# Data Overview

Google Analytics 4 in Coupler.io gives you access to a single, flexible report type that you customize with your choice of metrics and dimensions. Unlike some sources with fixed report types, GA4 lets you build exactly the report you need by selecting what to measure (metrics) and how to break it down (dimensions).

## What data is available?

When you connect GA4, you're pulling data from one or more **GA4 properties**. Each property tracks a website or app. Your report is shaped by three things:

* **Metrics** — The numbers you want to measure (e.g., page views, sessions, users, revenue)
* **Dimensions** — How you want to slice the data (e.g., by date, country, traffic source, page path)
* **Date range** — The time period to cover

{% hint style="info" %}
You can select up to **10 metrics** and **9 dimensions** per data flow. This is a GA4 API limitation, not a Coupler.io restriction. If you need more than 10 metrics, see the [workaround using multiple sources and joins](https://help.coupler.io/article/546-overcome-ga4-limit-for-10-metrics-in-a-single-report).
{% endhint %}

## When to use it

* You need website or app traffic data in a spreadsheet or BI tool
* You want to track user behavior trends over time
* You need to combine GA4 data with ad spend or CRM data in a single destination
* You want to build custom reports that go beyond what the GA4 interface allows

## Available metrics

GA4 offers a wide range of metrics. Here are the most commonly used ones, organized by category. The full list is loaded dynamically from the GA4 API based on your property — you can select exactly the columns you need when configuring your data source in Coupler.io.

{% hint style="warning" %}
Not all metrics are compatible with all dimensions. If you select an incompatible combination, GA4 returns an error like `The request's dimensions & metrics are incompatible`. Use the [GA4 Dimensions & Metrics Explorer](https://ga-dev-tools.web.app/ga4/dimensions-metrics-explorer/) to check compatibility before configuring your data flow.
{% endhint %}

#### Traffic & Engagement

| Metric                       | Description                                                       |
| ---------------------------- | ----------------------------------------------------------------- |
| **Views**                    | Total page views (or screen views for apps)                       |
| **Sessions**                 | Number of sessions started                                        |
| **Total users**              | Total number of unique users                                      |
| **New users**                | Users who visited for the first time                              |
| **Active users**             | Users who had an engaged session                                  |
| **Bounce rate**              | Percentage of sessions that were not engaged                      |
| **Engagement rate**          | Percentage of sessions that were engaged (inverse of bounce rate) |
| **Average session duration** | Average length of a session in seconds                            |
| **Views per session**        | Average number of pages viewed per session                        |
| **Sessions per user**        | Average number of sessions per user                               |
| **Event count**              | Total number of events triggered                                  |
| **Key events**               | Total number of key events (formerly conversions)                 |

#### E-commerce

| Metric                       | Description                                                      |
| ---------------------------- | ---------------------------------------------------------------- |
| **Purchase revenue**         | Total revenue from purchases                                     |
| **Total revenue**            | Total revenue including purchases, subscriptions, and ad revenue |
| **Ecommerce purchases**      | Number of completed purchases                                    |
| **Add-to-carts**             | Number of add-to-cart events                                     |
| **Checkouts**                | Number of checkout events                                        |
| **Item revenue**             | Revenue from individual items                                    |
| **Transactions**             | Number of transactions                                           |
| **Average purchase revenue** | Average revenue per purchase                                     |

#### Advertising

| Metric                 | Description                            |
| ---------------------- | -------------------------------------- |
| **Ads cost**           | Cost of linked advertising campaigns   |
| **Ads clicks**         | Clicks from linked ad campaigns        |
| **Ads impressions**    | Impressions from linked ad campaigns   |
| **Return on ad spend** | Revenue generated per unit of ad spend |
| **Cost per key event** | Ad cost per key event                  |

## Available dimensions

Dimensions let you break your data down by specific attributes. Here are the most commonly used categories.

#### Time

| Dimension             | What it shows                      |
| --------------------- | ---------------------------------- |
| **Date**              | Daily breakdown (YYYYMMDD)         |
| **Date + hour**       | Hourly breakdown                   |
| **Day of week**       | Which day of the week (0 = Sunday) |
| **Month, Week, Year** | Broader time periods               |

#### Traffic Source

| Dimension                   | What it shows                                                        |
| --------------------------- | -------------------------------------------------------------------- |
| **Session source**          | Where the session originated (e.g., google, facebook)                |
| **Session medium**          | The marketing medium (e.g., organic, cpc, referral)                  |
| **Session source / medium** | Combined source and medium                                           |
| **Session campaign**        | The campaign name from UTM parameters                                |
| **Default channel group**   | Google's auto-classified channel (Organic Search, Paid Search, etc.) |

#### Geography & Technology

| Dimension                 | What it shows                           |
| ------------------------- | --------------------------------------- |
| **Country, City, Region** | User location                           |
| **Device category**       | Desktop, mobile, or tablet              |
| **Browser**               | User's browser (Chrome, Safari, etc.)   |
| **Operating system**      | User's OS (Windows, iOS, Android, etc.) |

#### Content

| Dimension        | What it shows                   |
| ---------------- | ------------------------------- |
| **Page path**    | The URL path of the page viewed |
| **Page title**   | The title of the page viewed    |
| **Landing page** | The first page of the session   |
| **Hostname**     | The domain name                 |

#### E-commerce

| Dimension               | What it shows                 |
| ----------------------- | ----------------------------- |
| **Item name, Item ID**  | Product identifiers           |
| **Item category** (1–5) | Product category hierarchy    |
| **Item brand**          | Product brand                 |
| **Transaction ID**      | Unique transaction identifier |

## Common metric combinations

Here are some useful combinations depending on what you're tracking:

* **Website traffic overview** — Views, Sessions, Total users, New users, Bounce rate + Date dimension
* **Traffic source analysis** — Sessions, Total users, Key events, Engagement rate + Session source / medium dimension
* **Content performance** — Views, Average session duration, Engagement rate + Page path or Page title dimension
* **Geographic analysis** — Sessions, Total users, Key events + Country or City dimension
* **E-commerce performance** — Purchase revenue, Ecommerce purchases, Add-to-carts, Average purchase revenue + Date or Item name dimension
* **Campaign analysis** — Sessions, Key events, Ads cost, Return on ad spend + Session campaign dimension

## Use cases by role

#### Marketers

Track which channels and campaigns drive the most traffic and conversions. Combine GA4 data with ad spend from Google Ads or Facebook Ads to calculate true ROI across channels.

**Recommended metrics:** Sessions, Key events, Engagement rate, Total users

**Recommended dimensions:** Session source / medium, Session campaign, Default channel group

#### Content Teams

Identify top-performing pages, monitor engagement metrics by landing page, and track how content drives key events over time.

**Recommended metrics:** Views, Average session duration, Engagement rate, Key events

**Recommended dimensions:** Page path, Page title, Landing page, Date

#### E-commerce Managers

Analyze the full purchase funnel from product views to transactions. Break down revenue by product category, traffic source, or device to optimize the shopping experience.

**Recommended metrics:** Purchase revenue, Ecommerce purchases, Add-to-carts, Average purchase revenue

**Recommended dimensions:** Item name, Item category, Session source / medium, Device category

#### Business Owners

Get high-level dashboards showing total users, sessions, and revenue trends without needing to navigate the GA4 interface.

**Recommended metrics:** Total users, Sessions, Purchase revenue, Key events

**Recommended dimensions:** Date, Default channel group

## Platform-specific notes

* **10-metric / 9-dimension limits** — GA4 restricts reports to 10 metrics and 9 dimensions per request. If you need more metrics, create multiple data flows with different metric sets and combine them using a [data join](https://help.coupler.io/article/546-overcome-ga4-limit-for-10-metrics-in-a-single-report).
* **Dimension–metric compatibility** — Not all dimension–metric pairs work together. For example, combining `Referrer` with `Ads clicks` triggers a `400 incompatible` error. Always verify your combination using the [GA4 Dimensions & Metrics Explorer](https://ga-dev-tools.web.app/ga4/dimensions-metrics-explorer/) before setting up your flow.
* **Users are not summable** — `Total users` broken down by a dimension (e.g., Default channel group) will not sum up to the overall total. A single user can appear in multiple channel groups across different sessions. This is normal GA4 behavior, not a data issue.
* **Data freshness** — GA4 data is typically available within a few hours, but some metrics (especially those tied to Google Ads or Search Console integrations) may take 24–48 hours to fully process.
* **Data retention** — GA4 properties have a configurable retention period (2 or 14 months). Coupler.io can only pull data within the retention window. For historical backfills beyond that window, export your data to BigQuery or another destination before it expires.
* **Thresholding** — GA4 may apply data thresholds to protect user privacy, especially when Google Signals is enabled. Rows representing too few users may be withheld. Adding high-cardinality dimensions (e.g., `Landing page + query string`) makes thresholding more likely.
* **Unsampled data** — Coupler.io pulls data through the GA4 Data API, which returns unsampled results. This means your exports may differ slightly from the GA4 interface (which sometimes applies sampling) but are generally more accurate.
* **Event-based model** — Unlike Universal Analytics (which was session-based), GA4 uses an event-based data model. Every interaction is tracked as an event. "Conversions" are now called "key events" and are counted per event, not per session.
* **Key event names** — GA4 key event names must only contain letters (A–Z), numbers (0–9), and underscores. If your GA4 property has key events with special characters (spaces, hyphens, brackets, non-Latin characters), the API will reject the request. Rename the events in your GA4 property settings before pulling them.
* **"Returning users" metric** — The GA4 API does not expose a dedicated "Returning users" metric. To get this value, create a formula column in Coupler.io's Transformations step: `Total users − New users`.