Premium Export
Overview
Premium Export enables the delivery of Placer data at scale for businesses looking to enhance their in-house data analytics capabilities with accurate location data.
This feed provides delivery of various location metrics, allowing you to combine up-to-date location data into your first-party data and build internal reports, applications, and dashboards.
Configuration
| Configuration aspect | Available options descriptions |
|---|---|
| Data granularity | Daily - Available with the metrics explicitly specified and tagged with "Available for daily aggregation". Daily feed is available on a chain level only. Weekly and Monthly - Available with all the listed metrics within the schema |
| File formats | CSV and PARQUET |
| Regions | The following regions can be selected for the different regional chains: - Nationwide - State - DMA - CBSA |
| Feeds time frame | The feed's timeframe can be configured to commence from January 2017 or any later date. |
| Delivery methods | Please refer to the following Delivery Details for all supported Premium export feed delivery options. |
| Delivery Schedule | Here is the delivery scheduling for each of the available feeds: Weekly: Delivered each Thursday Monthly: Delivered on the 6th of each month |
| Control files | Supported |
| Success file | Supported |
| Amazon SNS notification | Supported |
Deliverables and Schemas
Metrics
Metrics availability
Please note that not all metrics are available for all types of entities in all possible granularities. You can check the availability of metrics here.
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' |
| name | Entity name | string | 'McDonald's' |
| type | Entity type. Supported entity types: 'venue', 'complex', 'chain', and 'billboard'. | string | 'venue' |
| time_frame | Data aggregation resolution. Supported values: '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', 'state', 'dma' & 'cbsa' are supported. Only available for entities of type 'chain.' 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' |
| visit_duration_segmentation | Displays the visit duration segmentation used for the generation of the raw reported data. The values within this column may fall into one of the following categories: - 'under_10_min' - '10_min_or_longer' - 'all_visits' | string | 'under_10_min' |
Visit Metrics
The set provides foot traffic data, breakdowns by time of day, day of week, and dwell times, as well as distance metrics to home and work locations.
| Column | Description | Type | Example |
|---|---|---|---|
| foottraffic 📅 Available for daily aggregation | Estimated foot traffic in the location during the relevant time frame. Foot-traffic is the extrapolated value of visits. Total of: 1 column | long | 5000000 |
| foottraffic_per_sqft | The number of visits at the property during the relevant time frame by its size (square footage) Not available for billboard-type entities Total of: 1 column | double | 10.91 |
| home_distance_estimated_foottraffic_X 📅 Available for daily aggregation | The accumulative foot traffic generated by customers who live within 'X' miles of the property. Total of: 14 columns. Each represents a different value of X: 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 visits generated by customers who live within 50 miles of the property | long | 40000 |
| home_distance_percentage_X 📅 Available for daily aggregation | The accumulative percentage of foot traffic generated by customers who live within 'X' miles of the property. Total of: 14 columns. Each represents a different value of X: 0.3, 0.5, 0.7, 1, 2, 3, 5, 7, 10, 30, 50, 100, 250, 250+ Example: 'home_distance_percentage_50' means the percentage of visits generated by customers who live within 50 miles of the property out of the total foot traffic for the defined period. | double | 25.485 |
| work_distance_estimated_foottraffic_X 📅 Available for daily aggregation | The accumulative foot traffic generated by customers who work within 'X' miles of the property. Total of: 14 columns. Each represents a different value of X: 0.3, 0.5, 0.7, 1, 2, 3, 5, 7, 10, 30, 50, 100, 250, 250+ Example: 'work_distance_estimated_foottraffic_50' means the sum of visits generated by customers who work within 50 miles of the property | long | 4000 |
| work_distance_percentage_X 📅 Available for daily aggregation | The accumulative percentage of foot traffic generated by customers who work within 'X' miles of the property. Total of: 14 columns. Each represents a different value of X: 0.3, 0.5, 0.7, 1, 2, 3, 5, 7, 10, 30, 50, 100, 250, 250+ Example:'home_distance_percentage_50' means the percentage of visits generated by customers who live within 50 miles of the property out of the total foot traffic for the defined period. | double | 13.35 |
| avg_visits_per_day | Describes the average visitation amount for a single day during the defined period. Total of: 1 column | double | 5984.44 |
| visits_by_day_of_week_X | Estimated aggregation of foot traffic bucketed by the day of the week. Total of: 7 columns Each represents a different value of X: monday, tuesday, wednesday, thursday, friday, saturday, sunday Example:'visits_by_day_of_week_sunday' means the number of visits generated by the POI's customers on Sundays for the defined period. | long | 5768 |
| visits_by_hour_of_day_X 📅 Available for daily aggregation | Estimated aggregation of foot traffic bucketed by the hours of the day. Total of: 24 columns Each represents an hour of the day. Example:'visits_by_hour_of_day_02:00_03:00' means the number of visits generated by the POI's customers between 2am and 3am (exclusive). | long | 1245 |
| visits_by_dwell_time_X 📅 Available for daily aggregation | Estimated aggregation of foot traffic bucketed by length-of-stay duration ranges. Total of: 13 columns Each represents a range of length-of-stay durations in minutes: 0-5(New! DV 2.0), 5-10(New! DV 2.0), 10-15(New! DV 2.0),15-30, 30-45, 45-60, 60-75, 75-90, 90-105, 105-120, 120-135, 135-150, 150 and more. Example: 'visits_by_dwell_time_90_105' means the number of visits generated by the POI's customers that stayed at the property between 90 to 105 (exclusive) minutes. | long | 654 |
| avg_dwell_time 📅 Available for daily aggregation | Describes the average visit length of stay in minutes during the defined period in the analyzed POI. Total of: 1 column | double | 15.6 |
Advanced Visit Metrics
This set provides visitor counts, visit frequency data and other statistics beyond basic foot traffic metrics.
| Column | Description | Type | Example |
|---|---|---|---|
| unique_visitors | Estimated unique visitors Total of: 1 column | double | 7000 |
| median_visits_per_day | Describes the median visitation amount for a single day during the defined period. Total of: 1 column | double | 6745.23 |
| median_dwell_time | The median length of stay in the analyzed POI. Total of: 1 column | double | 16.3 |
| avg_visits_frequency | The mean number of visits made by visitors to the analyzed POI. Total of: 1 column | double | 2.5 |
| visitors_percent_by_freq_X | Each bin of this metric represents the estimated number of unique visitors that visited the analyzed POI a certain number of times. Total of: 13 column Each represents a different value of X: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30 or more Example: 'visitors_percent_by_freq_15' means the number of unique visitors percentage to the property within the defined period who visited the property between 10 to 15 times. | double | 0.1234567 |
Census Potential Trade Area
This set provides demographic information based on Census 2022 dataset for the potential trade area of a property or a chain.
| Column | Description | Type | Example |
|---|---|---|---|
| census_potential_by_ethnicity_X | The demographic (based on Census 2022 dataset) distribution of the analyzed POI's potential market population (considering the 70% top most visited CBGs), segmented by ethnicity bins. Total of: 8 columns Each represents a different value of X: white, hispanic_or_latino, black, Asian, multi race, American indian or Alaska, native Hawaiian and other pacific islanders, other Example: 'census_potential_by_ethnicity _asian' means the population within the POI's potential trade area during the defined period identified as Asian. ** Chain level data is available | double | 1455 |
| census_potential_by_education_X | The demographic (based on Census 2022 dataset) distribution of the analyzed POI's potential market population older than 25 years (considering the 70% top most visited CBGs), segmented by education bins. Total of: 5 columns Each represents a different value of X: advanced degree, bachelors degree, college or associates degree, high school, elementary Example: 'census_potential_by_education _bachlors_degree' means the population older than 25 years within the POI's potential trade area during the defined period identified as having a bachelor's degree. ** Chain level data is available | double | 3989 |
| census_potential_by_marital_status _X | The demographic (based on Census 2022 dataset) distribution of the analyzed POI's potential market population (considering the 70% top most visited CBGs), segmented by marital status bins. Total of: 4 columns Each represents a different value of X: never married, married, divorced, widowed Example: 'census_potential_by_marital_status _married' means the population within the POI's potential trade area during the defined period identified as married. ** Chain level data is available | double | 12311 |
| census_potential_avg_hhi | The average household income (based on Census 2022 dataset) of the analyzed POI's potential market households (considering the 70% top most visited CBGs). Total of: 1 column ** Chain level data is available | double | 4563 |
| census_potential_median_hhi | The median household income (based on Census 2022 dataset) of the analyzed POI's potential market households (considering the 70% top most visited CBGs). Total of: 1 column ** Chain level data is available | double | 3545 |
| census_potential_by_age_X | The demographic (based on Census 2022 dataset) distribution of the analyzed POI's potential market population (considering the 70% top most visited CBGs), segmented by age bins. Total of: 18 columns Each represents a different value of X: Less than 5, 5 to 15, 15 to 18, 18 to 22, 22 to 25, 25 to 30, 30 to 35, 35 to 40, 40 to 45, 45 to 50, 50 to 55, 55 to 60, 60 to 65, 65 to 70, 70 to 75, 75 to 80, 80 to 85, 85 or more Example: 'census_potential_by_age _5_to_15' means the population within the POI's potential trade area during the defined period between the ages of 5 and 15. ** Chain level data is available | double | 22768 |
| census_potential_population | The total population within the analyzed POI's potential market population (considering the 70% top most visited CBGs). Total of: 1 column ** Chain level data is available | double | 19879 |
Census Captured Trade Area
This set provides demographic information based on Census 2022 dataset within the captured trade area (based on actual visits) of a property or a chain.
| Column | Description | Type | Example |
|---|---|---|---|
| census_captured_by_education _X | The demographic (based on Census 2022 dataset) distribution of the captured market audience older than 25 years(considering 70% of the traffic volume), segmented by education bins. Total of: 5 columns advanced degree, bachelors degree, college or associates degree, high school, elementary Example: 'census_captured_by_education _bachlors_degree' means the audience older than 25 years within the POI's captured market during the defined period identified as having a bachelor's degree. | double | 4032 |
| census_captured_by_ethnicity_X | The demographic (based on Census 2022 dataset) distribution of the captured market audience (considering 70% of the traffic volume), segmented by ethnicity bins. Total of: 8 columns Each represents a different value of X: white, hispanic_or_latino, black, Asian, multi race, American indian or Alaska, native Hawaiian and other pacific islanders, other Example: 'census_captured_by_ethnicity _asian' means the population within the POI's captured market during the defined period identified as Asian. | double | 1442 |
| census_captured_by_hhi_X | The distribution of the households(based on Census 2022 dataset) within the captured market audience (considering 70% of the traffic volume), segmented by household income bins. Total of: 16 columns Each represents a different value of X: less_than_10K, 10K_to_15K, 15K_to_20K, 20K_to_25K, 25K_to_30K, 30K_to_35K, 35K_to_40K, 40K_to_45K, 45K_to_50K, 50K_to_60K, 60K_to_75K, 75K_to_100K, 100K_to_125K, 125K_to_150K, 150K_to_200K, more_than_200K Example: 'census2019_vd _70pct_by_hhi _45K_to_50K' means the number of households within the POI's captured market during the defined period identified as having an income between 45K and 50K. | double | 12654 |
| census_captured_avg_hhi | The average household income (based on Census 2022 dataset) within the captured market audience (considering 70% of the traffic volume). Total of: 1 column | double | 76243.98 |
| census_captured_median_hhi | The median household income (based on Census 2022 dataset) within the captured market audience (considering 70% of the traffic volume). Total of: 1 column | double | 113777.22 |
| census_captured_by_marital_status _X | The demographic (based on Census 2022 dataset) distribution of the captured market audience (considering 70% of the traffic volume), segmented by marital status bins. Total of: 4 columns Each represents a different value of X: never married, married, divorced, widowed Example: 'census_captured_by_marital_status _married' means the population within the POI's captured market during the defined period identified as married. | double | 11599 |
Popstats Potential Trade Area
This set provides demographic information based on STI:Popstats 2023 dataset for the potential trade area of a property or a chain.
| Column | Description | Type | Example |
|---|---|---|---|
| popstats_potential_population | The total population (based on STI:Popstats 2023) within the analyzed POI's potential market population (considering the 70% top most visited CBGs). Total of: 1 column ** Chain level data is available | double | 30546 |
| popstats_potential_by_household_types _X | The demographic (based on STI:Popstats 2023) distribution of the analyzed POI's potential market households (considering the 70% top most visited CBGs), segmented by household types. Total of: 7 columns Each represents a different value of X: households, one_person_households, married_couple, male_householder, female_householder, non_family_households, households_with_children Example: 'popstats_potential_by_household _types_married_couple' means the number of households within the POI's potential trade area during the defined period identified as married couples. ** Chain level data is available | ||
| popstats_potential_by_age_X | The demographic (based on STI:Popstats 2023) distribution of the analyzed POI's potential market population (considering the 70% top most visited CBGs), segmented by age bins. Total of: 18 columns Each represents a different value of X: Less than 5, 5 to 14, 14 to 18, 18 to 22, 22 to 25, 25 to 30, 30 to 35, 35 to 40, 40 to 45, 45 to 50, 50 to 55, 55 to 60, 60 to 65, 65 to 70, 70 to 75, 75 to 80, 80 to 85, 85 or more Example: 'popstats_potential_by_age _35_to_40' means the population within the POI's potential trade area during the defined period between the ages of 5 and 14. ** Chain level data is available | double | 2657 |
| popstats_potential_by_education_X | The demographic (based on STI:Popstats 2023) distribution of the analyzed POI's potential market population older than 25 years(considering the 70% top most visited CBGs), segmented by education bins. Total of: 9 columns Each represents a different value of X: doctorate_degree, professional_degree, masters_degree, bachelors_degree_only, associates_degree_only, some college, some high school, high school, elementary Example: 'popstats_potential_by_education _doctorate_degree' means the population older than 25 years within the POI's potential trade area during the defined period identified as having a doctorate's degree. ** Chain level data is available | double | 2711 |
| popstats_potential_by_hhi_X | The distribution of the households(based on STI:Popstats 2023) within the analyzed POI's potential market population (considering the 70% top most visited CBGs), segmented by household income bins(in USD). Total of: 26 columns Each represents a different value of X: less_than_10K, 10K_to_15K, 15K_to_20K, 20K_to_25K, 25K_to_30K, 30K_to_35K, 35K_to_40K, 40K_to_45K, 45K_to_50K, 50K_to_55K, 55K_to_60K, 60K_to_65K, 65K_to_70K, 70K_to_75K, 75K_to_80K, 80K_to_85K, 85K_to_90K, 90K_to_95K, 95K_to_100K, 100K_to_125K, 125K_to_150K, 150K_to_175K, 175K_to_200K, 200K_to_250K, 250K_to_500K, more_than_500K Example: 'popstats_potential_by_hhi _45K_to_50K' means the number of households within the POI's potential trade area during the defined period identified as having an income between 45K and 50K. ** Chain level data is available | double | 260 |
| popstats_potential_by_ethnicity_X | The demographic (based on STI:Popstats 2023) distribution of the analyzed POI's potential market population (considering the 70% top most visited CBGs), segmented by ethnicity bins. Total of: 5 columns Each represents a different value of X: white, black, Asian, hispanic, other Example: 'popstats_potential_by_ethnicity _asian' means the population within the POI's potential trade area during the defined period identified as Asian. ** Chain level data is available | double | 2145 |
| popstats_potential_avg_hhi | The average household income (based on STI:Popstats 2023) of the analyzed POI's potential market households (considering the 70% top most visited CBGs). Total of: 1 column ** Chain level data is available | double | 3655 |
| popstats_potential_median_hhi | The median household income (based on STI:Popstats) of the analyzed POI's potential market households (considering the 70% top most visited CBGs). Total of: 1 column ** Chain level data is available | double | 3433 |
Ranking
Uses visits and visits/sq foot to rank POIs within chains, categories and category groups.
| Column | Description | Type | Example |
|---|---|---|---|
| category_group_ranking_by _visits_X | This ranking metric presents the ranking of the analyzed POI within its category group based on the number of visits during the defined period. The ranking is given within 4 different regions: - nationwide - state - dma - cbsa For each region 2 measurements are available: category_group_ranking_by _visits_nationwide - represents the actual ranking of the POI within the region category_group_ranking_by _visits_nationwide_total - represents the total number of entities taken into consideration for the ranking within the region(in this example "nationwide") for the specific category group.Total of: 8 columns | int | 35 |
| category_ranking_by _visits_X | This ranking metric presents the ranking of the analyzed POI within its category based on the number of visits during the defined period. The ranking is given within 4 different regions: - nationwide - state - dma - cbsa For each region 2 measurements are available: category_ranking_by_visits _nationwide - represents the actual ranking of the POI within the region. category_ranking_by_visits _nationwide_total - represents the total number of entities taken into consideration for the ranking within the region(in this example "nationwide") for the specific category.Total of: 8 columns | int | 24 |
| chain_ranking_by _visits_X | This ranking metric presents the ranking of the analyzed POI within its chain based on the number of visits during the defined period. The ranking is given within 4 different regions: - nationwide - state - dma - cbsa For each region 2 measurements are available: chain_ranking_by_visits _nationwide - represents the actual ranking of the POI within the region. chain_ranking_by_visits _nationwide_total - represents the total number of entities taken into consideration for the ranking within the region(in this example "nationwide") for the specific chain.Total of: 8 columns | int | 8 |
| category_group_ranking_by _visits_per_sqft_X | This ranking metric presents the ranking of the analyzed POI within its category group based on the number of visits per square feet during the defined period. The ranking is given within 4 different regions: - nationwide - state - dma - cbsa For each region 2 measurements are available: category_group_ranking_by _visits_per_sqft _nationwide - represents the actual ranking of the POI within the region category_group_ranking_by _visits_per_sqft _nationwide_total - represents the total number of entities taken into consideration for the ranking within the region(in this example "nationwide") for the specific category group.Total of: 8 columns | int | 15 |
| category_ranking_by _visits_per_sqft_X | This ranking metric presents the ranking of the analyzed POI within its category based on the number of visits per square feet during the defined period. The ranking is given within 4 different regions: - nationwide - state - dma - cbsa For each region 2 measurements are available: category_ranking_by_visits _per_sqft_nationwide - represents the actual ranking of the POI within the region. category_ranking_by_visits _per_sqft_nationwide_total - represents the total number of entities taken into consideration for the ranking within the region(in this example "nationwide") for the specific category.Total of: 8 columns | int | 33 |
| chain_ranking_by _visits_per_sqft_X | This ranking metric presents the ranking of the analyzed POI within its chain based on the number of visits per square feet during the defined period. The ranking is given within 4 different regions: - nationwide - state - dma - cbsa For each region 2 measurements are available: chain_ranking_by_visits _per_sqft_nationwide - represents the actual ranking of the POI within the region. chain_ranking_by_visits _per_sqft_nationwide_total - represents the total number of entities taken into consideration for the ranking within the region(in this example "nationwide") for the specific chain.Total of: 8 columns | int | 2 |
Retail Sales
Available to Retail Sales customers, this metric set provides sales estimates and traffic counts for POIs.
| Column | Description | Type | Example |
|---|---|---|---|
| sales | The total dollar value (USD) of all sales generated for the analyzed POI during the defined period. | double | 2324566.25 |
| sales_transactions | The total number of sales transactions, which took place at the analyzed POI during the defined period. | double | 34250 |
| sales_average_ticket_size | The average dollar value per transaction generated at the analyzed POI during the defined period. | double | 22.45 |
| sales_per_sqft | The total dollar value (USD) of sales per sq ft generated at the POI during the defined period. | double | 145.39 |
| category_group_ranking_by _sales_X | This ranking metric presents the ranking of the analyzed POI within its category group based on the total sales during the defined period. The ranking is given within 4 different regions: - nationwide - state - dma - cbsa For each region 2 measurements are available: category_group_ranking_by _sales_nationwide - represents the actual ranking of the POI within the region category_group_ranking_by _sales_nationwide_total - represents the total number of entities taken into consideration for the ranking within the region(in this example "nationwide") for the specific category group.Total of: 8 columns | int | 55 |
| category_ranking_by _sales_X | This ranking metric presents the ranking of the analyzed POI within its category based on the total sales during the defined period. The ranking is given within 4 different regions: - nationwide - state - dma - cbsa For each region 2 measurements are available: category_ranking_by_sales _nationwide - represents the actual ranking of the POI within the region. category_ranking_by_sales _nationwide_total - represents the total number of entities taken into consideration for the ranking within the region(in this example "nationwide") for the specific category.Total of: 8 columns | int | 145 |
| chain_ranking_by _sales_X | This ranking metric presents the ranking of the analyzed POI within its chain based on the total sales during the defined period. The ranking is given within 4 different regions: - nationwide - state - dma - cbsa For each region 2 measurements are available: chain_ranking_by_sales _nationwide - represents the actual ranking of the POI within the region. chain_ranking_by_sales _nationwide_total - represents the total number of entities taken into consideration for the ranking within the region(in this example "nationwide") for the specific chain.Total of: 8 columns | int | 34 |
Deprecated Columns
Captured market age and gender metrics
| Column | Description | Type | Example |
|---|---|---|---|
| vd_age_X (Visitors demographics) | The distribution of the analyzed POI's visitors' ages Total of: 3 columns Each represents a different value of X: 18 to 37, 38 to 51, 52 or more Example: 'vd_age_18_to_37' means the visitors to the property during the defined period between the ages of 18 and 37. - Limited coverage | double | 3000 |
| vd_gender_X (Visitors demographics) | The gender of visitors at the property analyzed is presented as either Male or Female. Total of: 2 columns Each represents a different value of X: female, male Example: 'vd_gender_female' means the visitors to the property during the defined period identified as female. - Limited coverage | double | 15000 |
POI metadata
Please refer to the following page for the POI metadata schema.
Metadata for Tags
Customers that request a metadata file for feeds that contain tags (i.e. the feed’s entity list is defined using tags) will receive a tags_entities_mapping.csv file to supplement your analysis.
The tag entities mapping file helps to bridge the relationship between tags and the entities they contain, offering a clear data structure that enhances the traceability and usability of the delivered tag-based data.
The metadata file includes the following schema:
| Column | Description | Type | Example |
|---|---|---|---|
| tag_id | The identifier of the tag. | string | '636371ee42a729232a6b755e' |
| tag_name | The name of the tag. | string | 'My Tag' |
| entity_id | The identifier of the entity associated with the tag. | string | '5965fca0173f564b883c222e' |
| entity_type | The type of entity (i.e. venue, complex, chain or billboard) associated with the tag. | string | 'venue' |
This file helps you easily correlate feed entities with the originating tags, enabling streamlined data validation, filtering, and analysis.
Sample files
Sample Premium Export (CSV file)
Grow and expand
Follow our announcements regarding additional attributes (metadata) and metrics.
New metadata attributes will be announced and delivered to you once released.
Please contact your customer support manager to receive new/additional metrics as part of your feed.
Columns order
Please be aware that the order of columns may change slightly due to the continuous addition of data to the export and its associated metadata.
Privacy comes first
Placer is a privacy-first company, and like all our product this feed conforms to our privacy policy as is described in our Trust Center. In situations where the content of this feed conflicts with our privacy policy, the conflicting data points will be redacted from the files.
Updated 1 day ago