Chain Visit Forecast
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 |
File format | CSV |
Regions | The following regions can be selected for your delivery:
|
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 |
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 |
Updated 1 day ago