AGENT SKILLBY RETIEEDRA-PROFOUND
AI search attribution planner
AT A GLANCE
AI search attribution planner is an agent skill for analytics. Designs measurement for AI mentions, delayed brand visits, assisted conversions, and business outcomes beyond direct referral clicks. It is published by retieedra-profound in the retieedra-profound/skills-marketing-library GitHub repository under the MIT license. Install it with: npx skills add retieedra-profound/skills-marketing-library --skill ai-search-attribution-planner
- REPO STARS
- NOT AVAILABLE
- LICENSE
- MIT
- CATEGORIES
- SKILL.MD SIZE
- 2.9 KB65 LINES
QUICK ANSWER
- WHAT IT IS01
- Designs measurement for AI mentions, delayed brand visits, assisted conversions, and business outcomes beyond direct referral clicks. It brings Profound's specific operating context into AI search attribution planner, so the agent is guided by a sharper source than a generic prompt.
- INPUTS02
- Context the agent needs: your goals, audience, constraints, and any source material the skill asks for.
- OUTPUT03
- A ready-to-use result: the analysis, copy, or recommendations the agent produces.
INSTALL
One command adds this skill from its source repository.
npx skills add retieedra-profound/skills-marketing-library --skill ai-search-attribution-plannerREAD THE SKILL.MD BELOW BEFORE YOU RUN IT. SKILLS INSTRUCT YOUR AGENT.
SKILL.MD
The full file, as published in the source repository. Copy it, download it or open it on GitHub.
FRONTMATTER
- name
- ai-search-attribution-planner
- description
- Designs measurement for AI mentions, delayed brand visits, assisted conversions, and business outcomes beyond direct referral clicks. Use when proving AEO impact, building analytics requirements, setting KPIs, or explaining why AI visibility does not match referral traffic.
ON THIS PAGE · 5
AI Search Attribution Planner#
Research basis#
This skill operationalizes Profound's research, The AI mention effect (opens in a new tab), published July 1, 2026.
Key takeaways from the study:
- Profound joined more than two million privacy-safe AI conversations with downstream browsing behavior.
- After an AI assistant introduced a brand, users visited its site above their forecast baseline during the following seven days.
- Only 42% of downstream visits occurred within 24 hours; a same-session window misses much of the behavior.
- More than 97% of measured downstream visits lacked a trackable AI-referral parameter, even after ChatGPT made links more clickable.
The study was observational, US-only, and measured site visits rather than purchases. Do not present its aggregate lift as a causal forecast for an individual brand.
Goal#
Measure AI search as an influence channel using direct, assisted, delayed, and self-reported evidence while keeping causal claims proportional to the design.
Measurement layers#
- Exposure: brand mention, recommendation, prominence, sentiment, and citation.
- Immediate behavior: direct referral, click, landing page, and engaged session.
- Delayed behavior: branded search, direct visit, return visit, and cross-session conversion.
- Business outcome: signup, lead, qualified pipeline, purchase, revenue, retention, or support deflection.
Keep these layers separate. A visibility increase is not automatically a revenue increase.
Workflow#
- Define the decision the measurement must support.
- Specify exposure by engine, prompt cohort, market, language, and date.
- Audit current referral tagging and analytics classification.
- Preserve known AI referrals, landing pages, query parameters, and referrers.
- Add assisted indicators:
- branded search movement
- direct and organic visits to exposed pages
- one-hour, 24-hour, and seven-day windows
- self-reported attribution
- CRM notes and sales-call evidence
- Choose an evaluation design:
- pre/post with stable cohort
- matched market or page comparison
- holdout when feasible
- interrupted time series
- exposure panel or incrementality study
- Identify confounders such as campaigns, seasonality, launches, press, and platform changes.
- Connect metrics to business outcomes without double counting.
- Document privacy, consent, retention, and minimum aggregation requirements.
- Report uncertainty and alternative explanations.
Output#
Return:
- Measurement objective and causal confidence level.
- Funnel from AI exposure to business outcome.
- Event and property specification.
- Attribution-window recommendation.
- Dashboard metrics split into exposure, immediate, delayed, and business layers.
- Experiment or quasi-experiment design.
- Confounder and privacy checklist.
- Reporting language that distinguishes observation, association, and causation.
FAQ
07 QUESTIONS
01What is the AI search attribution planner agent skill?
Designs measurement for AI mentions, delayed brand visits, assisted conversions, and business outcomes beyond direct referral clicks. It is listed under analytics in the 100xLab agent skills directory.
02How do I install AI search attribution planner in Cursor, Claude Code, or Codex?
Run npx skills add retieedra-profound/skills-marketing-library --skill ai-search-attribution-planner in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only AI search attribution planner, not every skill in the repository.
03What does the AI search attribution planner SKILL.md cover?
The SKILL.md includes sections on Research basis, Goal, Measurement layers, Workflow and Output. Read the full text on this page or in plain markdown at /resources/agent-skills/retieedra-profound-skills-marketing-library--ai-search-attribution-planner--1eupmi8/raw.
04Which agents can use AI search attribution planner?
AI search attribution planner installs with the cross-agent skills installer (npx skills add), which sets it up for agents such as Claude Code, Cursor and Codex. Each agent loads the SKILL.md when you ask for the skill by name.
05What license is AI search attribution planner under?
The retieedra-profound/skills-marketing-library repository declares the MIT license. Read the license file in the repository before you copy or redistribute the skill.
06Is AI search attribution planner free to use?
Reading, copying and installing AI search attribution planner costs nothing: it is published in a public GitHub repository under the MIT license. Reuse and redistribution follow that license.
07Where is the source of AI search attribution planner?
AI search attribution planner comes from https://github.com/retieedra-profound/skills-marketing-library. The SKILL.md is at https://github.com/retieedra-profound/skills-marketing-library/blob/HEAD/profound/ai-search-attribution-planner/SKILL.md. The author is retieedra-profound.
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ATTRIBUTION
AI search attribution planner was written by its original authors and is published in retieedra-profound/skills-marketing-library (opens GitHub in a new tab) under the MIT license. All rights stay with the original authors.
100xLab did not write, maintain or endorse this skill. This page lists it for discovery. Repo stars belong to the source repository, not to the skill. Review any skill before you install it.