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. New accounts start with 25 free credits.

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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