What the data for this use case looks like
Marketing-related data mainly comes from offline branch client lead ledgers, online mini-program and official account reservation forms, and local customer group operation and household registration linked data. There are two update rhythms: offline ledgers are synced in batches weekly, and online form submissions are updated in real time. Documents use structured table format, including fields such as customer name, contact phone number, intended marketing product, handling branch, and scheduled processing time. The contact phone number field is 11-digit pure digits. The product name field uses fixed enumeration values. The amount field unit is yuan. The time field uses the YYYY-MM-DD format.
What constraints these characteristics impose on forms and interaction
Offline batch sync requires forms to support batch import data format validation to avoid field misalignment or format mismatches. Real-time online submission requires built-in real-time field validation to block inputs with invalid formats. Local service attributes require the branch selection field to link to local administrative regions, only displaying business branches within the corresponding county to reduce user selection costs. The fixed enumeration intended product field requires the form to use a dropdown selection field, disallowing free input to reduce subsequent AI recognition ambiguity. The local attribute of customer group data requires the form to not collect non-local customer group information across regions to avoid invalid leads.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
FORM_FIELD_VALIDATE_TIMEOUT | 3 seconds | The target marketing form has a limited number of fields. All field format validation can be completed within 3 seconds, avoiding excessive user waiting time. |
BATCH_IMPORT_MAX_ROWS | 500 rows | Offline branch single-sync customer lead data is usually in the hundreds range. This value covers most batch import scenarios. |
WORKFLOW_GLOBAL_VAR_TYPE | Enumeration type | Intended marketing products use fixed enumeration values. Enumeration types limit input scope and reduce subsequent AI recognition ambiguity. |
PARSE_FORM_CONTENT_TIMEOUT | 10 seconds | Parsing single form data from batch imports requires a reasonable duration. 10 seconds covers most non-extreme data scenarios. |
FORM_SUBMIT_RATE_LIMIT | 10 requests per minute | Online user submission frequency stays within a reasonable range. This avoids malicious submissions occupying system resources. |
The parameter values provided on this page are all common recommendations used as starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Mistakes
- Phenomenon: After selecting a global variable for the knowledge base in the workflow, retrieval cannot be triggered normally. The error prompt reads "variable type mismatch". Reason: The global variable was not set to enumeration type. In this marketing scenario, product options are fixed enumeration values. Free text type variables cannot match the preset classification labels of the knowledge base.
- Phenomenon: The intended product description submitted by the user cannot be correctly recognized by the AI node. The system returns "no valid product information matched". Reason: The form did not use a dropdown selection field. Users can freely input non-enumerated product names. This results in the AI prompt not covering all input scenarios.
- Phenomenon: Some fields are empty in the offline ledger data imported in batches. The import task shows "partial data verification failed". Reason: Corresponding format verification rules were not configured. This causes fields with non-local branches or invalid phone numbers to be skipped.
How to Confirm Proper Configuration
- Submit a test form data entry. Check the completion duration of field verification. Confirm it meets the preset verification time requirements.
- Import a small amount of offline ledger test data. Check that all fields are correctly mapped. No empty fields or format errors appear.
- Configure the AI node prompt in the workflow. Use enumeration product names as input. Confirm the AI can correctly recognize and return matching results.
- Simulate preset frequency submission operations. Check whether rate limit interception is triggered. Confirm the rate limit logic works properly.
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.