Set Dynamics returns detailed reach and frequency results for each scenario, providing comprehensive metrics for campaign planning and analysis. Results are delivered as JSON objects containing scenario metadata and performance metrics.

Response Structure

Each response contains customer information, cohort details, and reach metrics across multiple frequency thresholds and duration periods.

{
  "customer": {
    "customer_id": 30,
    "customer_name": "Motionworks",
    "customer_scenario_id": "686d59e67e25e60012b986cb",
    "customer_scenario_name": "Albany NY panels",
    "customer_scenario_info": "{\"customer_name\":\"test_name\",\"customer_email\":\"[email protected]\"}"
  },
  "cohort": {
    "customer_segment_id": 2035,
    "customer_base_segment_id": 9330,
    "geography_ids": ["US2020XDMA532"]
  },
  "effective_reach_per_duration": [
    {
      "duration": "28",
      "effective_freq_list": [
        {"effective_freq": "1", "lts_reach": 0.38148},
        {"effective_freq": "2", "lts_reach": 0.30715},
        {"effective_freq": "3", "lts_reach": 0.25684},
        {"effective_freq": "4", "lts_reach": 0.22148},
        {"effective_freq": "5", "lts_reach": 0.19922},
        {"effective_freq": "6", "lts_reach": 0.1845},
        {"effective_freq": "7", "lts_reach": 0.16959},
        {"effective_freq": "8", "lts_reach": 0.15534},
        {"effective_freq": "9", "lts_reach": 0.14473},
        {"effective_freq": "10", "lts_reach": 0.13538},
        {"effective_freq": "11", "lts_reach": 0.12776},
        {"effective_freq": "20", "lts_reach": 0.07511},
        {"effective_freq": "50", "lts_reach": 0.02026},
        {"effective_freq": "100", "lts_reach": 0.00074}
      ]
    }
  ],
  "debug": {
    "qa_flag": "ideal",
    "devices_panel": 224.17,
    "lts_ots_disorder": false,
    "per_duration": [
      {
        "duration": "28",
        "unique_people": 137773.59,
        "total_exposures": 795053.09,
        "target_devices_routed": 37.14,
        "device_events": 220.1,
        "days_with_obs": "39",
        "pct_days_with_obs": 144.44,
        "num_observed_devices": "34",
        "total_observed_passes": "136",
        "qa_flag": "ideal"
      }
    ]
  },
  "messages": "Success"
}

Schema

Name	Description	Type	Example
customer. customer_id	Motionworks customer identification number (echoed from request)	integer	30
customer. customer_name	Customer organization name (echoed from request)	string	Motionworks
customer. customer_scenario_id	Unique identifier for the scenario (echoed from request)	string	686d59e67e25e60012b986cb
customer. customer_scenario_name	Human-readable scenario name (echoed from request)	string	Albany NY panels
customer. customer_scenario_info	Additional scenario information, often containing customer contact details as JSON string (echoed from request)	string	{"customer_name":"test_name","customer_email":"[email protected]"}
cohort. customer_segment_id	Consumer demographic segment used for analysis (echoed from request)	integer	2035
cohort. customer_base_segment_id	Base age segment used for analysis (echoed from request)	integer	9330
cohort. geography_ids	Array of geographic markets included in the analysis (echoed from request)	array of strings	["US2020XDMA532"]
effective_reach_per_duration	Array of reach and frequency results organized by analysis duration. Contains one object for each requested duration period	array of objects	[{"duration":"28","effective_freq_list":[...]}]
effective_reach_per_duration[]. duration	Analysis duration in days for this set of results	string	28
effective_reach_per_duration[]. effective_freq_list	Array of reach percentages for each effective frequency threshold	array of objects	[{"effective_freq":"1","lts_reach":0.38148}]
effective_reach_per_duration[]. effective_freq_list[]. effective_freq	Frequency threshold (minimum number of exposures)	string	1, 2, 10, 50, 100
effective_reach_per_duration[]. effective_freq_list[]. lts_reach	Percentage of target population reached at or above this frequency threshold. Values are decimal representations (e.g., 0.38148 = 38.148%)	float	0.38148
debug	Diagnostic detail behind the results. Provided for QA and support; not intended for planning use.	object	See below
debug. qa_flag	Scenario-level quality tier summarized across durations: ideal, good, or bad.	string	ideal
debug. devices_panel	Panel devices associated with the target population for this scenario.	float	224.17
debug. lts_ots_disorder	True when likely-to-see reach exceeded opportunity-to-see reach, which indicates an unreliable scenario.	boolean	false
debug. per_duration	Array of per-duration diagnostics, one object per analysis duration. Each object carries its own duration, so match on that rather than on position.	array of objects	[{"duration":"28", ...}]
debug.per_duration[]. duration	Analysis duration in days that this set of diagnostics describes. Diagnostics may cover intermediate durations that do not appear in effective_reach_per_duration.	string	28
debug.per_duration[]. unique_people	Estimated people reached at least once during the duration.	float	137773.59
debug.per_duration[]. total_exposures	Estimated exposures during the duration (people reached x frequency).	float	795053.09
debug.per_duration[]. target_devices_routed	Devices with routes used in this scenario, before population weighting.	float	37.14
debug.per_duration[]. device_events	Device-level exposures before population weighting (devices x frequency).	float	220.1
debug.per_duration[]. days_with_obs	Days on which at least one pass was observed.	string	39
debug.per_duration[]. pct_days_with_obs	Days with observations as a percentage of the scenario period span. Values can exceed 100 because observed days span a wider window.	float	144.44
debug.per_duration[]. num_observed_devices	Distinct devices observed passing the spots in the set.	string	34
debug.per_duration[]. total_observed_passes	Observed passes counted across the spots in the set.	string	136
debug.per_duration[]. qa_flag	Quality tier for this duration: ideal, good, or bad. Populated even when the measures are absent.	string	ideal
debug. composition	Present on some responses. Internal detail about how the campaign was assembled, retained for support. Not intended for planning use, and its fields may change without notice.	object	{"flight_days":28, ...}
messages	Processing status message. "Success" for successful processing, error description for failures	string	Success

Multiple Durations

When multiple duration periods are requested, the effective_reach_per_duration array contains separate objects for each period:

{
  "customer": {...},
  "cohort": {...},
  "effective_reach_per_duration": [
    {
      "duration": "7",
      "effective_freq_list": [...]
    },
    {
      "duration": "14", 
      "effective_freq_list": [...]
    },
    {
      "duration": "28",
      "effective_freq_list": [...]
    }
  ],
  "debug": {
    "qa_flag": "ideal",
    "devices_panel": 224.17,
    "lts_ots_disorder": false,
    "per_duration": [
      {"duration": "7", ...},
      {"duration": "14", ...},
      {"duration": "28", ...}
    ]
  },
  "messages": "Success"
}

Campaign Flight Results

A campaign measured over a single flight returns one entry in effective_reach_per_duration, at the flight length. The diagnostics still report the shorter durations behind that result, so the two arrays differ in length. Match on the duration field rather than on position:

{
  "customer": {...},
  "cohort": {...},
  "effective_reach_per_duration": [
    {
      "duration": "28",
      "effective_freq_list": [...]
    }
  ],
  "debug": {
    "qa_flag": "ideal",
    "devices_panel": 1502.44,
    "lts_ots_disorder": false,
    "per_duration": [
      {
        "duration": "7",
        "unique_people": 758950.69,
        "total_exposures": 2157137.32,
        "target_devices_routed": 758950.69,
        "device_events": 2999,
        "days_with_obs": "7",
        "pct_days_with_obs": 100,
        "num_observed_devices": "991",
        "total_observed_passes": "2999",
        "qa_flag": "ideal"
      },
      {"duration": "14", ...},
      {"duration": "21", ...},
      {"duration": "28", ...}
    ],
    "composition": {...}
  },
  "messages": "Success"
}

Data Interpretation

Frequency Thresholds: Higher frequency thresholds represent subsets of the population. The reach value decreases as frequency requirements increase (e.g., effective_freq_1 ≥ effective_freq_10 ≥ effective_freq_50).

Effective Frequency: Each threshold shows the percentage of people who were exposed at least that many times during the analysis period.

Diagnostics (debug): The debug object carries QA detail behind the results and is intended for support and troubleshooting rather than planning. debug.per_duration holds one object per analysis duration, and each object carries its own duration.

Match diagnostics on duration, not position: Read the duration field on each per_duration object rather than assuming its position lines up with effective_reach_per_duration. The two are not always the same length. A campaign measured over a single flight returns one entry in effective_reach_per_duration while debug.per_duration still reports the shorter durations behind it, so a campaign with a 28-day flight can return one result entry and four diagnostic entries covering 7, 14, 21 and 28 days.

Missing diagnostics for a duration: When a duration produced no observations, its per_duration object is still present and still carries duration and qa_flag, but the measure fields are omitted from the JSON. Treat an absent key as "no data for that duration" rather than as zero, and skip those durations when summing or averaging.

Whole numbers arrive as strings: duration, days_with_obs, num_observed_devices and total_observed_passes are delivered as quoted strings rather than JSON numbers, matching effective_freq elsewhere in the response. Convert before doing arithmetic on them.