Overview

Supermetrics is a data integration platform that enables marketing professionals and data analysts to consolidate performance data from various marketing, sales, and analytics sources. Founded in 2013, the company provides connectors that extract data from platforms such as Google Ads, Facebook Ads, Google Analytics, and LinkedIn Ads, then transfer it to destinations like Google Sheets, Microsoft Excel, Looker Studio (formerly Google Data Studio), Microsoft Power BI, and cloud data warehouses including Google BigQuery, Snowflake, and Azure Synapse. This aggregation capability addresses the challenge of siloed data, allowing users to create unified reports and dashboards for comprehensive marketing performance analysis.

The platform is designed for users ranging from individual marketers and small agencies to large enterprises. For marketers, Supermetrics automates the manual process of exporting and combining data, reducing the time spent on data preparation and allowing more focus on analysis and strategy. For data professionals, it provides a reliable pipeline for ingesting marketing-specific datasets into central data repositories, which can then be used for advanced analytics, machine learning initiatives, or integration with broader business intelligence efforts. Its core value proposition lies in its ability to provide fresh, accurate data directly within familiar reporting environments, fostering data-driven decision-making in marketing operations.

Supermetrics excels in scenarios requiring regular, automated reporting across a diverse set of marketing channels. For example, an e-commerce business tracking ROI across search, social, and display campaigns can use Supermetrics to pull all relevant cost and conversion data into a single Google Sheet, where custom calculations and visualizations can be applied. Similarly, a marketing agency managing multiple client accounts can standardize their reporting processes by connecting each client's data sources to a central reporting template in Looker Studio. The platform's direct integration with popular BI tools and spreadsheets minimizes the need for extensive ETL (Extract, Transform, Load) development work typically associated with data warehousing projects, positioning it as a tool for rapid deployment of marketing analytics infrastructure. While it offers an API for more custom or programmatic integrations, its primary focus is on user-friendly, pre-built connectors that abstract away much of the underlying complexity of API interactions and data normalization across different platforms.

Key features

  • Data Connectors for Marketing Platforms: Provides direct integrations to over 100 marketing data sources, including advertising platforms (e.g., Google Ads, Facebook Ads, LinkedIn Ads), analytics tools (e.g., Google Analytics, Adobe Analytics), social media platforms (e.g., Facebook, Instagram, X), and SEO tools (e.g., Google Search Console, Semrush). This allows for consolidated data extraction from diverse ecosystems (Supermetrics Docs).
  • Destinations for Reporting and Analysis: Supports various data destinations including spreadsheet applications (Google Sheets, Microsoft Excel), business intelligence tools (Looker Studio, Microsoft Power BI), and cloud data warehouses (Google BigQuery, Snowflake, Azure Synapse). This flexibility enables users to work with their preferred analytics environment.
  • Automated Data Transfers: Enables scheduled refreshes of data, automating the process of fetching fresh data from connected sources into the chosen destination. This eliminates the need for manual data exports and imports, ensuring reports are always up-to-date.
  • Custom Query Building: Offers an interface to define specific metrics, dimensions, and date ranges for data extraction, allowing users to pull precisely the data points required for their analysis without over-fetching.
  • API for Custom Integrations: Provides a REST API for developers to build custom data pipelines or integrate Supermetrics functionality into proprietary applications, offering flexibility beyond the pre-built connectors for unique use cases. The API supports various authentication methods and data formats (Supermetrics Docs).
  • Templates and Reporting Solutions: Offers pre-built report templates for common marketing use cases, such as cross-channel performance analysis or e-commerce reporting, to accelerate the setup of new dashboards and analyses.
  • Centralized Data Management: Allows users to manage all their data connections and queries from a single Supermetrics account, providing an overview of data flows and scheduled jobs.

Pricing

Supermetrics offers tiered subscription plans based on the number of data sources, users, and queries. Plans are generally billed annually, with discounts compared to monthly billing.

Supermetrics Pricing Tiers (as of May 2026)
Plan Name Key Features Starting Price
Essential Limited data sources, basic destinations (e.g., Google Sheets, Looker Studio), suitable for individual marketers. $39/month (billed annually)
Core Expanded data source options, additional destinations (e.g., Excel, Power BI), increased query limits. Contact for pricing
Super More data sources and destinations, higher query volumes, API access, suitable for teams and agencies. Contact for pricing
Enterprise Custom data source and destination requirements, dedicated support, advanced security features, custom query capacity. Contact for pricing

For detailed and up-to-date pricing information, including specific feature breakdowns for each tier and options for monthly billing, refer to the official Supermetrics pricing page.

Common integrations

Alternatives

  • Fivetran: A cloud-based ETL tool focusing on automated data movement from various sources into data warehouses, including a broad range of marketing and non-marketing connectors.
  • Funnel.io: Specializes in marketing data integration, normalization, and transformation, with a strong focus on data quality for marketing analytics.
  • Improvado: Offers a marketing data aggregation platform with a wide array of connectors, focusing on creating custom dashboards and reports for agencies and brands.

Getting started

To begin using Supermetrics, the typical starting point involves connecting a data source to a destination like Google Sheets or Looker Studio. The following example demonstrates how to pull Google Ads data into Google Sheets using the Supermetrics add-on. This process involves installing the add-on, authenticating Google Ads, and then configuring the query parameters.

First, install the Supermetrics add-on for Google Sheets from the Google Workspace Marketplace. Once installed, navigate to an empty Google Sheet and open the add-on sidebar:

// In Google Sheets:
// Extensions > Supermetrics > Launch
// This opens the Supermetrics sidebar.

From the sidebar, you would then select your data source (e.g., Google Ads), authenticate your account, and define your query. The query specifies what data to fetch (metrics), how to break it down (dimensions), and the date range.

// Example Supermetrics query configuration (conceptual representation in JSON format for clarity)
{
  "data_source": "Google Ads",
  "account": "My Google Ads Account (client ID: XXXXXX)",
  "select_metrics": [
    "Clicks",
    "Impressions",
    "Cost",
    "Conversions"
  ],
  "split_by_dimensions": [
    "Date",
    "Campaign"
  ],
  "date_range": "Last 30 days",
  "options": {
    "rows_per_fetch": 10000,
    "data_sampling": "no_sampling"
  },
  "destination": "active_sheet",
  "write_headers": true
}

After configuring these parameters in the Supermetrics sidebar, pressing "Get Data to Table" will execute the query and populate the selected Google Sheet with the requested Google Ads data. This process is similar across other destinations like Looker Studio, where you would use the Supermetrics connector to build a data source based on similar query parameters.

For more advanced use cases, such as integrating with data warehouses, the Supermetrics admin panel on their website typically manages transfers. For example, setting up a transfer to Google BigQuery involves configuring the source, destination BigQuery dataset, and scheduling within the Supermetrics interface.

# Conceptual command to initiate a Supermetrics data transfer to BigQuery
# (This is handled via the Supermetrics web UI, not direct CLI for most users)
supermetrics_cli transfer create \
  --source "google_ads" \
  --destination "google_bigquery" \
  --source-account "my_google_ads_id" \
  --bigquery-project "my-gcp-project" \
  --bigquery-dataset "marketing_data" \
  --table-prefix "google_ads_daily" \
  --interval "daily" \
  --metrics "clicks,impressions,cost" \
  --dimensions "date,campaign"

This flow prioritizes a graphical user interface for most operations, with the API offering more programmatic control for specific development needs.