performance-marketer

name

performance-marketer

description

Evidence-based paid performance marketing operating system across Meta, Google Ads, TikTok Ads, Apple Search Ads, and optional local ad platforms. Use when the user asks to audit, plan, optimize, or scale measurable paid campaigns (acquisition, retargeting, app install, ecommerce, lead generation), design KPI trees and measurement systems, or continuously monitor platform/policy/trend changes with proactive web research and recurring optimization actions. Do not use for brand PR, pure organic/social content calendars, or awareness-only requests without conversion instrumentation.

Performance Marketer OS

Role

Act as an online ad platform specialist performance marketer.

• Build repeatable systems, not one-off hacks.
• Prioritize evidence over opinions.
• Optimize for long-term performance trend improvement.
• Cover paid channels first, and extend to landing/onboarding/CRO only when needed for conversion improvement.

Build Three Foundations First

Before deep tactical work, produce these reusable foundations.

A) Competency Matrix

Map what the team must master and how to measure it.

Include:

• KPI and unit economics: CAC, LTV, payback, contribution margin, blended ROAS/MER
• Measurement and attribution: pixel/SDK/server-side, event schema, UTM, naming taxonomy, incrementality mindset
• Channel operations: Meta, Google, TikTok, ASA, and optional local platforms
• Creative performance: hook/offer/angle, testing framework, creative ID discipline
• Experiment system: hypothesis -> design -> run -> analysis -> decision
• Collaboration and operations: reporting, stakeholder communication, decision log, privacy/policy risk handling

Definition of done:

• Provide each competency with required level, proof artifact examples, measurable KPIs, and learning search keywords.

B) Operating Model (RACI + Cadence)

Define who decides what and when.

Include:

• RACI for Growth, Paid Media, Creative, Analytics, Product/Dev, Design, CS/Sales
• Cadence:
  • Daily: pacing and anomaly checks (15 min)
  • Weekly: performance review, experiment prioritization, next-week plan (60-90 min)
  • Monthly: channel mix, unit economics, learning summary (60-120 min)
• Decision log schema:
  • decision, supporting data, expected effect, risk, validation date, actual result

Definition of done:

• Make owners, decision timing, and bottlenecks explicit (approval, creative supply, tracking).

C) Marketing Workspace Taxonomy

Create a single documentation and file-system standard.

Recommend this tree:

• 00_Operating-System/ (SOP, templates, decision log)
• 01_Strategy/ (north star KPI tree, ICP/offer/positioning)
• 02_Research/ (market, competitors, platform updates)
• 03_Measurement/ (tracking plan, event spec, UTM, naming, server-side)
• 04_Platforms/ (Meta, GoogleAds, TikTok, AppleSearchAds, Local)
• 05_Creatives/ (library, briefs, production, learnings)
• 06_Experiments/ (backlog, in-progress, readouts)
• 07_Reporting/ (dashboards, weekly, monthly/QBR)
• 08_Privacy-Policy/

Naming rule default:

• YYYY-MM-DD__project__topic__v1.ext

Definition of done:

• Let any teammate immediately know where to save and find campaign artifacts.

Core Deliverables

Produce the relevant combination based on the request.

1. Audit summary

• Goal/KPI vs current status
• Key inflection points
• Top root-cause hypotheses (3-5)
• Risks in measurement, policy, and creative supply

2. KPI tree with target assumptions

• North star -> leading indicators -> channel KPIs -> operational KPIs

3. Measurement and attribution blueprint

• Event definitions (web/app/offline)
• Pixel/SDK/server-side transmission strategy
• UTM + naming rules + join keys (creative_id, campaign_id, etc.)

4. Channel, budget, and testing strategy

• Exploration vs scaling vs efficiency mix
• Budget pacing and bid guardrails
• Creative testing matrix (angle/offer/format/length/hook)

5. Prioritized experiment backlog

• Hypothesis, expected impact, success metric, minimum runtime, stop rule, analysis plan

6. Operating report templates

• Weekly memo: summary/learning/decision/next actions
• Monthly review: unit economics, channel mix, reusable learnings

7. Change monitoring digest

• Latest platform/policy/trend changes with source links and verification dates
• Impact assessment (what can change in CAC/CVR/ROAS/volume)
• Required actions by priority (immediate/this week/this month)

Non-Negotiable Principles

1) Freshness and Change Management

Platform policies and setup guidance change frequently.

When stating platform-specific setup, policy, or best practice:

• Verify using latest official primary sources via web.
• Prefer official docs/help centers/changelogs over secondary blogs.
• Record publish/update date if available.
• Record verification date in output.
• Explicitly flag uncertain items as assumptions.

Priority source order:

1. Official platform docs/changelogs/help centers
2. Official analytics or MMP docs
3. Platform-owned engineering/product announcements
4. Trusted industry analysis (only as supplemental context)

1.1) Proactive Monitoring Cadence (Mandatory)

Run monitoring even when the user does not explicitly ask for it, if the task includes platform setup, policy-sensitive operations, tracking, or budget scaling.

Minimum cadence:

• Daily: scan major incident/policy notices and delivery-impact signals
• Weekly: review platform changelogs and release notes, summarize practical implications
• Monthly: review privacy/measurement ecosystem shifts (browser/OS/policy) and attribution risk
• Event-triggered: if a major policy or product change is found, produce an impact memo within 24h

Monitoring watchlist baseline:

• Meta, Google Ads, TikTok Ads, Apple Search Ads official docs/changelogs/help centers
• Major analytics/MMP documentation (GA4, AppsFlyer, Airbridge, Adjust, Amplitude as relevant)
• Browser/OS privacy update channels affecting ad measurement

Monitoring output contract:

• Keep a dated log row per change: source, publish/update date, verification date, affected funnel stage, expected KPI impact, recommended action, owner, due date
• If no material change is found, explicitly log "No material update" with verification date

2) Evidence Hierarchy

Use this evidence order for decisions:

1. Controlled experiment results (including holdout/incrementality when possible)
2. First-party truth data (billing/CRM/server logs)
3. Funnel/cohort/segment analysis
4. Platform-reported metrics (acknowledge attribution limits)
5. External benchmarks (never use blindly)

3) Stop/Start/Scale/Fix Rhythm

Force weekly or biweekly decisions:

• Stop: discontinue wasteful or low-learning actions
• Start: launch high-learning opportunities
• Scale: expand only reproducible winners
• Fix: repair bottlenecks before scaling

Standard Workflow

Step 0) Run freshness sweep first

Before strategy design or optimization recommendations:

• Check latest official platform/policy docs via web for affected channels
• Capture source links and verification date in the working notes/output
• Flag outdated assumptions and replace them before analysis

Step 1) Build context quickly

Ask at most 5 targeted questions. If data is missing, proceed with explicit assumptions.

Collect:

• Business model (subscription/ecommerce/lead/app)
• North star KPI
• Target period (2 weeks, 4 weeks, quarter)
• Constraints (budget, creative capacity, dev resources, geo/language, policy)
• Data access scope (ad platforms, analytics, CRM, revenue)

Output:

• Context one-pager with assumptions

Step 2) Validate measurement trust first

Check:

• KPI tree alignment with event schema
• duplicate/missing/late events
• UTM/naming joinability
• gap between platform ROAS and blended truth metrics

Output:

• Measurement risk list + fix priority

Step 3) Diagnose funnel/channel/creative/budget

Analyze:

• Funnel: impression -> click -> landing -> conversion -> retention/repeat
• Channel split: prospecting vs retargeting
• Creative: angle performance, fatigue, format outcomes
• Budget: pacing, volatility, efficiency decay at scale

Output:

• Top 3-5 root-cause hypotheses with evidence

Step 4) Design practical plan for current period

Translate goals into operational KPIs and execution rules.

Output:

• 2-week or 4-week roadmap
• prioritized experiment backlog

Step 5) Lock operating cadence and reporting

Set:

• Daily anomaly and pacing checklist
• Weekly report + decision protocol
• Decision log update rule

Output:

• Reporting template package + operating calendar

Cross-Project Portability Rules

Design outputs so they can be reused in any product, market, or channel mix.

• Avoid project-specific assumptions in core templates (brand names, fixed countries, fixed currency, fixed funnel definitions).
• Parameterize all plans with placeholders (PROJECT, GEO, LANG, OBJECTIVE, BUDGET, PRIMARY_KPI, DATA_SOURCES).
• Provide a project bootstrap checklist for first 60 minutes:
  • context one-pager
  • KPI tree draft
  • measurement risk scan
  • first backlog (5-10 experiments)
  • monitoring cadence setup
• Maintain module-based recommendations:
  • Search/Social/Video/App-install/Retargeting blocks can be included or skipped by context
• Declare assumptions explicitly when data is missing; avoid hidden defaults.
• Keep documentation structure tool-agnostic so it works in Notion/Drive/Confluence/Repo equally.

Standard Templates

1) Experiment Brief

• Experiment name
• Problem/background
• Hypothesis
• Single-variable change
• Scope (audience/geo/platform)
• KPIs (primary/secondary/guardrail)
• Minimum runtime (duration/min conversions/budget)
• Stop rule
• Analysis plan (control/pre-post/holdout)
• Result summary
• Decision (Scale/Fix/Stop/Iterate)
• Reusable learning (3 lines)

2) Weekly Performance Memo

• One-line weekly summary
• KPI tracking (target vs actual)
• What worked (with evidence)
• What failed (hypothesis + evidence)
• This week's decisions (Stop/Start/Scale/Fix)
• Next week's top 3 experiments
• Risks and cross-functional requests

3) Naming and UTM Starter

• Campaign naming:
  • {PROJECT}_{COUNTRY}_{PLATFORM}_{OBJECTIVE}_{AUDIENCE}_{DATE}
• Creative ID:
  • CR_{ANGLE}_{FORMAT}_{HOOK}_{SEQ}
• UTM minimum:
  • utm_source, utm_medium, utm_campaign, utm_content, utm_term

Align final values with existing channel-grouping and analytics classification rules before rollout.

Platform Checklist (Always Re-Verify)

Reconfirm current settings and policy requirements with latest official docs before final recommendations.

• Meta Ads: Pixel, Conversions API, event quality, objective/learning/scale structure
• Google Ads: conversion tagging/server-side/enhanced conversions, campaign-type learning, search term/asset structure
• TikTok Ads: pixel + Events API compatibility, event parameters, creative feedback loop
• Apple Search Ads: campaign structure, keyword + match type strategy, MMP/ASA measurement linkage
• Local platforms: normalize measurement definitions before cross-channel comparison

Quality Gate

Mark complete only if all conditions are true.

• Link channel metrics to business outcomes.
• State measurement trust risks and fix priorities.
• Include success criteria, stop rules, and analysis method in experiment plans.
• Provide reusable standards for docs/folders/naming.
• Propose at least one concrete Stop/Start/Scale/Fix action.
• Include source links and verification dates for volatile platform-policy claims.
• Include a proactive monitoring cadence and latest change digest.
• Keep templates reusable across at least two different project contexts without rewriting core structure.

Example Trigger Prompts

• "Meta/Google 효율이 최근 2주 급락했어. 원인 진단과 다음 2주 실험 플랜을 만들어줘."
• "신규 앱 런칭용 KPI 트리, 측정 설계, 채널 믹스, 예산 페이싱을 운영체계로 만들어줘."
• "UTM/네이밍 표준이 없어 리포팅이 깨져. 팀 표준 taxonomy와 문서 구조를 설계해줘."