What the data for this category looks like
Data on revenue yields and market daily reports in the advertising and marketing field mainly comes from open APIs of various media advertising platforms, and databases from advertisers' self-built ad delivery management systems. There are two types of data update cycles: full daily report data is batched and updated at a fixed time every early morning, while real-time bidding data is refreshed every 15 minutes.
The data is stored in a structured format. Each row corresponds to an independent ad campaign or delivery unit, and includes the following fields: ad campaign unique ID, delivery channel type, impression count, click count, cumulative consumption amount, valid conversion count, final revenue amount, and revenue-to-cost ratio.
The units for each field are as follows: impression count is counts, click count is counts, cumulative consumption amount is yuan, valid conversion count is counts, final revenue amount is yuan, and revenue-to-cost ratio is a dimensionless value.
What constraints do these characteristics impose on workflow orchestration
There are several key constraints:
- Multi-source API authentication requirements: Different advertising channels use different authentication methods. Corresponding nodes must be configured in the workflow to handle different keys, OAuth tokens, and similar information.
- Dual data update rhythm requirements: The workflow must support both scheduled full data pull and incremental real-time synchronization nodes.
- Field naming differences: A mapping step must be added to the workflow to unify fields from different platforms into a standardized format before subsequent revenue yield calculations can be performed.
- Revenue yield calculation relies on linked multiple fields: A data validation node must be added to filter missing or abnormal values, to avoid distorted calculation results.
- Daily report data requires aggregation by channel, time period, and other dimensions: A grouping and aggregation node must be configured in the workflow to complete data integration.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
scheduled task cron expression | 0 2 1 * * * | Ad platforms typically complete batch processing of the previous day's data before 1 AM. Triggering 2 minutes early ensures complete data is obtained. |
HTTP request timeout | 600 seconds | Full daily report data returned by ad platforms has large volume. Sufficient request time must be reserved to avoid task interruption. |
field mapping rules | Automatically match via preset mapping tables per channel | Different ad channels have different field naming conventions. Automatic mapping reduces manual configuration workload. |
missing value handling method | Skip abnormal fields and trigger alerts | Missing advertising data will cause errors in revenue yield calculations. Alerts enable timely anomaly troubleshooting. |
workflow retry times | 3 times | Ad platform APIs may experience temporary fluctuations. Multiple retries improve overall task success rate. |
Feishu multidimensional table write mode | Overwrite the specified worksheet for the current day | Daily report data needs to be updated with the latest results each day. Overwrite mode ensures data consistency. |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: Workflow stops mid-execution with no error logs. Cause: No reasonable
HTTP request timeoutis set, the request times out when the ad platform returns full data, and the node does not trigger the exception reporting mechanism. - Symptom: Prompt templates in the workflow fail to correctly recognize field names with spaces. Cause: Field separation rules are not clearly specified in the
prompt template, or the space retention configuration oftext preprocessingis not enabled, causing multiple field contents to be merged and recognized. - Symptom: Model nodes cannot call preset environment variable keys. Cause: The environment variable reference permission is not enabled in
model configuration, or the ad platform API key is not added to the global environment variable list, causing the model node to fail to obtain authentication information.
How to confirm the configuration is correct
- Manually trigger the workflow, check the output logs of each node, and confirm that the fields returned by each API request match the preset mapping rules.
- Check the output results of the data calculation node, and verify that the revenue-to-cost ratio calculation logic conforms to business definitions.
- View the write results in the Feishu multidimensional table, and confirm that the current day's data has been correctly updated to the specified worksheet.
- Simulate a data missing test scenario, and confirm that the workflow triggers the preset alert notification.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.