age_to int 15 Age classification (maximum age for the record), for unknown, the age_from=0, age_to=100
is_estimated bool FALSE Whether the data is directly generated by the CCTV processing, or whether it was reconstructed because of an incident (server, network, camera, ...)
reliability float 95 How reliable is the video stream during the record time interval
reliability_comment string offline Comment for the video stream reliability (origin of the low relaibility - low FPS, no images, ...)
mall_id int 1 ID identifying the mall
mall_name string example_mall_name_1 Name of the mall in digeiz database
mall_external_identifier string 1 Identifier from the shopping mall owner, i.e. how the mall is identified in their database

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