What the Data for This Category Looks Like
Data for this category originates from search ad backends, search term reports, bidding ranking data, and landing page data. Update cycles follow daily and weekly schedules. Daily production creates documents including keyword lists, negative keyword tables, bid records, and search term reports. Core fields include keyword text, match type, single bid amount, negative keyword effective scope, average daily search volume, and conversion cost. Supported units include yuan, occurrences, characters, and others. The data centers on user-initiated search trigger terms, and forms a complete workflow around keyword expansion, filtering, and adjustment.
Constraints Imposed on Forms and Interactions
This category’s data comes from multiple sources and has scattered fields. FastGPT form input nodes accept input data processed by external business systems. External business systems handle batch import of multiple document types and field mapping logic. External business systems implement specific import processing and field association logic. External business systems manage synchronization triggers, real-time validation, and scheduled pull logic for data with different update frequencies. FastGPT form input nodes only collect input and pass it to subsequent nodes. Since core data centers on user-initiated search terms, FastGPT form input nodes support relevant interaction configurations. External business systems implement exclusive interaction control logic for keyword match types and negative keyword rules, preventing subsequent ad delivery exceptions caused by incorrect field formats. External business systems simplify interaction paths for high-frequency operations during the most time-consuming keyword expansion, negative keyword filtering, and bid adjustment processes. External business systems provide operation logs and version rollback entries, facilitating tracing of operation records during defect troubleshooting.
How to Configure Settings
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
Form Input Node formInput | Test example: Select 3 fields from search ad keyword management as required inputs; actual fields are determined per task | This node collects user input; troubleshoot interaction status when required items are missing, to prevent subsequent nodes from failing to receive complete input |
User Select Node userSelect | Test example: Set 2 business options, check corresponding branches one by one | This node handles user selection; querying and filtering records related to search ad keyword management must be implemented by subsequent interfaces or external systems |
| Field Passing After Submission | Test example: Prepare 10 search ad keyword management input samples, covering complete filling, missing required items, and cancel operations | Compare input and node output, verify whether subsequent nodes receive corresponding fields; result thresholds are determined per actual task |
| External Implementation Item: Negative Keyword Validation Trigger Timing | Must be implemented separately by external systems; when keywords are submitted | Implemented by external business systems, proactively block negative keyword rules with incorrect formats, reduce subsequent ad delivery exceptions |
| External Implementation Item: Data Source Sync Interval | Must be implemented separately by external systems; 24 hours / 7 days | Corresponds to the daily and weekly update cycles of data; synchronization logic is implemented by external business systems |
| External Implementation Item: Form Field Grouping Rules | Must be implemented separately by external systems; split by document type | Matches the classification logic of daily documents such as keyword lists and negative keyword tables; grouping configuration is implemented by external business systems |
Three Common Mistakes
- After a form related to search ad keyword management is submitted, subsequent nodes do not receive complete fields. Compare required items, actual submitted content, and node output mapping one by one, then check subsequent interface returns. Existing symptoms alone cannot determine the root cause.
- Configured negative keyword rules do not take effect, and matching results displayed in the backend do not match expectations. The cause is that the selected match type does not match the standard configuration of the ad backend; broad match is mistakenly selected as exact match, resulting in the negative keyword scope not covering target search terms.
- After batch importing bid records, some fields are empty and cannot be saved. The cause is that the form mapping is not configured according to the document field order of the external business system, resulting in the bid amount field not being correctly associated with the data source column.
How to Confirm Proper Configuration
- Upload a test keyword list, verify that the imported field mapping matches the document classification logic of the external business system.
- Submit a test keyword containing special characters, check whether the format validation prompt from the external business system is triggered.
- Switch the data source sync interval, check whether the synchronization task logs of the external business system execute according to the configured cycle.
- Select different match type options, check whether the matching logic of the ad backend preview interface meets expectations. This verification is based on the form node interaction logic of FastGPT v4.17.0. Business validation and synchronization configuration are implemented by external business systems.
The values provided are common starting points and should be compared against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.