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Integration: BigQuery integration for Analytics data

This article provides instructions to share Analytics data via BigQuery integration

Updated over 12 months ago

Data Format & Requirements

Please prepare a table or a view in BigQuery where we can access data in a format similar to the one in this spreadsheet: Google Sheet Link

This table should contain the following dimensions and metrics:

Dimensions

  • Date – Data should be provided daily.

  • Product ID – Used to match data in ROI Hunter. Ensure this ID matches one of the IDs in your catalog (typically Product ID, Retailer ID, or Item Group ID).

  • Country / Other Filters (Optional) – If you want to share data for multiple markets in a single table, you may include a country or other relevant filters.

Tracking Dimensions for ROI Hunter (strongly recommended)

To enable proper tracking and connect revenue with campaigns and ads, please include:

  • Source – Typically utm_source, indicating where the revenue originated (e.g., Facebook).

  • Medium – Typically utm_medium, specifying the marketing medium (e.g., cpc, paid social).

  • Tracking ID – ideally the ID of the ad that generated revenue.

    • If Ad ID is unavailable, provide one of the following:

      • Ad Name (support only if all ads use unique names)

      • Ad Set ID or Name

      • Campaign ID or Name

Metrics

  • Product Revenue - Revenue from individual product sales.

  • Item Quantity - Total number of product units sold. Also known as "purchases", "items sold", "units" or "orders".

  • Quantity Added to Cart - Number of times a product has been added to cart. Also known as "add to cart" or "cart additions"

  • Product Detail Views - Number of times users viewed the product-detail page. Also known as "view items", "product views" or "items viewed".

  • up to three custom metrics - available for additional metrics you wish to use in ROI Hunter.


Data Setup Guidelines

  • Partitioning: Please ensure the table is partitioned by date to reduce data processing costs.

  • Region: Set up the dataset for the EU region. If this is not feasible, specify which region the data is stored in.

  • Access & Table Information:

    • Provide us with the name of the table, where we can find your data, e.g. your_project.your_dataset.your_table

    • Share “BigQuery Data Viewer” access to this table with the following email: data-warehouse@roihunter.com

Additional Information

  • Currency: Indicate the currency used in your data. If multiple currencies are present, specify how we can filter them and which currency corresponds to which filter.

  • Data Availability: Let us know when we can start using the data and when the numbers are considered final. For example, if revenue stabilizes after two days, please specify that.

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