{
  "format": "dataset-manifest/1",
  "slug": "email-campaign-engagement",
  "version": 3,
  "seed": "email-campaign-engagement:1",
  "spec": {
    "format": "dataset/1",
    "slug": "email-campaign-engagement",
    "name": "Email Campaign Engagement",
    "tagline": "Email marketing metrics including audiences, campaigns, sends, engagement events, and unsubscribes.",
    "description": "Email marketing teams craft engaging campaigns to connect with their audiences and drive action. They segment target audiences based on demographics and behaviors to maximize engagement. Each campaign is carefully designed with specific goals, and once launched, emails are sent to the identified audiences, initiating a series of measurable interactions. These interactions are captured through various engagement events, including opens, clicks, and unsubscribes, allowing marketers to analyze the effectiveness of their strategies in real-time.\n\nIn this dataset, the 'audiences' table contains information about different segments of recipients, detailing their preferences and characteristics. Each audience is linked to multiple 'campaigns', which outline the specific emails sent out. The 'sends' table records each email sent, associated with a specific campaign and audience, including timestamps for accurate tracking. The 'engagement_events' capture the actions taken by recipients after receiving the emails, providing insights into how effectively the campaigns resonate with the intended audience. Lastly, the 'unsubscribes' table logs instances where recipients choose to opt-out, offering crucial feedback on audience satisfaction and campaign relevance.\n\nThe relationships among these tables allow marketers to answer vital questions, such as: Which audience segments engage the most? What type of content leads to higher click-through rates? How do engagement rates differ across various campaigns? This data is excellent for practicing skills related to data analysis, marketing strategy evaluation, and understanding customer behavior in a digital marketing context. \n\nKeep in mind, this data is synthetic, designed to mimic real-world scenarios while providing a safe and practical environment for developers to hone their skills.",
    "domain": "marketing",
    "shape": "event-log",
    "useCases": [
      "analytics-demo",
      "bi-dashboards"
    ],
    "keywords": [
      "email marketing",
      "campaigns",
      "engagement",
      "analytics",
      "unsubscribes",
      "sends",
      "audiences"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "audiences": {
        "description": "This table contains information about the audiences targeted in email campaigns. Each audience has a unique identifier and descriptive attributes.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each audience."
          },
          "name": {
            "kind": "words",
            "max": 3,
            "description": "The name of the audience.",
            "pool": [
              "marketers",
              "students",
              "professionals",
              "parents",
              "retirees",
              "techies",
              "gamers",
              "travelers",
              "foodies",
              "athletes",
              "creatives",
              "entrepreneurs",
              "educators",
              "investors",
              "healthcare",
              "petowners",
              "fashionistas",
              "environmentalists",
              "hobbyists",
              "seniors"
            ],
            "min": 1
          },
          "description": {
            "kind": "sentence",
            "max": 50,
            "description": "A brief description of the audience."
          }
        }
      },
      "campaigns": {
        "description": "This table holds details about the email campaigns created. Each campaign is linked to a specific audience.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each campaign."
          },
          "audience_id": {
            "kind": "fk",
            "ref": "audiences.id",
            "description": "The audience targeted by the campaign."
          },
          "title": {
            "kind": "words",
            "max": 3,
            "description": "Title of the email campaign.",
            "pool": [
              "launch",
              "update",
              "newsletter",
              "promotion",
              "event",
              "webinar",
              "offer",
              "survey",
              "announcement",
              "guide",
              "strategy",
              "tips",
              "trends",
              "insights",
              "case",
              "study",
              "report",
              "feedback",
              "invitation",
              "reminder",
              "welcome"
            ],
            "min": 1
          },
          "created_at": {
            "kind": "datetime",
            "from": "2022-01-01",
            "to": "2023-01-01",
            "description": "The date and time when the campaign was created.",
            "dayProfile": "business"
          }
        }
      },
      "sends": {
        "description": "This table records the instances when emails are sent out as part of a campaign. Each send is linked to a specific campaign.",
        "rows": 500,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each send event."
          },
          "campaign_id": {
            "kind": "fk",
            "ref": "campaigns.id",
            "description": "The campaign associated with this send."
          },
          "sent_at": {
            "kind": "datetime",
            "from": "2022-01-01",
            "to": "2023-01-01",
            "description": "The date and time when the email was sent.",
            "dayProfile": "waking"
          }
        }
      },
      "engagement_events": {
        "description": "This table captures user engagement events resulting from email sends, such as opens and clicks. Each event is linked to the specific send.",
        "rows": 1000,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each engagement event."
          },
          "send_id": {
            "kind": "fk",
            "ref": "sends.id",
            "description": "The send associated with this engagement event."
          },
          "event_type": {
            "kind": "enum",
            "values": [
              "open",
              "click"
            ],
            "description": "Type of engagement event.",
            "weights": [
              7,
              3
            ]
          },
          "event_at": {
            "kind": "datetime",
            "after": "send_id.sent_at",
            "withinDays": 30,
            "description": "The date and time when the engagement event occurred."
          }
        }
      },
      "unsubscribes": {
        "description": "This table records instances of users unsubscribing from campaigns. Each unsubscribe is linked to a specific send.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each unsubscribe event."
          },
          "send_id": {
            "kind": "fk",
            "ref": "sends.id",
            "description": "The send associated with this unsubscribe event."
          },
          "unsubscribed_at": {
            "kind": "datetime",
            "after": "send_id.sent_at",
            "withinDays": 30,
            "description": "The date and time when the unsubscribe occurred."
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "timestamped",
      "categorical",
      "nullable"
    ],
    "analysisQuestions": [
      "What is the average open rate for different campaigns?",
      "How quickly do users engage with emails after they are sent?",
      "What percentage of recipients unsubscribe after receiving a campaign?",
      "Which audience segments respond better to specific campaign types?",
      "How do engagement metrics vary across different times of the year?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Campaigns and Sends",
        "sql": "SELECT c.title, s.sent_at FROM campaigns c JOIN sends s ON c.id = s.campaign_id;",
        "dialect": "postgres"
      },
      {
        "title": "Count Engagement Events by Type",
        "sql": "SELECT event_type, COUNT(*) FROM engagement_events GROUP BY event_type;",
        "dialect": "postgres"
      },
      {
        "title": "Average Unsubscribes per Campaign",
        "sql": "SELECT c.title, COUNT(u.id) AS unsubscribe_count FROM campaigns c LEFT JOIN unsubscribes u ON u.send_id IN (SELECT id FROM sends WHERE campaign_id = c.id) GROUP BY c.id;",
        "dialect": "postgres"
      },
      {
        "title": "Engagement Over Time",
        "sql": "SELECT DATE(event_at) AS engagement_date, COUNT(*) FROM engagement_events GROUP BY engagement_date ORDER BY engagement_date;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Marketing Analyst",
        "body": "A marketing analyst can utilize this dataset to evaluate the effectiveness of various email campaigns over time. By analyzing open and click rates, they can identify trends and patterns that inform future campaign strategies."
      },
      {
        "title": "Data Scientist",
        "body": "A data scientist might use this dataset to build predictive models around user engagement. By examining the timing and type of engagement events, they can create algorithms that predict future user behavior based on historical data."
      },
      {
        "title": "Business Intelligence Developer",
        "body": "A BI developer can integrate this dataset into a dashboard, providing stakeholders with real-time insights into campaign performance. Visualizations can highlight key metrics such as engagement rates and unsubscribe counts, supporting data-driven decision-making."
      }
    ]
  },
  "counts": {
    "audiences": 200,
    "campaigns": 150,
    "sends": 500,
    "engagement_events": 1000,
    "unsubscribes": 200
  },
  "stats": {
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      "columns": {
        "id": {
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        "description": {
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        "title": {
          "nulls": 0,
          "distinct": 113
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        "created_at": {
          "nulls": 0,
          "distinct": 150,
          "min": "2022-01-15 17:12:46",
          "max": "2023-01-01 10:17:18"
        }
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          "min": "2022-01-01 13:46:07",
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          "max": "2023-01-28 12:59:56"
        }
      }
    }
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