What the data for this category looks like
Marketing content data for professional chains comes primarily from three sources: headquarters brand material libraries, localized materials uploaded by individual stores, and activity templates configured by regional operations. Data update frequency varies by scenario: localized store materials are added and adjusted weekly, regional activity templates are updated monthly, and headquarters brand specifications are synchronized quarterly. Each data entry includes fields such as store unique identifier, region code, material type (poster/tweet/short video script), effective time period, applicable customer group tags, material size (pixels), and activity budget (yuan). Some fields associated with member consumption behavior are synchronized in real time with in-store customer data.
What constraints these characteristics impose on workflow orchestration
The layered data structure of professional chains requires workflows to support hierarchical permission filtering. Only editable data corresponding to the current store or region is accessible, preventing cross-level data leaks. Material attributes with units, such as pixel size and budget amount, need built-in format validation rules in workflows to prevent non-standardized materials from entering subsequent review stages. Real-time synchronized in-store customer data requires workflows to support minute-level triggers. It is also necessary to limit the data shard size processed in a single run, to avoid node execution timeouts. The need for material reuse across multiple stores requires workflows to support template parameterized configuration, allowing quick replacement of variables such as store-specific identifiers and customer group tags.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
workflow_trigger_interval | 60 seconds | Matches the update rhythm of store localized materials, avoids overly frequent triggers |
data_permission_filter | Store/Region/Headquarters three-level isolation | Adapts to the layered data management requirements of professional chains, prevents cross-level data leaks |
format_validation_rules | Includes unit validation for pixel size and budget amount | Standardizes marketing material formats, reduces subsequent review costs |
batch_process_size | No more than 50 entries processed per run | Limits single-run data processing volume, avoids workflow node timeouts |
template_variable_scope | Supports store ID, customer group tags, effective time period | Meets parameterized configuration needs for multi-store material reuse |
plugin_execution_timeout | 300 seconds | Adapts to the processing duration of database connection plugins, balances execution efficiency and stability |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material types, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: Database connection plugin execution time increases significantly compared to older versions, and logs return the
timeout_warningstatus code. Cause: The default plugin timeout value of the new FastGPT version is not adapted, and theplugin_execution_timeoutconfiguration is not adjusted for batch processing of multi-store data in professional chains. - Phenomenon: The AI model cannot be selected in the classify module configuration interface, but the published workflow runs normally. Cause: Available models are not specified for the classify module in the workflow's global model management. The platform's default bound model is automatically called during publishing.
- Phenomenon: The reply from a previous AI conversation in the workflow is included in the final output result. Cause: No output filtering node is added to the workflow, and previous conversation content is not truncated or excluded.
How to confirm the configuration is complete
- Manually trigger the workflow once, view the data filtering records in the execution log, confirm that only marketing data from the current authorized level is loaded.
- Upload a test material without pixel size labeling, check if the workflow's format validation node intercepts the entry.
- Configure template variables and generate test outputs for two different stores, confirm that variables such as store ID and customer group tags are correctly replaced.
- Test the single-run execution duration of the database connection plugin, adjust the
plugin_execution_timeoutconfiguration to a threshold adapted to the current business processing speed.
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.