supermetrics

What This Skill Does

The Supermetrics skill for OpenClaw provides a powerful, robust interface for programmatic access to marketing analytics data across over 100 different platforms. By integrating directly with the Supermetrics API, this skill allows users to automate the extraction of critical performance indicators from major ad networks and web analytics tools, including Meta Ads, Google Ads, LinkedIn Ads, and Google Analytics 4. It handles the complexities of API authentication, source discovery, and asynchronous data querying, enabling developers and analysts to build custom reporting pipelines, monitor marketing spend, or derive cross-channel insights directly through OpenClaw.

Installation

You can install this skill directly via the command line within your OpenClaw environment. Run the following command in your terminal:

clawhub install openclaw/skills/skills/bartschneider/supermetrics-openclawd

Once installed, ensure you have your API credentials configured according to the OpenClaw environment variables settings for this skill.

Use Cases

• Automated Performance Reporting: Automatically generate and retrieve weekly marketing performance summaries across multiple ad platforms without logging into individual dashboards.
• Data Centralization: Aggregate metrics like clicks, impressions, and conversions from various sources to store in a centralized data warehouse or custom database.
• Anomaly Detection: Use the skill to pull daily spend or conversion data and build lightweight monitors that alert you to spikes or drops in campaign performance.
• Cross-Channel Analysis: Compare the efficiency of your marketing spend across LinkedIn, Facebook, and Google Search side-by-side using unified field names retrieved via the discover_fields functionality.

Example Prompts

1. "Check the current status of the Supermetrics connection and then pull the last 7 days of sessions and pageviews for my GA4 property."
2. "List all available accounts for Meta Ads and then execute a query for clicks, impressions, and spend for the last 30 days."
3. "Search for the available metrics in Google Ads and generate a report comparing current traffic against my internal performance benchmarks."

Tips & Limitations

• Async Handling: Remember that query_data returns a schedule_id. You must use get_results to retrieve the final dataset; always implement a small polling delay if running this as part of an automated workflow.
• Resource Management: Use discover_fields frequently to ensure you are referencing the correct field IDs, as platforms often update their available metrics.
• Performance: While the skill supports large queries, it is best practice to filter data using the filters parameter early in the query_data call to minimize payload sizes.
• Authentication: Ensure your API key has the necessary read scopes for all platforms you intend to query, or you may receive permission errors during the discover_accounts or query_data phases.