Customer Technical Support and Pre-sales Q&A for Search Ad Keyword Management: Multi-turn Dialogue and Prompt Engineering

Daily processed data for this category is primarily sourced from search ad backends, search term reports, bidding ranking data, and landing page data.

What the Data for This Category Looks Like

Daily processed data for this category is primarily sourced from search ad backends, search term reports, bidding ranking data, and landing page data. Update frequency is typically daily or weekly. Daily documents include structured keyword lists, negative keyword tables, bid records, and unstructured search term reports. Data fields cover keyword text, matching mode, single bid amount, historical search volume, conversion-related data, and more. Units include yuan, times, characters, and others. The processing logic centers on user-initiated search terms, which differs from creative testing scenarios for feed ads.

Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering

The mixed structured and unstructured nature of data requires distinguishing between structured fields such as keyword text and bid values, and unstructured fields such as search term text during multi-turn dialogue. Prompts must clearly define field format constraints. Data updated daily or weekly requires limiting dialogue context to the past 7 days of reports to avoid introducing outdated data. Keyword lists typically have a large number of entries, so the context window for multi-turn dialogue must limit valid field counts to prevent exceeding model processing limits. Unstructured text from search term reports must first undergo field extraction. Intermediate extraction results must be retained for subsequent calls during multi-turn dialogue. Processing logic focused on user-initiated search terms requires prompts to focus on keyword association analysis in search scenarios, and avoid unrelated creative testing logic.

Configuration Settings

The following configurations are written based on FastGPT v4.17.0.

Configuration ItemRecommended SettingRationale
Session ID BindingBind the chatId parameterEnsures session uniqueness for multi-turn dialogue, avoids cross-session confusion
Maximum Context WindowFirst 6 turns of dialogue + past 7 days of data summaryMatches daily update data frequency, avoids outdated information, and limits context length to prevent model overload
Context Memory ToggleEnabledRequires retaining historical conversation content in messages to ensure continuity of multi-turn Q&A
Variable BindingBind the latest files for keyword lists and negative keyword tablesEnsures variables calls the latest business data, aligns with daily update cycles
Prompt Format ConstraintRequire output structured results compliant with JSON SchemaAdapts to structured fields of keyword data, facilitating subsequent automated processing
Single Dialogue Token Limit8000 tokenAdapts to the text length of search term reports and keyword lists, avoids truncating critical information

Three Common Misconfiguration Issues

  • Phenomenon: The model fails to associate keyword bid information from the prior turn, even after setting 6 turns of context memory. Cause: Historical conversation content in the messages parameter is not correctly bound, or the context window configuration does not cover all historical interactions.
  • Phenomenon: Extracted keyword information displays garbled text. Cause: The prompt does not explicitly specify an encoding format, or special characters in unstructured search term reports are not escaped.
  • Phenomenon: Generated keyword expansion results do not match current business data. Cause: The latest keyword list or negative keyword table data bound via variables is not called in the conversation flow, leading to the use of outdated business configurations.

How to Verify Correct Configuration

  • Initiate a query that includes historical keyword bid information, and confirm whether the model can associate the bid value from the previous turn.
  • Upload the latest search term report, submit a request to extract keywords, and confirm whether the output format matches preset requirements.
  • Test the iframe embedding scenario without user interaction, and observe whether system performance metrics meet expected standards.
  • Check whether the file bound to variables in the configuration page is the latest daily updated version.

The values provided here are common starting points and should be evaluated 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.