OpenKPIs
Leaderboard
Sign in
← Back to KPIs

Revenue per Visit

RevenueRetail, SaaS, E-commerce, Media, Technology, Other

Revenue per visit measures the average revenue generated each time a user visits the website. It is crucial for understanding the effectiveness of the website in converting visits into revenue.

Business Use Case

An e-commerce growth team monitors revenue per visit by channel and device. If paid social drives high traffic but low revenue per visit compared with email, the team can reduce spend on low-value campaigns, improve landing page relevance, or retarget higher-intent audiences.

Business Criticality

High

Journey / Navigation Area

Digital Analytics

Scope

Session

Formula

Total Revenue / Total Visits

Calculation Notes

1️⃣ Use visits as sessions, not users or pageviews. 2️⃣ Include only completed revenue events (purchases, paid conversions). 3️⃣ Exclude refunds, canceled orders, test transactions, internal traffic, bot traffic, and duplicate purchases. 4️⃣ Subtract refunds from gross revenue for net revenue per visit. 5️⃣ Ensure consistent sessionization logic across web and app data. 6️⃣ Deduplicate sessions in cross-domain implementations where identity stitching is available.

Technical Details

Measure TypeCurrency
Aggregation WindowSession, User, Hourly, Weekly, Daily, Monthly, Yearly, Quarterly

Events

PlatformEvent
Google Analytics 4purchase
Adobepurchase

Data Mappings

W3 Data Layer
{
  "event": "purchase",
  "ecommerce": {
    "transaction_id": "T12345",
    "currency": "USD",
    "value": 149.99,
    "items": [
      {
        "item_id": "SKU-001",
        "item_name": "Running Shoes",
        "price": 149.99,
        "quantity": 1
      }
    ]
  },
  "web": {
    "webPageDetails": {
      "URL": "https://www.example.com/checkout/confirmation"
    }
  }
}
GA4 Data Layer
{
  "event": "purchase",
  "ecommerce": {
    "transaction_id": "T12345",
    "currency": "USD",
    "value": 149.99,
    "tax": 12.5,
    "shipping": 0,
    "items": [
      {
        "item_id": "SKU-001",
        "item_name": "Running Shoes",
        "price": 149.99,
        "quantity": 1
      }
    ]
  }
}
Adobe Client Data Layer
{
  "event": "purchase",
  "commerce": {
    "order": {
      "purchaseID": "T12345",
      "currencyCode": "USD",
      "priceTotal": 149.99
    },
    "productListItems": [
      {
        "SKU": "SKU-001",
        "name": "Running Shoes",
        "priceTotal": 149.99,
        "quantity": 1
      }
    ]
  }
}
XDM Mapping
{
  "eventType": "commerce.purchases",
  "commerce": {
    "order": {
      "purchaseID": "T12345",
      "priceTotal": 149.99,
      "currencyCode": "USD"
    }
  },
  "productListItems": [
    {
      "SKU": "SKU-001",
      "name": "Running Shoes",
      "priceTotal": 149.99,
      "quantity": 1
    }
  ],
  "web": {
    "webPageDetails": {
      "URL": "https://www.example.com/checkout/confirmation"
    }
  }
}

SQL Queries

Google Analytics 4 (BigQuery)
WITH session_revenue AS ( SELECT user_pseudo_id, user_id, CONCAT(user_pseudo_id, '-', CAST((SELECT value.int_value FROM UNNEST(event_params) WHERE key = 'ga_session_id') AS STRING)) AS session_id, SUM(COALESCE((SELECT SUM(CAST(item.revenue AS FLOAT64)) FROM UNNEST(items) AS item), 0)) AS revenue FROM `project.dataset.events_*` WHERE event_name = 'purchase' GROUP BY 1, 2 ), sessions AS ( SELECT DISTINCT user_pseudo_id, user_id, CONCAT(user_pseudo_id, '-', CAST((SELECT value.int_value FROM UNNEST(event_params) WHERE key = 'ga_session_id') AS STRING)) AS session_id FROM `project.dataset.events_*` WHERE (SELECT value.int_value FROM UNNEST(event_params) WHERE key = 'ga_session_id') IS NOT NULL ) SELECT SAFE_DIVIDE(SUM(COALESCE(sr.revenue, 0)), COUNT(DISTINCT s.session_id)) AS revenue_per_visit FROM sessions s LEFT JOIN session_revenue sr ON s.session_id = sr.session_id;
Adobe Experience Platform (AEP Query Service)
WITH session_revenue AS ( SELECT identityMap.ECID[0].id AS mcid, session_id, SUM(COALESCE(commerce.purchases.value, 0)) AS revenue FROM dataset.events WHERE eventType = 'commerce.purchases' GROUP BY 1, 2 ), sessions AS ( SELECT DISTINCT identityMap.ECID[0].id AS mcid, session_id FROM dataset.events WHERE session_id IS NOT NULL ) SELECT COALESCE(SUM(sr.revenue), 0) / NULLIF(COUNT(DISTINCT s.session_id), 0) AS revenue_per_visit FROM sessions s LEFT JOIN session_revenue sr ON s.session_id = sr.session_id;

Source Data

Digital Analytics, Business Intelligence, ERP

Dependencies

Prerequisite: List the dependencies required for this KPI

Events:

purchase

Metrics:

revenuesessions/visitscurrency code

Report Attributes

Dimensions: Default channel group, Source/Medium, Campaign, Device category, Landing page, Country, New vs Returning Metrics: Revenue, Sessions, Transactions, Conversion rate, Average order value, Revenue per visit

Recommended Reporting Views

Views
Executive KPI DashboardE-commerce PerformanceTraffic AnalysisChannel PerformanceConversion Optimization

Segment Eligibility

True

Governance

Data SensitivityInternal

Governance

Created byswapnamagantius
Created on5/23/2026
Last modified bydevyendarm
Last modified on5/31/2026
StatusPUBLISHED

GitHub

View related Pull Requestcatalog/kpis/revenue-per-visit.yml

Community Discussion