¶ Reports - BigQuery and Looker Studio
Reports based on Google BigQuery and Google Looker Studio let you analyze sales and customer behavior in the Hummerce store more deeply than the standard statistics in the panel. The store exports order, item and, optionally, older history data to BigQuery, and fully configurable reports and charts are built on top of it in Looker Studio, without affecting the store's performance.
As of Hummerce 2.29 (order and item export to BigQuery), extended with history export and a built-in Looker Studio report since version 2.34, updated 2026-09-29.
¶ Benefits and use cases
- Full report freedom - your own charts, filters and segments based on the store's real data, with none of the limits of the standard panel statistics, see Reports and statistics in the panel.
- Processing on Google's side - building and displaying reports doesn't affect the store's performance; the store only sends data to BigQuery once a day.
- Segmentation by any field - e.g. company account versus individual customer, store view, order source, delivery city.
- Can be combined with Google Analytics data - in the same analysis, alongside the store's sales data.
- A smaller store database - older change history (of items, orders, customers and other objects) can be moved to BigQuery instead of growing the store's database, which speeds up the panel.
- A ready-made report for reviewing the moved history directly in the store panel, with no SQL knowledge needed.
- Automatic, recurring emailing of the report (a Looker Studio feature) - e.g. a monthly sales summary.
- Once a day, in the background, the store sends new and changed orders and ordered items to BigQuery - among others, the order symbol and status, view, payment and delivery method, order source and coupons used, customer and delivery address data (country, city, postal code), language, customer group, net and gross values, currency; for items - symbol, category, producer, item group, quantity, prices, and the price list and promotion rules used and not used.
- The set of fields sent can be extended during implementation with any data available in the store, including custom parameters - this requires changing the module's configuration and preparing the matching columns in BigQuery.
- Selected fields (e.g. customer email, phone) can be encrypted before sending, if they are to reach BigQuery.
- A separate, optional mechanism moves the store's change history entries - dozens of object types (including items, orders, customers, warehouse, prices and promotions) - older than a set time to BigQuery. This keeps the store's database smaller and the store runs faster.
- Moved entries remain available for review in BigQuery with no time limit.
- Reviewing the moved history without SQL knowledge is done with a ready-made Looker Studio report, which can be embedded directly in the store panel (the Status -> History backup tab) - just enter the report ID in the configuration.
- Looker Studio combines data from BigQuery (optionally also from Google Analytics) into interactive reports: tables, bar, pie, line, stacked, scatter, time series and geographic charts.
- Reports are filtered by any field available in the source data, e.g. view, order source, customer group or delivery city.
- Access to the report is granted separately for each person, with the role of owner, editor or viewer.
- Reports can be scheduled to be emailed automatically, e.g. as a recurring sales summary.
- Data in the reports refreshes every 12 hours; the source data in BigQuery is updated once a day, according to the store's sending schedule.
- Looker Studio itself is free - the Google Cloud/BigQuery service the data goes to is what costs. At a typical store's scale, the cost is usually small.
- Building and displaying reports runs entirely on Google's side - it doesn't affect the store's performance. The only work on the store's side is the daily data send, run in the background, at night.
- Exporting orders and items to Google BigQuery - since version 2.29.
- Exporting older change history to BigQuery, and the built-in Looker Studio report for reviewing it in the panel - since version 2.34.
- A Google Cloud account with the BigQuery service running (Google's service cost, independent of Hummerce).
- A Google Looker Studio account to build and share reports (the tool itself is free).
- Optionally - a Google Analytics 4 account, if the report is to combine the store's sales data with analytics data, see Google Analytics 4.
- Order source tagging - the source field in the export comes from the source tagging module, see Campaign and traffic source tracking.
- Requires implementation - the integration doesn't turn on by itself after an update. Scope:
- setting up a Google Cloud account and the BigQuery service, preparing the dataset and tables,
- configuring the module in the store panel (dataset and table names, BigQuery access data),
- optionally: enabling and configuring the export of older history (retention time in the store, object types to move),
- building reports in Looker Studio and connecting data sources (BigQuery, optionally Google Analytics),
- testing the data sending and the report's correctness, going live in production.
- Minimum estimated time:
- exporting orders and items to BigQuery, basic configuration - from 4 h,
- exporting older history - from 2 h more,
- building the first report in Looker Studio - from 4 h, depending on the number and complexity of the charts.
- The time for a specific implementation depends on its scope - we quote it individually.
- What the time depends on:
- the amount and type of data to send - a standard set or one extended with additional fields and parameters,
- the number and complexity of reports and charts in Looker Studio,
- the need to connect with Google Analytics,
- whether the store already has a Google Cloud/BigQuery account, or it needs to be set up from scratch,
- exporting older history - the number of object types to cover and the retention period in the store.
- The store shows only one built-in report in its own panel (change history) - the rest of the reports are viewed in Looker Studio.
- Data in BigQuery that the store tries to change right after sending it may be temporarily unavailable for editing (Google's streaming buffer) - a typical delay of up to about 90 minutes.
- Data in the reports refreshes every 12 hours - this isn't real-time analytics.
- Extending the sent data with new fields requires changing the module's configuration and preparing the matching columns in BigQuery - this can't be done on your own from the panel.
- BigQuery/Google Cloud service costs are independent of Hummerce and grow with the amount of data stored and processed.
- We do not verify the configuration for legal compliance - storing customer data outside the store, in Google Cloud, is something the store accounts for in its own privacy policy.
- More ready-made Looker Studio reports embedded directly in the store panel - today, only the history report is available.
- Extending the standard set of sent fields with more sales and marketing data, with no individual configuration needed.
Do BigQuery and Looker Studio reports require Google Analytics?
No. The store's sales data is enough to build reports - Google Analytics can optionally be connected to extend the analysis.
Does building reports affect the store's performance?
No. Reports run entirely on Google's side - the store only sends data to BigQuery once a day, at night.
Are the reports updated in real time?
No. Data in BigQuery is updated once a day, and reports in Looker Studio refresh every 12 hours.
Is Looker Studio paid?
The tool itself is free. What's paid is the Google Cloud/BigQuery service the data goes to - at a typical store's scale, the cost is usually small.
How long does implementing the BigQuery export and the first report take?
Basic order and item export - from 4 h. The first report in Looker Studio - from 4 h more, depending on the number of charts.
Can access to a report be limited to selected people?
Yes. Looker Studio lets you grant access with the role of owner, editor or viewer, separately for each person.
Want to check what your own sales reports could look like for your store? Contact the Hummerce team (in Polish).
- Configuration in the panel: Configuration -> Settings, BigQuery group:
- Dataset name, Orders table name, Cart item table name - names matching the structure prepared in BigQuery,
- Task activated - turns the send to BigQuery on and off,
- Show detailed logs, Use mock - test mode, simulates BigQuery responses, doesn't save data,
- Maximum number of attempts - how many times the module retries sending a single order after an error,
- Updates statuses of orders in BigQuery, Updates orders on properties change in BigQuery, Update last update column,
- Save UTMs to your order - saves campaign parameters with the order for further analysis,
- History Entries Table Name, Send History Data - export of older change history,
- Looker Studio report ID - the ID of the report embedded in the Status -> History backup tab.
- Google Cloud service account access data - configured technically during implementation, not in the panel.
- Scheduled tasks on the task list: BigQuery - sending orders, BigQuery - sending history.
¶ REST API and MCP
- No dedicated operations in the REST API - the export runs as a background scheduled task.
- MCP (AI assistant - MCP server): general module configuration tools (ec2_module_describe, ec2_config_search, ec2_config_get, ec2_config_set) and task monitoring (ec2_tasks_list, ec2_task_log); no dedicated BigQuery or Looker Studio tools.
The module has no messages of its own visible to the customer - the export runs in the background, with no effect on page content.
The module doesn't add its own item or customer parameters - it uses the existing order, item and customer data.