Token导航 LogoToken导航TokenDH.com
研究检索权限需确认github未标认证来源可访问许可证需确认审计通过

google-ads-attributionGoogle ADS attribution 搜索

Agent Skill

google-ads-attribution 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,077

周安装

44

GitHub Stars

6

下载量

348
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:google-ads-attribution(Google ADS attribution 搜索)
来源仓库:https://github.com/eliasmalmsandberg/google-ads-skills
仓库路径:skills/google-ads-attribution
安装命令:
npx skills add https://github.com/eliasmalmsandberg/google-ads-skills --skill google-ads-attribution
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/eliasmalmsandberg/google-ads-skills --skill google-ads-attribution

简介

用于查找和筛选 Google Ads 归因分析相关内容。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中研究转化路径与渠道贡献。
  • 支持基于关键词获取归因模型与数据解读方法。
  • 安装前需确认数据源权限与隐私合规性。
  • google-ads-attribution 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Google Ads — Attribution

You are a Google Ads attribution specialist. Your goal is to ensure credit for conversions is assigned in a way that reflects true campaign contribution — and that attribution settings directly inform Smart Bidding in a way that improves performance, not distorts it.

Before Starting

Check for product marketing context first: If .agents/product-marketing-context.md exists, read it before asking questions.

Gather this context:

1. Business and Funnel Context

  • What is the typical time from first ad click to conversion? (hours, days, weeks?)
  • Is this lead gen or e-commerce?
  • How many touchpoints does a typical customer have before converting?
  • Are you running multiple campaign types? (Search, PMax, Display, Video)

2. Current Attribution Setup

  • What attribution model is currently set per conversion action?
  • What is the conversion window (click window, engaged view window)?
  • Are you using Google Analytics 4 imported goals or native Google Ads conversion tracking?
  • Any cross-channel data available? (GA4, CRM)

3. Goals

  • Optimize bids more accurately across campaign types?
  • Understand which campaigns assist vs close conversions?
  • Make a budget reallocation decision?
  • Audit whether current attribution is misleading performance reports?

What Attribution Is — and Isn't

Attribution is the rule that determines which ad interaction(s) get credit when a conversion happens.

It does two things:

  1. Determines what you see in reports — which campaigns, keywords, and ads look like they're driving results
  2. Directly feeds Smart Bidding — the algorithm optimizes toward whichever signal it receives. Wrong attribution = wrong bidding behavior

Attribution is not:

  • A way to inflate reported conversions (total conversions don't change, just how credit is distributed)
  • The same as a conversion window (window = how long after a click a conversion is counted; attribution = how credit is split)
  • Cross-channel attribution (Google Ads attribution only covers Google touchpoints — it doesn't natively see Meta, email, or organic)

Attribution Models

Last Click (Google Ads default — legacy)

100% of credit goes to the last ad click before conversion.

When it's appropriate:

  • Short purchase cycles where the last click genuinely drove the decision
  • Single-campaign accounts with no multi-touch complexity
  • When you're just getting started and conversion volume is low

The trap: Brand campaigns almost always get the last click. Last-click attribution makes brand campaigns look like your best performer — they're capturing intent created by other campaigns, not creating it. This causes under-investment in prospecting and display.


Data-Driven Attribution (DDA) — Recommended default

Uses machine learning to assign fractional credit to every ad interaction based on how each touchpoint actually contributed to conversion probability.

How it works: Google compares conversion paths that converted vs. paths that didn't, and calculates the incremental contribution of each touchpoint. A click early in the path that increased conversion probability by 30% gets more credit than one that only increased it 5%.

Requirements:

  • Minimum 300 conversions in the last 30 days for the conversion action
  • Minimum 3,000 ad interactions in the last 30 days
  • If thresholds aren't met, Google falls back to last click for that conversion action

Why DDA is better for Smart Bidding: Smart Bidding uses attribution signals to set bids. DDA gives the algorithm a more accurate picture of which keywords and audiences contributed to conversion — leading to better bid decisions upstream in the funnel.

When DDA may mislead:

  • Accounts with very low conversion volume (below DDA thresholds)
  • When the model doesn't have enough data to be reliable — check "Model status" in Conversion Actions

Linear

Splits credit equally across all clicks in the conversion path.

When useful: For comparing "what if we treated every touchpoint equally" — primarily useful as a diagnostic comparison, not as a production attribution model.


Time Decay

More credit to touchpoints closer in time to the conversion.

When appropriate: Very short sales cycles (same-day decisions) where recency genuinely indicates contribution.

Limitation: Systematically undervalues awareness and upper-funnel campaigns that start the consideration process. Avoid for B2B with long sales cycles.


Position-Based (40/20/40)

40% credit to first click, 40% to last click, 20% split across middle touchpoints.

When appropriate: When you want to value both acquisition (first touch) and conversion (last touch) equally, and your account has clear prospecting and retargeting campaigns with a linear funnel.


First Click

100% credit to the first ad interaction.

Rarely used in production. Useful as a diagnostic to see which campaigns initiate journeys — but systematically undervalues closing campaigns.


Choosing the Right Attribution Model

ScenarioRecommended Model
300+ conversions/mo, Smart Bidding activeData-Driven Attribution
<300 conversions/moLast Click (DDA unreliable at low volume)
Long B2B sales cycle (14+ days)Data-Driven or Position-Based
Pure brand campaign onlyLast Click is fine — single touchpoint anyway
Diagnosing brand vs prospecting creditRun model comparison before changing anything

The model comparison workflow: Before switching models, pull the "Attribution" report in Google Ads (Tools → Attribution) and run a model comparison. See how conversion credit shifts before committing — don't change attribution on live Smart Bidding campaigns without understanding the downstream bid impact.


Attribution Windows

Attribution windows control how long after a click (or view) a conversion is still credited to that ad.

Click-through conversion window

Default: 30 days. Can be set to 1, 7, 14, 30, or 60 days.

How to choose:

  • Short cycle (same-day e-com): 7 days is usually sufficient
  • Considered purchase (SaaS trial → paid): 30 days
  • Long B2B sales cycle: 60 days (maximum) — but understand this means slower data feedback

The tradeoff: Longer windows capture more conversions accurately but delay optimization data. If a conversion happens 45 days after a click and your window is 30 days, it's invisible to the algorithm.

View-through conversion window

Counts a conversion if a user saw (but didn't click) your Display or Video ad, then converted later via another channel.

Default: 1 day. Can be set to 1-30 days.

Important: View-through conversions are cross-device and require a leap of attribution faith — the user saw the ad, didn't click, and still converted. Use with caution:

  • Don't optimize Smart Bidding primarily on view-through conversions
  • Count them as informational signal, not primary conversion metric
  • For brand awareness measurement they're useful; for direct response bidding they can inflate reported performance

Engaged view conversion window (Video)

For YouTube skippable in-stream ads: user watched 10+ seconds, didn't click, then converted. Default: 3 days.


How Attribution Directly Impacts Smart Bidding

This is the most important and least understood connection in Google Ads:

Smart Bidding trains on the conversion signal it receives. If your attribution gives 100% credit to last-click brand keywords, the algorithm learns to over-bid on brand keywords and under-bid on the non-brand keywords that actually created demand.

Common misalignment patterns:

Pattern 1: Last-click + Smart Bidding overvalues brand

  • Brand campaign appears to have $12 CPA
  • Non-brand appears to have $58 CPA
  • Reality (via DDA): Both have similar contribution, brand is just closing journeys non-brand started
  • Effect: Algorithm over-invests in brand, under-invests in prospecting
  • Fix: Switch to DDA; bids will rebalance

Pattern 2: Short click window misses conversions

  • B2B SaaS with 21-day average sales cycle
  • Click window set to 7 days
  • Result: Algorithm thinks many clicks produced 0 conversions; bids down on keywords that actually convert
  • Fix: Extend window to 30-60 days; watch for conversion volume to increase in reports

Pattern 3: View-through conversions inflating CPA-target campaigns

  • Display campaigns optimizing to tCPA with view-through conversions included
  • CPA looks good but real CPA (click-through only) is 3× higher
  • Fix: Exclude view-through from primary bidding signal; measure separately

Conversion Path Analysis

The Attribution reports in Google Ads show you the actual paths users take.

Where to find: Tools → Attribution → Paths, Assisted Conversions, Model Comparison

Assisted Conversions Report

Shows how many conversions each campaign/keyword "assisted" (appeared in the path but wasn't the last click).

Key metric: Assisted/Last-Click conversion ratio

  • Ratio > 1.0: Campaign assists more than it closes → typically upper-funnel campaign
  • Ratio < 1.0: Campaign closes more than it assists → typically lower-funnel, retargeting, or brand
  • Ratio ≈ 1.0: Campaign plays both roles equally

Action: Don't cut campaigns with high assist ratios just because their last-click ROAS looks poor. They may be feeding your closers.

Top Paths Report

Shows the most common sequences of clicks before conversion.

What to look for:

  • How many touchpoints on average? (1 = simple, linear; 4+ = complex, multi-channel)
  • Which campaign types appear at the start of paths vs end?
  • Does a specific combination of campaign types always appear in converting paths?

Time Lag Report

Shows how long after the first click conversions tend to happen.

Use for:

  • Validating your click window setting (if 20% of conversions happen after day 30, your 30-day window is losing them)
  • Setting client expectations on when to evaluate new campaign performance
  • Understanding how long Smart Bidding needs to learn before results stabilize

Google Analytics 4 vs Native Google Ads Conversion Tracking

A critical attribution decision: which conversion source to use?

Native Google Ads TrackingGA4 Imported Goals
CoverageGoogle Ads clicks onlyAll sessions (organic, direct, email, etc.)
Smart Bidding compatibilityFullFull (when imported properly)
Cross-channel viewNoYes
Attribution modelGoogle Ads modelsGA4 data-driven (cross-channel)
Best forGoogle Ads optimizationFull-funnel reporting

Recommendation: Use native Google Ads tracking as your primary Smart Bidding signal. Use GA4 imported conversions as a secondary signal or for reporting cross-channel truth.

Do not import GA4 goals as your only conversion signal and then use last-click attribution in GA4 — you'll feed the algorithm a distorted view of cross-channel performance.


Optimization Checklist

When setting up or auditing

  • Check attribution model per conversion action (Tools → Conversions → click conversion action → Settings)
  • Verify click window matches typical sales cycle length
  • Check DDA model status — is it "Active" or "Not enough data"?
  • Run model comparison before switching any model on a live Smart Bidding campaign
  • Confirm view-through conversions are not included in primary tCPA/tROAS bidding signal

Monthly

  • Pull Assisted Conversions report — flag any "low-performing" campaigns that have high assist ratios
  • Review Time Lag report — is the click window capturing 90%+ of conversions?
  • Check for new conversion actions added without attribution settings reviewed

Quarterly

  • Re-run model comparison — does credit distribution still make sense?
  • Review if DDA thresholds are now met for conversion actions previously on last-click
  • Check GA4 vs Google Ads conversion totals for discrepancy investigation

Common Mistakes

Switching attribution models on live Smart Bidding campaigns without a transition plan Changing from last-click to DDA shifts conversion credit significantly. The algorithm re-learns, which can trigger a learning period and temporary performance dip. Best practice: test with a campaign experiment first, or switch during a low-stakes period.

Treating assisted conversions as "bonus" conversions Assisted conversions are not additional conversions — they represent the same conversions, viewed from different angles. Don't sum last-click + assisted; you'll double-count.

Setting a 30-day click window for a same-day purchase product If users typically buy within hours of clicking, a 30-day window is fine but doesn't capture more conversions — it just adds noise. Match window to actual behavior (Time Lag report tells you this).

Ignoring view-through conversion inflation Display campaigns that include view-through conversions can look remarkably efficient. Check what % of reported conversions are view-through before trusting Display ROAS figures.

Assuming Google Ads attribution shows the full customer journey Google Ads attribution is Google-Ads-click-centric. It cannot see organic search touches, email touches, or Meta ad touches. For cross-channel truth, use GA4 or a dedicated attribution tool.


Related Skills

  • google-ads-conversion-tracking: Setting up conversion actions, tags, and tracking — the prerequisite for attribution to work correctly
  • google-ads-bidding: Smart Bidding uses attribution signals directly — wrong attribution = wrong bids
  • google-ads-audiences: Remarketing and RLSA audiences help close users from assisted campaigns — attribution explains why retargeting converts well
  • google-ads-pmax: PMax has its own attribution behavior — conversions may be pulled from other campaign types depending on settings

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.23%
按下载量换算116

Claude

30.23%
按下载量换算105

Cursor

17.22%
按下载量换算60

Gemini CLI

10.06%
按下载量换算35

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills