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Skillsyao-geo-tracking

yao-geo-tracking

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Updated 10-16 08:02

About this skill

Yao GEO Tracking

When To Use

  • Input the company name, brand name, and a small amount of supporting information, and expect the system to complete authoritative retrieval on its own and generate a GEO backend effect attribution framework and tracking system plan suitable for this company.
  • It is necessary to use the official website as the core basis, combine public materials and user-supplied information, identify business characteristics, and then output a personalized monitoring design for direct effects and indirect effects.
  • The deliverable needs to be a structured plan, and ideally it should also directly generate HTML and Word files.
  • It is necessary to map "enterprise type, conversion funnel, existing site capabilities, trackable signals" into an implementation roadmap with clear priorities.

Do Not Use

  • The user only wants to understand what GEO is, or only wants a set of general methodology popularization.
  • The user only wants to do GEO content strategy, topic planning, source analysis, or competitor research.
  • The user only wants to do SEO, SEM, CRM event tracking, or BI dashboard implementation, and does not need GEO attribution framework design.
  • The user explicitly only wants code implementation and does not want analysis plans, data definitions, or attribution design.

Required Inputs

The minimum input is only the company name. If the user provides the following information, absorb it as well:

  • Brand aliases, English name, product names, core business lines
  • Known official website or suspected official website links
  • Target market, customer groups, typical conversion actions
  • Existing landing pages, forms, hotlines, WeCom, promo codes, consultant entry points, and other reception assets
  • Key AI platforms, key keyword topics, core actions you hope to monitor
  • Whether direct output is needed HTML / Word

If the user does not provide supplementary information, it should still be started from the company name, and the information gaps should be explicitly listed at the end.

Required Reading

Read as needed before starting:

  • references/evidence-sourcing-workflow.md
  • references/attribution-framework.md
  • references/personalization-matrix.md
  • references/market-split-framework.md
  • references/quality-gates.md
  • references/html-output-outline.md
  • references/report-ui-rules.md
  • references/output-file-workflow.md
  • references/open-source-sanitization.md
  • references/observability-estimation-framework.md

Workflow

  1. First unify the enterprise entity.
    • Standardize the company's full name, brand name, product names, aliases, and English name.
    • If there is more than one company with the same name, first perform candidate alignment, then continue the analysis.
  2. Do not use internal systems as a default dependency.
    • Prioritize information provided by the user and publicly verifiable materials.
    • If internet access is available, first confirm the official domain, then supplement with public evidence such as the official website, product pages, about page, contact page, pricing page, case studies page, and careers page.
    • If internet access is unavailable, explicitly state that only a low-confidence version based on user-provided materials is being output.
  3. Determine the market scope and platform environment.
    • Clarify whether the current analysis leans more toward 国内 GEO、海外 GEO or 混合 GEO。
    • If domestic GEO mainly revolves around DeepSeek、豆包、元宝、Kimi and other platforms, increase the weight of passwords, questionnaires, WeCom, phone calls, campaign pages, and exclusive reception actions.
    • If overseas GEO mainly revolves around ChatGPT、Gemini、Perplexity and other platforms, it can rely more strongly on official website content structure, landing pages, form fields, web analytics, and the official page matrix.
  4. Establish a public evidence ledger.
    • Record every key piece of material source_system、source_locator、absolute_time、fact_or_inference、how_used。
    • Conclusions related to "latest" must include an absolute date; when a date cannot be obtained, do not say "latest."
  5. First determine the business type and conversion funnel.
    • At minimum determine B2B 销售型、PLG / SaaS、电商 / 标准化消费、预约 / 咨询型服务 the primary type among them.
    • In combination with references/personalization-matrix.md select the most matching reception actions and metric definitions.
  6. Verify the official website, and do not treat second-hand pages as the official website.
    • Verify the consistency of the brand's self-description, About Us, contact information, legal pages, social media, or recruitment pages.
    • Do not misjudge media releases, directory sites, or agency pages as the official website.
  7. Establish a foundational analysis draft for the enterprise's GEO backend.
    • At minimum, record the company positioning, core products, target audience, typical conversion paths, existing reception assets, current monitoring capabilities, and site capability limitations.
    • Clearly identify which are verified facts and which are inferences based on facts.
  8. Model in two layers: "direct effects / indirect effects."
    • First, break GEO value into 品牌层价值 and 效果转化层价值。
    • Brand-layer value emphasizes the role of "third-party endorsement" within AI platforms, including brand awareness, trust building, mindshare reinforcement, and reduced friction in subsequent conversions.
    • The effect-conversion layer value is further broken into 可直接监测的效果 and 间接促进的效果。
    • Direct effects: dedicated phone number, dedicated mobile number, dedicated WeChat ID, dedicated consultant entry point, dedicated benefit code, AI-exclusive landing page, form fields, source parameters, campaign page, customized CTA.
    • Indirect effects: brand term search volume, official website UV, landing page UV, CTA click-through rate, registration rate, booking rate, lead rate, conversion rate, self-reported source questionnaire.
    • Under 现状诊断 , a 效果追踪方法与原理说明 module must be added, using a table to list the principles, methods, applicable conditions, and recommended execution actions for all direct and indirect monitoring; if the deliverable is HTML, preferably also include a set of process diagrams.
    • Under 间接效果追踪方案 , a 监测效果边界说明 module must be added, explaining that directly observable GEO effects are usually only part of the total contribution, and that a common conservative planning assumption is approximately 20%~30%; scenarios with strong overseas official website reception may be higher; this ratio can only serve as a planning and interpretation boundary and must not be written as a fixed cross-industry fact.
    • Under 监测效果边界说明 , a 可观测性估算框架 module must continue to be added, outputting Observed / Recoverable / Unobservable three-layer planning values or ranges, applicable preconditions, main determining factors, and next-stage calibration actions.
    • Clearly state: the total GEO effect usually cannot be fully tracked, and the focus of the plan is to establish a minimal closed loop sufficient to explain trends, calibrate direction, and guide optimization actions.
  9. Select a plan based on the enterprise's actual situation and market type.
    • For high-ticket, long-decision-chain businesses, prioritize lead attribution, dedicated consultant entry points, form fields, and supplementary questionnaires.
    • For standardized consumer businesses, prioritize landing pages, discount codes, source parameters, registration conversion, and post-purchase self-reported sources.
    • Overseas GEO can focus more on official website page matrices, form sources, page events, and upgrade path design.
    • Domestic GEO usually needs to place more emphasis on codes, campaign pages, enterprise WeChat/phone, questionnaire backfill, and cross-device source patches.
    • If the official website capability is weak, prioritize supplementing reception pages and a minimal attribution closed loop, rather than piling on complex metrics.
  10. Output a personalized plan.
  • At minimum cover objectives, definitions, data sources, implementation methods, priorities, responsible parties, explainability, gaps, and risks.
  • If the user wants an "analysis plan" rather than an "implementation plan," also provide a minimal actionable checklist.
  1. If the user requests a delivered file.
  • First organize the conclusions into report_input.json。
  • then run:
  • python3 scripts/render_yao_geo_tracking.py --input <report_input.json> --output-dir <输出目录>
  • Generate by default .html and .docx。
  1. The public version skill must remain privacy-clean.
  • Do not require any private CLI, intranet address, private table, or company internal document.
  • Do not write private company samples, undisclosed metrics, or internal screenshots into examples, assets, reports, or delivery examples.

Output Contract

Each execution must return at least the following content:

  • 企业理解摘要: company positioning, products, target audience, typical conversion actions
  • 市场分层判断: domestic / overseas / hybrid GEO and its impact on the solution
  • 公开证据表: sources of the official website and public materials, absolute dates, key facts, purposes
  • 官网核验: official domain, verification basis, relevant public pages
  • 现状诊断: existing GEO reception and attribution capabilities, obvious gaps, assets already in place
  • 效果追踪方法与原理说明: brand value, conversion value, direct and indirect monitoring logic, including at least one methodology table and one set of diagrams or process structures
  • 直接效果追踪方案
  • 间接效果追踪方案
  • 监测效果边界说明
  • 可观测性估算框架
  • 归因口径与数据表设计
  • 优先级路线图
  • 置信度与缺口
  • 可视化 HTML 方案
  • 可交付文件: if the user requests it, actually generate .html and .docx

Validation Checklist

  • The output does not rely on any private system, private API, internal knowledge base, or unauthorized material.
  • The official website has been explicitly verified, rather than subjectively determined based on search results.
  • The domestic / overseas / hybrid GEO scenario has been determined, and the focus of the monitoring method has been adjusted accordingly.
  • Every key judgment can be traced back to the evidence table, and facts are distinguished from inferences.
  • All statements related to "latest" carry absolute dates.
  • The output clearly distinguishes direct effects from indirect effects.
  • The output clearly distinguishes brand-level value, direct effects, and indirect effects, and explains the relationship among the three.
  • The output includes 效果追踪方法与原理说明、监测效果边界说明 as well as 可观测性估算框架。
  • If output Observed / Recoverable / Unobservable three-layer percentage allocation, the three must sum to 100%。
  • The solution reflects differences in the enterprise's business type, conversion path, and site capabilities, rather than generic template boilerplate.
  • 20%~30% observable proportions such as these, if used, must be written as conservative planning assumptions or boundary explanations, and must not be passed off as universal conclusions.
  • If public evidence is insufficient, explicitly state the information gaps and the reasons for reduced certainty.
  • If the user requests deliverables, actually generate .html and .docx files, rather than only saying they will be generated.

Reference Map

  • references/evidence-sourcing-workflow.md: public evidence acquisition order and evidence table specification
  • references/attribution-framework.md: direct effects, indirect effects, and data design framework
  • references/personalization-matrix.md: personalized selection of attribution actions by business type
  • references/market-split-framework.md: monitoring differences and routing rules between domestic GEO and overseas GEO
  • references/quality-gates.md: quality gate for the open-source version skill
  • references/html-output-outline.md: HTML report structure and visualization modules
  • references/report-ui-rules.md: designing systematic HTML report UI rules
  • references/output-file-workflow.md: report input structure and file generation process
  • references/open-source-sanitization.md: de-privatization, removal of intranet dependencies, and public sample replacement rules
  • references/observability-estimation-framework.md: three-layer observability estimation framework and interval rules
  • scripts/render_yao_geo_tracking.py: generate HTML / Word deliverables
  • examples/hubspot-demo/report_input.json: public demo input samples
  • evals/trigger_cases.json: trigger boundaries
  • evals/quality_cases.json: quality and privacy gate samples