What the Data for This Category Looks Like
Marketing content data for professional chains in the financial, insurance, or wealth management space comes primarily from four sources: transcribed customer consultation records from offline stores, customer service conversations from online membership systems, customer follow-up logs from store sales associates, and distribution and click data for marketing materials of wealth or insurance products. Data updates follow two schedules: real-time conversation data syncs every hour, while logs and campaign data update daily. Most data is structured in table format, with fields including unique store identifiers, customer group profile tags, conversation turn numbers, associated marketing product IDs, conversion node status, and similar fields. Field units include store numbers, number of people, number of interactions, number of materials, and similar units.
What Constraints These Characteristics Impose on Multi-turn Conversation and Prompt Engineering
The multi-store, multi-customer group data characteristics of professional chains in the financial, insurance, or wealth management space impose multiple constraints on the multi-turn conversation and prompt engineering workflow. Unique store identifiers must be included in conversation context at all times to prevent cross-store product adaptation confusion. Short-turn real-time in-store consultations require limiting the context window to a reasonable range, to avoid redundant historical content interfering with current wealth or insurance script generation. The associated marketing product ID field requires prompts to explicitly call structured information for the corresponding product. Customer group profile tags must be embedded in the prompt’s role settings to adapt marketing scripts for different customer groups. Daily updated logs and campaign data require regular synchronization of the knowledge base, to ensure product information called by prompts remains up to date.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 800–1200 characters | Multi-turn conversations for professional chains are mostly short-turn customer consultations. This range retains valid historical conversation content while preventing token overflow |
sessionExpireTime | 7200 seconds | In-store consultations are mostly coherent single-visit conversations. A 2-hour session duration covers the full in-store consultation cycle |
recallTopK | Top 3 entries | Marketing content for professional chains is mostly store-specific short materials. Excessive recall causes information overload; 3 entries cover the core needs of the current customer group |
knowledgeBaseRefreshCycle | 86400 seconds | Marketing data for professional chains updates daily. Daily refresh ensures content called by prompts remains timely |
apiUserIdentifierField | Store ID + User Unique Identifier | Professional chains have multi-store, multi-user scenarios. Combined identifiers accurately distinguish chat records from different stores to avoid context confusion |
versionUpdateNoticeSwitch | Off | Business system integration requires no disruption to the conversation interface. When turned off, new conversations will not display version update notices |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: A version update notice pops up every time a new conversation is opened. Cause: The
versionUpdateNoticeSwitchconfiguration item was not turned off, as the default setting enables version update prompts. - Symptom: The API returns a
401 Unauthorizederror, and conversations cannot be started. Cause: TheAPI_KEYparameter was not configured correctly, or key permissions were not enabled. - Symptom: Redundant content from specified reply plugins appears in multi-turn conversations, interfering with current script generation. Cause: No rule to ignore plugin historical records was added to the prompt, or context filtering parameters were not configured.
How to Verify Correct Configuration
- A simulated conversation including a store identifier is initiated. The conversation context is checked to confirm it retains the corresponding store information, with no cross-store irrelevant content.
- System configuration items are reviewed to confirm
versionUpdateNoticeSwitchis set to off, ensuring new conversations do not display version update prompts. - Different user identifier combinations are passed when calling the API. Chat records for different sessions are checked to confirm they are stored independently, with no mutual interference.
- A conversation request is triggered. The returned result is checked to confirm it does not include redundant content from specified reply plugins, and complies with preset prompt rules.
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.