Chain/Venue Multi-Metrics
Placer will upload your feeds to your bucket in the schema detailed below on a daily/weekly basis.
Filenames, path, and retention policy:
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Files will be provided on Amazon Web Services (AWS) S3 or Google Cloud Storage (GCS) (see Delivery Options)
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Files will be exported until midnight UTC every day.
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File path will include your custom bucket name with the following addition: '/export/analytics/multi_metrics/[DAILY/WEEKLY]/[DATE]
Daily/Weekly- refers to data aggregation type by the time -
Files are divided per chain and export configuration. Examples:
multi_metrics_daily_chain_2020-07-27_Walmart_2017-01-01_2020-07-25.csv.gz - Walmart Daily aggregated chain data, that was published on July 27, 2020. The file includes historical data from January 2017.
multi_metrics_weekly_property_2020-07-27_Walmart_2017-01-01_2020-07-25.csv.gz - Walmart Weekly individual property level Data, that was published on July 27, 2020. The file includes historical data from January 2017. -
Files are available formatted as CSV or as Parquet.
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Files are GZip compressed
Schema Overview
| Column | Description | Type | Example |
|---|---|---|---|
| publication_date | Data publication date | ISO-8601 | 2020-08-01 |
| version_code | Calibration version code | string | 1.0.0 |
| id | Placer's entity ID | string | '5965fca0173f564b883c222e' |
| name | Entity name | string | 'Mcdonald's' |
| type | Entity type. See Location Info for a full list of supported types. | string | 'venue' |
| time_frame | Data aggregation resolution. Supported values: 'daily', 'weekly' and 'monthly'. | string | 'daily' |
| start_date | Data start date. | ISO-8601 | 2018-04-15 |
| end_date | Data end date (inclusive) | ISO-8601 | 2018-04-15 |
| region_type | 'nationwide', 'state', 'dma' & 'cbsa' are supported. Note: CBSA is the union of MSAs & micro-MSAs | string | 'nationwide' |
| region_name | Region's name | string | 'California' |
| region_code | Region's code | string | 'CA' |
| lat | The entity's latitude. Only available for entities of type 'venue' or 'complex | double | 37.786099 |
| lng | The entity's longitude. Only available for entities of type 'venue' or 'complex | double | -121.46352 |
| ticker_symbol | The stock exchange ticker symbol | string | 'MCD' |
| company_name | If available, the parent company chain name. | string | 'Mcdonald's' |
| foottraffic | Estimated foot-traffic in the location during the relevant time frame. Foot-traffic is extrapolated from the panel_visits. | long | 5000000 |
| panel_visits | The actual number of visits generated by Placer's panel (observed visit). | long | 50000 |
| home_distance _estimated_foottraffic_X (multiple columns) | The accumulative foottraffic generated by customer who live within 'X' miles of the property. Includes a column per distance(mi) as follows: 0.3, 0.5, 0.7, 1, 2, 3, 5, 7, 10, 30, 50, 100, 250, 250+ Example: 'home_distance _estimated_foottraffic_50' means the sum of foottraffic generated by customers who live within 50 miles of the property | integer | 40000 |
| home_distance _percentage_X (multiple columns) | The percentage of foottraffic generated by customer who live within 'X' miles of the property. Includes a column per distance(mi) as follows: 0.3, 0.5, 0.7, 1, 2, 3, 5, 7, 10, 30, 50, 100, 250, 250+ | double | 25.485 |
| work_distance _estimated_foottraffic_X (multiple columns) | The accumulative foottraffic generated by customer who work within 'X' miles of the property. Includes a column per distance(mi) as follows: 0.3, 0.5, 0.7, 1, 2, 3, 5, 7, 10, 30, 50, 100, 250, 250+ | integer | 4000 |
| work_distance _percentage_X (multiple columns) | The percentage of foottraffic generated by customer who work within 'X' miles of the property. Includes a column per distance(mi) as follows: 0.3, 0.5, 0.7, 1, 2, 3, 5, 7, 10, 30, 50, 100, 250, 250+ | double | 13.35 |
| foottraffic_per_sqft | The number of visits at the property during the relevant time frame by its size (square footage) | double | 10.91 |
Additional Metrics
From time to time, Placer may add additional metrics to the schema. They will be appended as additional columns, and you will be given a 30 days note in advance with a sample file.
Sample files
Note
- Use the following files to review the delivery format structure and compression method.
- The delivery will include more data (history/chains/venues).
- Files contain fake data and therefore cannot be used for data-evaluation
Sample #1 - Daily Chain-level data for Walmart Supercenter, Only January 2017 - CSV formatted
Sample #2 - Weekly Venue-level data for a selected Applebee's store in Q1/Q2 2017 - CSV formatted
Updated 15 days ago