Overview

The Chain Visits Forecast Feed delivers projected foot traffic estimates for retail chains, helping you optimize operations, improve planning, and mitigate risks. Get an accurate visitation forecast with a confidence interval, based on the historical performance of the chain. View expected visit counts for the chain, detailed by state or nationwide, over the next 90 days.

Configuration

Configuration aspect	Available options descriptions
Data granularity	Daily Weekly Monthly
File format	CSV
Regions	The following regions can be selected for your delivery: - Nationwide - State
Feeds time frame	The feed’s timeframe covers history.
Delivery methods	The feed can be configured to deliver to your email, GCS,S3, or Azure buckets
Delivery Schedule	Weekly: Delivered each Thursday Monthly: Delivered by the 10th of each month

Deliverables and Schemas

Forecast and Entity Metrics

Please refer to the definitions and structure of each metric:

Column	Description	Type	Example
publication_date	Data publication date	ISO-8601	2024-08-01
version_code	Calibration version code	string	2.1.0
id	Placer's entity ID	string	'5965fca0173f564b883c222e'
type	Entity type. Supporting 'chain' only	string	'chain'
name	Entity name	string	'McDonald's'
time_frame	Data aggregation resolution. Supported values: 'daily', 'weekly' and 'monthly'.	string	'monthly'
start_date	Data start date.	ISO-8601	2018-04-15
end_date	Data end date (inclusive)	ISO-8601	2018-04-15
region_type	'nationwide' and 'state' are supported.	string	'state'
region_name	Region's name	string	'California'
region_code	Region's code	string	'CA'
visits_forecast	A predicted number of visits to the entity for the future period	int	10340
yoy_forecast	The projected year-over-year percentage change in visits	float	0.05
confidence_interval_low	The lower bound of the confidence interval for the forecast	int	8000
confidence_interval_low	The upper bound of the confidence interval for the forecast	int	12934

Model Accuracy Metadata

Column	Description	Type	Example
id	Placer's entity ID	string	'5965fca0173f564b883c222e'
type	Placer's entity type	string	'chain'
ticker_symbol	The stock exchange ticker symbol	string	'MC'
name	Placer’s entity name	string	'Sephora'
category	Entity’s category	string	'Beauty & Spa'
sub_category	The subcategory of the entity	string	'Cosmetics Shops'
locations	Total number of Placer entities	int	400
locations_showing_visits	Number of Placer entities with foot traffic data included	int	350
mape	Mean absolute percentage error, representing how far off the model is from the actual value on average	float	0.89