What the data for this category looks like
Marketing-related data for diversified finance comes primarily from three sources: the internal product filing repository, user behavior log repository, and marketing material repository. Product filing data is in structured format, including fields such as product code, risk level, investment scope, and performance benchmark. The risk_level field uses R1 to R5 rating units, with updates made quarterly alongside filing adjustments. User behavior data consists of semi-structured session and form logs. The visit_duration field uses seconds as its unit, with updates made in real time. Marketing materials are in rich-text format, including product promotional copy, jump links, and image assets, with updates made on demand.
What constraints do these characteristics impose on workflow orchestration?
Structured product filing data requires the workflow to strictly match field formats. Any field misalignment or missing field may lead to compliance risks in marketing content, so strict field mapping validation must be configured. Real-time updated user behavior data cannot rely on scheduled pulls, so a real-time trigger mode must be used, otherwise it cannot meet the immediate marketing needs of user consultations. Rich-text marketing materials include external link resources, so the workflow must support full parsing of links and images to avoid resource failures in generated content. Additionally, diversified financial marketing content must meet regulatory requirements, so a pre-validation step must be added to the workflow to ensure generated copy matches filed product information.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
trigger_mode | real_time_webhook | Customer behavior data for diversified finance is generated in real time, requiring immediate triggering of the marketing content generation process to match immediate user consultation needs |
data_sync_cron | 0 0 2 * * * | Diversified financial product filing information is updated quarterly. Synchronizing daily at 2 AM covers temporary adjustments and avoids using outdated data for marketing |
field_mapping_strictness | strict | Product data fields must strictly match filing formats to avoid compliance risks in marketing content caused by field misalignment |
text_extract_node_parse_mode | structured_field_only | Only extract structured product and user fields for marketing content generation, avoiding redundant information interfering with AI generation logic |
ai_prompt_context_limit | 12000–16000 characters | Diversified financial product information includes multi-dimensional content, and sufficient context can generate accurate and compliant marketing copy |
plugin_db_connection_timeout | 30 seconds | Connecting to PostgreSQL to query product filing data, a 30-second timeout avoids workflow blocking caused by database lag |
The parameter values provided on this page are common recommendations used as starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Phenomenon: Fields returned by the text extraction node are empty or do not meet filing format requirements. Cause: Strict field mapping configuration is not enabled, causing extracted product or user data to not match expected fields, preventing normal calling by subsequent nodes.
- Phenomenon: The AI model node in the workflow throws the error
chat:ai_input_is_e. Cause: The output of the code running node is not escaped, and unclosed special characters are carried when directly passed to the AI model, destroying the input format. - Phenomenon: After the database connection plugin runs, the prompt "Workflow verification failed, please check for missing or null values, and whether connections are normal" appears. Cause: Required parameters for the database connection are not pre-configured in the workflow, or a pre-validation node is not added, resulting in incomplete connection parameters or no effective prompt being triggered due to timeout.
How to Verify Proper Configuration
- Trigger a simulated user behavior event, check the workflow run log to confirm the process starts on time in
real_time_webhookmode. - Export the product data synchronized on the current day, compare with official filing information to confirm the field mapping configuration takes effect, with no misalignment or missing fields.
- Run the code node and export the output result, confirm the content has been escaped and can be normally pasted into the input box of the AI model node.
- Manually test the database connection, check the connection status returned by the plugin to confirm the parameter configuration is complete and the timeout setting meets business requirements.
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.