{
  "format": "dataset-manifest/1",
  "slug": "ad-spend-and-conversions",
  "version": 1,
  "seed": "ad-spend-and-conversions:1",
  "spec": {
    "format": "dataset/1",
    "slug": "ad-spend-and-conversions",
    "name": "Ad Spend and Conversions",
    "tagline": "Ad spend, campaign details, channels, ad groups, daily impressions, and conversions for paid advertising analysis.",
    "description": "Paid advertising campaigns leverage various channels to drive traffic and conversions. This dataset provides a comprehensive view of ad spend across multiple channels, campaigns, and ad groups, capturing daily spending, impressions, and conversion data. Each table in this dataset models a specific aspect of advertising performance, allowing analysts to explore the relationship between expenditure and effectiveness in driving user actions. By analyzing this data, marketers can answer critical questions about return on ad spend, optimize budgeting across channels, and assess the performance of specific campaigns and ad groups. The dataset is synthetic and designed for practice and testing purposes, ideal for SQL queries and ETL pipeline development.",
    "domain": "marketing",
    "shape": "transactional",
    "useCases": [
      "sql-practice",
      "etl-pipelines"
    ],
    "keywords": [
      "advertising",
      "spend",
      "conversions",
      "campaigns",
      "analytics",
      "marketing"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "channels": {
        "description": "This table lists the various advertising channels, linking to campaigns that utilize them. Each channel has a unique identifier.",
        "rows": 10,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the advertising channel."
          },
          "name": {
            "kind": "fullName",
            "description": "Name of the advertising channel, e.g., Google Ads, Facebook.",
            "nullable": true
          }
        }
      },
      "campaigns": {
        "description": "This table contains campaigns linked to channels, representing distinct marketing initiatives. Each campaign has a unique identifier.",
        "rows": 20,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the campaign."
          },
          "channel_id": {
            "kind": "fk",
            "ref": "channels.id",
            "description": "References the channel to which this campaign belongs."
          },
          "name": {
            "kind": "fullName",
            "description": "Name of the campaign.",
            "nullable": true
          }
        }
      },
      "ad_groups": {
        "description": "This table outlines the ad groups associated with campaigns, providing structure to how ads are grouped for marketing efforts.",
        "rows": 30,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the ad group."
          },
          "campaign_id": {
            "kind": "fk",
            "ref": "campaigns.id",
            "description": "References the campaign this ad group belongs to."
          },
          "name": {
            "kind": "fullName",
            "description": "Name of the ad group.",
            "nullable": true
          }
        }
      },
      "daily_spend": {
        "description": "This table records daily spending for each ad group, providing a detailed view of advertising expenditure over time.",
        "rows": 120,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the daily spend record."
          },
          "ad_group_id": {
            "kind": "fk",
            "ref": "ad_groups.id",
            "description": "References the ad group for which this spend is recorded."
          },
          "date": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date of the recorded spend.",
            "trend": "growing"
          },
          "spend": {
            "kind": "decimal",
            "min": 10,
            "max": 500,
            "scale": 2,
            "description": "Amount spent on this date, in dollars.",
            "nullable": true
          },
          "impressions": {
            "kind": "int",
            "min": 100,
            "max": 10000,
            "description": "Number of impressions generated on this date.",
            "nullable": true
          }
        }
      },
      "conversions": {
        "description": "This table captures conversion data attributed to ad groups, linking back to daily spend records for performance analysis.",
        "rows": 120,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the conversion record."
          },
          "ad_group_id": {
            "kind": "fk",
            "ref": "ad_groups.id",
            "description": "References the ad group associated with this conversion."
          },
          "date": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date of the recorded conversion.",
            "trend": "growing"
          },
          "conversions": {
            "kind": "int",
            "min": 0,
            "max": 100,
            "description": "Number of conversions attributed to the ad group on this date.",
            "nullable": true
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "monetary",
      "timestamped",
      "nullable"
    ],
    "analysisQuestions": [
      "What is the return on ad spend for each campaign?",
      "Which ad groups are generating the most conversions?",
      "How does daily spend impact the number of impressions?",
      "What trends can be observed in conversion rates over time?",
      "Which channels yield the highest conversion rates?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Daily Spend and Conversions by Ad Group",
        "sql": "SELECT ds.date, ds.spend, c.conversions FROM daily_spend ds JOIN conversions c ON ds.ad_group_id = c.ad_group_id WHERE ds.date = c.date;",
        "dialect": "postgres"
      },
      {
        "title": "Total Spend and Conversions by Campaign",
        "sql": "SELECT ca.name, SUM(ds.spend) AS total_spend, SUM(c.conversions) AS total_conversions FROM campaigns ca JOIN ad_groups ag ON ca.id = ag.campaign_id JOIN daily_spend ds ON ag.id = ds.ad_group_id JOIN conversions c ON ag.id = c.ad_group_id GROUP BY ca.name;",
        "dialect": "postgres"
      },
      {
        "title": "Daily Spend Trends",
        "sql": "SELECT date, SUM(spend) AS daily_total FROM daily_spend GROUP BY date ORDER BY date;",
        "dialect": "postgres"
      },
      {
        "title": "Average Conversion Rate by Ad Group",
        "sql": "SELECT ag.name, AVG(c.conversions::decimal / ds.impressions) AS conversion_rate FROM ad_groups ag JOIN daily_spend ds ON ag.id = ds.ad_group_id JOIN conversions c ON ag.id = c.ad_group_id GROUP BY ag.name;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Marketing Analysts",
        "body": "Marketing analysts would utilize this dataset to assess the effectiveness of various advertising campaigns. By examining the relationship between ad spend and conversion rates, they can identify which campaigns are yielding the best return on investment and optimize future marketing strategies accordingly."
      },
      {
        "title": "Data Engineers",
        "body": "Data engineers tasked with building ETL pipelines can leverage this dataset to integrate advertising performance data into larger marketing analytics platforms. They can create workflows that aggregate daily spend and conversion metrics for reporting and analysis."
      },
      {
        "title": "Business Intelligence Professionals",
        "body": "Business intelligence professionals can use this dataset to create dashboards that visualize ad performance metrics. By analyzing trends in spending and conversions, they can provide insights to stakeholders regarding the effectiveness of different channels and campaigns."
      }
    ]
  },
  "counts": {
    "channels": 10,
    "campaigns": 20,
    "ad_groups": 30,
    "conversions": 120,
    "daily_spend": 120
  },
  "stats": {
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          "min": "Anna Klein",
          "max": "Zoe Miller"
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