IoT-Driven Campaign Adjustment Logs

This dataset logs real-time adjustments to digital marketing campaigns triggered by IoT sensor data, including details on the sensor event, campaign parameters changed, AI/ML decision context, and operator actions. It enables marketers and data scientists to analyze, automate, and optimize campaign responsiveness to live audience interactions, driving digital transformation in marketing operations.

  • last updated 4 Jan 2026
  • by GoMask
The brief that made it

Real-time campaign optimization and automation

Sample rows

preview · 8 of 65 rows · all 17 columns
adjustment_idstringadjusted_parameterstringpre_adjustment_valuefloatoperator_idstringcampaign_idstringcampaign_namestringadjustment_timestampdatetimesensor_idstringsensor_typestringsensor_locationstringtrigger_eventstringpost_adjustment_valuefloatadjustment_typestringai_decision_scorefloatai_model_versionstringaudience_segmentstringadjustment_reasonstring
ADJ-100001bid0.85OP-0031CMP-32455Spring Sale 20242024-03-05T09:12:15ZSEN-7821motionStore #14 Entrancecustomer_present1increase0.91v3.4.1new_visitorsIncreased bid due to high influx of new customers detected.
ADJ-100002budget1500OP-0031CMP-32455Spring Sale 20242024-03-05T09:14:50ZSEN-7822cameraAisle #7high_traffic1800increase0.74v3.4.1mobile_usersBudget increased to accommodate spike in mobile users.
ADJ-100003bid0.65OP-0092CMP-52112Summer Gear Promo2024-03-07T10:07:21ZSEN-9120temperatureStore #22 Maintemperature_above_threshold0.55decrease0.67v3.3.8loyal_customersBid decreased due to reduced interest in summer gear.
ADJ-100004ad_frequency3OP-0092CMP-52112Summer Gear Promo2024-03-07T10:19:45ZSEN-9121beaconStore #22 Checkoutcustomer_present4increase0.82v3.3.8desktop_usersAd frequency increased to target desktop users at checkout.
ADJ-100005ad_frequency2OP-0018CMP-00478Weekend Flash Deals2024-03-09T11:02:30ZSEN-6700motionStore #5 Entrancecustomer_present1decrease0.59v2.8.5returning_visitorsReduced ad frequency due to repeated exposure to same users.
ADJ-100006budget500OP-0018CMP-00478Weekend Flash Deals2024-03-09T11:10:13ZSEN-6701cameraStore #5 Exitlow_footfall350decrease0.84v2.8.5loyal_customersBudget decreased to optimize spend during low traffic.
ADJ-100007bid1.2OP-0025CMP-87522New Arrivals Showcase2024-03-10T13:17:02ZSEN-2328beaconWebsite Headerhigh_traffic1.5increase0.94v4.0.2new_visitorsBid increased based on high web traffic from new users.
ADJ-100008ad_frequency2.5OP-0025CMP-87522New Arrivals Showcase2024-03-10T13:22:20ZSEN-2329motionStore #8 Entrancecustomer_present3increase0.78v4.0.2mobile_usersFrequency increased for mobile segment during peak hours.

What the 65 rows show

from the 65-row sample

Budget (adjusted parameter) stands out: mean pre_adjustment_value is 737.5, against 1.9 for the rest.

  • 2.1median pre_adjustment_value
  • 3adjustment types
  • 4sensor types
  • 6trigger events
  • 11audience segments
  • 12ai model versions
Mean pre_adjustment_value by adjusted_parameter50 rows
04008001.4bid24 rows2.8ad_frequency14 rows737.5budget12 rows
pre_adjustment_value50 rows, in bands of 200
0204038243001208001,600pre_adjustment_value →

Median 2.1, from 0.55 to 1,600.

operator_id48 rows with a value · 17 left blank
  1. OP-01458
  2. OP-00317
  3. OP-00187
  4. OP-00926
  5. OP-00256
  6. OP-03194
  7. OP-02313
  8. OP-01123
  9. OP-03362
  10. OP-03241
17 columns by typefrom the column list below
  • string 13
  • float 3
  • datetime 1

Columns

17 columns in three groups
blueprint · 17 columns
columntypedescriptionexample
Text 13 columns
adjustment_idstringUnique identifier for each campaign adjustment event.uniqueADJ-100001
campaign_idstringIdentifier for the digital marketing campaign being adjusted.CMP-32455
campaign_namestringHuman-readable name of the marketing campaign.Spring Sale 2024
sensor_idstringUnique identifier for the IoT sensor that triggered the adjustment.SEN-7821
sensor_typestringType of IoT sensor (e.g., motion, temperature, beacon, camera).4 typesmotion
sensor_locationstringPhysical or logical location of the sensor (e.g., 'Store #12 Entrance', 'Website Banner').optionalStore #14 Entrance
trigger_eventstringDescription or type of event detected by the sensor that triggered the adjustment (e.g., 'customer_present', 'high_traffic', 'temperature_above_threshold').6 eventscustomer_present
adjusted_parameterstringName of the campaign parameter that was adjusted (e.g., 'bid', 'budget', 'ad_frequency', 'target_audience').3 parametersbid
adjustment_typestringType of adjustment performed (e.g., 'increase', 'decrease', 'pause', 'resume', 'targeting_change').6 valuesincrease
ai_model_versionstringVersion identifier for the AI/ML model used to make the adjustment decision.12 versions · optionalv3.4.1
audience_segmentstringTarget audience segment affected by the adjustment (e.g., 'new_visitors', 'loyal_customers', 'mobile_users').11 segments · optionalnew_visitors
adjustment_reasonstringDetailed explanation or rationale for the adjustment, as provided by the AI/ML system or operator.optionalBar crowd spike.
operator_idstringIdentifier for the human operator or system that approved or executed the adjustment (if applicable).11 operators · optionalOP-0031
Numbers 3 columns
pre_adjustment_valuefloatValue of the adjusted campaign parameter before the change (e.g., previous bid, budget, or display frequency).optional0.85
post_adjustment_valuefloatValue of the adjusted campaign parameter after the change.1
ai_decision_scorefloatConfidence score or probability (0-1) from the AI/ML model that recommended the adjustment.0 to 1 · optional0.91
Dates and times 1 column
adjustment_timestampdatetimeTimestamp when the campaign adjustment was made.2024-03-05T09:12:15Z

Use it for

  • median pre adj…2.150 rowsmean pre adjustment v…1.4bid2.8ad_fre…737.5budget

    A marketing dashboard

    Pre_adjustment_value by adjusted_parameter and a breakdown of operator_id. Excel, Power BI or Tableau.

  • Why do the 12 budget rows have a mean pre_adjustment_value of 737.5?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable adjustments with campaign_id, campaign_name and adjustment_timestamp to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 17 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

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This dataset65 rows17 columns
Yours1,000 rows17 columnssensor_location: UK only

blueprint · iot-driven-campaign-adjustment-logs

Behind this dataset

Same schema. As many rows as you need.

These 65 rows came out of a blueprint — 17 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each row records a unique campaign adjustment event linked to an IoT sensor trigger.
  • Include sensor type, adjustment type, previous and new campaign parameters.
  • Log timestamp, campaign ID, and adjustment outcome metrics.
  • Capture audience segment influenced and resulting performance uplift.
  • Exclude adjustments unrelated to real-time sensor data.
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
iot-driven-campaign-adjustment-logs

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