Placecast™ Select
Motionworks Placecast™ Select provides a complete profile of activity at a Motionworks Place or Region during a given timeframe.
Motionworks Placecast™ Select provides a complete profile of activity at a Motionworks Place or Region during specific dates and times. These insights are produced with the Motionworks Population Intelligence Platform. Placecast™ Select is best used to understand all the dimensions of activity at an individual place or group of places (all movie theaters in a market) during user-specified dates/times. This could be to understand a single event (concert over 6 hours at a location) or groups of events over time (movies in the park on the third Saturday of each month last summer). The dimensions of data include:
- Reference to a Motionworks place or Motionworks place set
- Activities by type, including short visits (dropoffs and overnight stays).
- Activities by long-distance travelers (50mi from home).
- Activities by demographic segment.
- Activities by top consumer segment.
- Home locations of guests by:
- Surrounding neighborhood or postal code.
- Nationwide by State, County, or Metropolitan Area.
- Standard dwell time distributions.
- Mode of travel for trips passing by the location.
Scenario Requests
In order to facilitate a Placecast™ Select analysis, the user must provide certain input data that defines the scenario being analyzed.
The following are required:
- A single Motionworks Place or a Motionworks Place set.
- Timeframe - A specific date and time or set of dates and times. These should be provided in the same time zone as the place or places included in the scenario.
The following are optional:
- Motionworks segment IDs - The scenario will return top segments, but if specific segments are needed, the identifiers should be provided to ensure they are included. More information is available on Population, Consumer, and PRIZM segment.
- Custom dwell threshold - The default behavior will use the same dwell time threshold as the place or places being used in the scenario. However, if a different dwell time threshold is required for the scenario, this can be provided as a value in minutes.
Scenario Response Dimensions
- Frequency Published by request.
- Geographic coverage Summarizes activities for residents of the U.S. for Motionworks Places and Regions.
- Zone systems Not applicable. No zone systems are used in reporting data in this schema.
- Date availability Specific dates and times from 2019 through the current latency period.
- Latency Data are available on a 15-day latency. For example, by 27 March 2023, data through 12 March 2023 will be available.
Scenario Response Schema
Name | Description | Type | Example |
---|---|---|---|
scenario_identifier | Unique and persistent identifier of the input details for this scenario | Integer | 275640 |
activities | Total activities at all of the places part of the scenario where an activity refers to any significant time spent at a place. Activities are the sum of dropoffs and visits , which are differentiated by a dwell time threshold. | Integer | 1765 |
visits | Total visits at all of the places part of the scenario. A visit is an activity with a measured dwell time at the place greater than or equal to activities_dwell_threshold . | Integer | 1013 |
dropoffs | Total dropoffs at all of the places part of the scenario. A dropoff is an activity with a measured dwell time at the place less than ‘activities_dwell_threshold‘. | Integer | 752 |
passbys | Total pass-bys at all of the places part of the scenario. A pass-by has zero dwell time at the place and is NOT an activity. They do not count as a dropoff or visit (or stay). | Integer | 172 |
stays | Total stays at all of the places part of the scenario. In short, a stay is an overnight visit. Stays are a subset of ‘visits‘, meaning a ‘stay‘ counts as a ‘visit‘, but not all ‘visits‘ count as a ‘stay‘. A stay is a visit with a measured dwell time of at least 4 hours inclusive of 03:00 a.m. in local time. If the scenario does not include a date and time that includes overnight periods the stays will be 0. | Integer | 261 |
visits_ci | 90% confidence interval of the ‘visits‘ estimate. If we were to repeatedly make new estimates of ‘visits‘ using the same procedure with new data from different samples of people, the confidence interval would contain the resulting estimate 90% of the time. | JSON [Integer, len=2] | [913, 1113] |
visits_observations | The number of visits observed directly in the sample in total over the time frame in the scenario. | Integer | 59 |
imputed | A boolean flag indicating whether the estimates for the scenario were imputed with a larger time window than the scenario defined time frame. If true, activities , visits , dropoffs , passbys , stays , and all other included metrics are imputed. | Boolean | true |
visits_avg_dwell | Average dwell time (in minutes) per person over the time frame in the scenario, ignoring those panel members who live in the associated block group(s) that intersect the place or that work in the place. | Number (Float) | 47.1 |
activities_dwell_threshold | The dwell time threshold (in minutes) for the place. Activities measuring a dwell time less than this threshold at this place are counted as dropoffs , and activities measuring a dwell time greater than or equal to this threshold at this place are counted as visits . Default value is a minimum of 2 minutes and a maximum of 30 minutes, but can be defined as part of the scenario definition. | Number (Float) | 2.4 |
visits_frequency_per_person | Average visits per person over the time frame in the scenario, ignoring those panel members who live in the associated block group(s) that intersect the place or that work in the place. | Number (Float) | 1.15 |
visits_unique_persons | The number of unique persons visiting all of the places part of the scenario. Equals ‘visits‘ divided by ‘visits_frequency_per_person‘. | Integer | 1532 |
visits_unique_long_trips | The number of unique long-distance trips visiting the place during time frame of the scenario. A long-distance trip is counted when a panel member is more than 50 miles from their home neighborhood. Panel members are only eligible to contribute to the estimate of unique long-distance trips if the place does not overlap with the home county of the panel member. | Integer | 71 |
passbys_travel_mode | Pass-bys by vehicular and pedestrian status during the time frame of the scenario. The determination of vehicular pass-bys and pedestrian pass-bys are determined by observed speed. The sum of all will equal ‘passbys‘. Vehicular are first, and pedestrian are second in the array. If NULL, the polygon of this place is large enough to be considered a region and is not calculated. | JSON [Integer, len = 2] | [172, 0] |
local_radius | Activities, pass-bys, dropoffs, and visits by local and non-local status during the time frame of the scenario. A local activity or pass-by is counted when the home block group of the panel member is within a 50-mile radius of the place. The radius is calculated between the observed lat/lon of the panel member and the center point of the home block group. The sum of all will equal ‘activities‘, ‘passbys‘, ‘dropoffs‘, and ‘visits‘, respectively. Local is first, and non-local is second in the array. | JSON {String: [Integer, len = 2]} | {"passbys": [75, 97], "dropoffs": [506, 246], "visits": [161, 100], "stays": [150, 111]} |
percent_visits | Percent of visits by various dimensions, including demographic segments and home locations. This will include any Motionworks segments defined in the scenario. The sum of all will generally equal 100, except in the case of rounding error. Indices against the population are included for demographic segments. For example, with the age group 0-17 having 3.1% of visits, an index of 100 indicates that 3.1% of the population of the surrounding DMA also is aged 0-17. Indices can range from 0 to infinity, where 0 occurs when there are no visits from a given segment, and infinity occurs when the segment is not present in the surrounding DMA. See the Percent Visits section for a more detailed example. | JSON {String: {String: {String: Float}}} | {"day": {...}, "segment": {...}, "home": {...}} |
Household Demographics and Privacy
All of our demographics, even if person-level, like age or gender, are estimated by considering the demographic profiles of the household unit. If we observe visits from a neighborhood characterized by households that tend to be single parents as well as multi-generational, all of this neighborhood-typical household’s ages contribute to the characterization of the estimated visit. Specifically, let’s say a neighborhood's typical household tends to have equal distributions of people in age segments 0-17, 35-44, and 75+. If we observe visits to a bar from this neighborhood, the percentage of visits by age segment at the bar would be 33.3% for each of the three age segments.
JSON Schema
All metrics reported as percentages are rounded to the nearest tenth of a percent, where 25.1 is 25.1%.
Percent Visits
Percent of visits by a variety of dimensions, including demographic segments and home locations. Some of these dimensions are mutually exclusive groups, and some of them overlap. These differences determine whether all possible categories within the groups are reported and what the sum of the percentages should equal. The bulleted list highlights these differences, and the JSON sample below demonstrates the format of the object.
The daily_dwell_bins measure the total time spent in a day by a panel member, regardless of the number of times coming and going. For example, when an individual spends 3.5 hours at work, leaves for lunch, and returns for another 4.5 hours, their daily dwell will be 8 hours.
{
"daily_dwell_bins": [
{
"id": "persons_000_030min",
"description": "Less than 30 minutes",
"value": 0.5456
},
{
"id": "persons_030_060min",
"description": "30 minutes to 59 minutes",
"value": 0.2342
},
{
"id": "persons_060_120min",
"description": "1 hour to 1 hour 59 minutes",
"value": 0.1689
},
{
"id": "persons_120_240min",
"description": "2 hours to 3 hours 59 minutes",
"value": 0.0272
},
{
"id": "persons_240_plus",
"description": "4 hours or more",
"value": 0.0241
}
],
"segments": {
"basic_demographics": [
{
"category": "age_plus",
"segments": [
{
"id": "age_00plus",
"description": "All Persons",
"value": 1.000,
"index": 1.0
},
{
"id": "age_18plus",
"description": "Population, Age 18+",
"value": 0.7862,
"index": 0.9796
},
...
]
},
{
"category": "age",
"segments": [
{
"id": "age_00t17",
"description": "Population, Age 0 - 17",
"value": 0.031,
"index": 0.3
},
{
"id": "age_18t24",
"description": "Population, Age 18 - 24",
"value": 0.052,
"index": 1022.3
},
...
]
},
...
],
...
},
"home": {
"state_province": [
{
"id": "50",
"alias": "VT",
"description": "Vermont",
"value": 0.252
},
{
"id": "33",
"alias": "NH",
"description": "New Hampshire",
"value": 0.137
},
...
],
...
}
}
Small Mutually-Exclusive Dimensions
The following dimensions have mutually exclusive groups and include a small enough set of groups that all of the groups are reported. In these cases, the sum of all of the values will generally equal 100, except in the case of rounding error.
daily_dwell_bins
segment:basic_demographics:age
See the Household Demographics and Privacy section for details on how this is estimated.segment:basic_demographics:hh_income
segment:basic_demographics:race
See the Household Demographics and Privacy section for details on how this is estimated.segment:basic_demographics:gender
See the Household Demographics and Privacy section for details on how this is estimated.segment:basic_demographics:ethnicity
See the Household Demographics and Privacy section for details on how this is estimated.segment:basic_demographics:prizm
home:state_province
Labeled by 2-digit FIPS code (including leading zeros).home:dma
Labeled by DMA identifier.
Large, Mutually-Exclusive Dimensions
The following dimensions also have mutually exclusive groups, but there are too many groups to report percentages for all the groups. In these cases, the groups representing the top 75th percentile of all visits are reported (with a minimum of 10 groups). Also, any segment with an index value greater than 1.05 is included. Accordingly, the sum of all the values will NOT equal 100, but the sum will be at least 75.
home:metro_area
Labeled by core-based statistical area (CBSA) identifier in the United States.home:county
Labeled by 5-digit county FIPS code (including leading zeros).home:postal_code
Labeled by 5-digit postal code.home:census_neighborhood
Labeled by block group's 12-digit FIPS code (including leading zeros) in the United States and by dissemination area's 8-digit identifier in Canada.
Overlapping Dimensions
The following dimensions have overlapping groups.
segment:basic_demographics:age_plus
segment:consumer:alcohol
segment:consumer:automotive
segment:consumer:commuting_and_transportation
segment:consumer:digital_video_displays
segment:consumer:environment
segment:consumer:financial
segment:consumer:food_and_beverages
segment:consumer:health
segment:consumer:items_in_the_home
segment:consumer:mri_apparel_and_jewelry
segment:consumer:mri_home_improvements
segment:consumer:mri_psychographics
segment:consumer:restaurants
segment:consumer:retail_shopping
segment:consumer:sports_and_leisure
segment:consumer:telecommunications
segment:consumer:travel
segment:consumer:voting
Updated 9 months ago