Tenjin面板包含哪些指标？ #
Tenjin 面板默认提供了多种常用指标及分析，供营销人员更好的决策。
Metric Tooltips 指标提示
将鼠标悬停在面板上的指标名称附近，就可以查看其定义和公式说明。
指标分类
你可以在 Edit Metrics 下看到指标的各种分类，迅速找到并添加您需要的指标。
以下是 Tenjin 面板上的常见指标清单。
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指标清单 #
用户增长-指标 #
| report type | abbreviated name | full name | description |
|---|---|---|---|
| UA | IAP Rev | IAP Revenue | Total In App Purchase Amount ($) |
| UA | IAP ARPDAU | IAP Revenue Per Daily Active Users | Average amount of IAP Revenue per DAU ($) |
| UA | In App Purchase LTV | In App Purchase LTV | Average In App Purchase Amount ($) |
| UA | In App Purchase LTV / User | In App Purchase LTV / User | Average In App Purchase LTV per User Amount ($) |
| UA | N-Day IAP LTV ｜N日内购LTV | N-Day IAP LTV ｜N日内购LTV | Cumulative IAP revenue N days after Install |
| UA | N-Day IAP LTV / User ｜ 平均用户N日内购LTV | N-Day IAP LTV / User ｜ 平均用户N日内购LTV | Average N-Day In App Purchase LTV per User Amount ($) |
| UA | N-Day IAP ROAS | N-Day Ad ROAS | Average N-Day ROAS Percentage (%) Amount of cumulative IAP revenue N days after Install divided by spend |
| UA | N-Day IAP ROI | N-Day Ad ROI | Average N-Day ROI Percentage (%) Amount of cumulative profit (IAP revenue N days after Install – spend) divided by spend |
| UA | Lifetime IAP ROI（全生命周期内购ROI） | Lifetime IAP ROI（全生命周期内购ROI） | Average In App Purchase ROI Percentage (%) |
| UA | IAP Profit Margin | IAP Profit Margin | IAP Revenue – Spend |
| UA | Ad Revenue (Ad Network) | Ad Revenue (Ad Network) | Total Ad Revenue Amount estimated by Tenjin ($) |
| UA | Ad Revenue (Ad Mediation) | Ad Revenue (Ad Mediation) ｜广告聚合收入 | Total Ad Mediation Value ($) |
| UA | Ad ARPDAU (Ad Network) | Ad Revenue Per Daily Active Users (Ad Network) | Average amount of Ad Revenue per DAU ($) |
| UA | Ad ARPDAU (Ad Mediation) | Ad Revenue Per Daily Active Users (Ad Mediation) | Average amount of Ad Mediation Revenue per DAU ($) |
| UA | Ad Revenue LTV (Ad Network) | Ad Revenue LTV (Ad Network) | Total Ad Revenue LTV Amount estimated by Tenjin ($) |
| UA | Ad Revenue LTV / User (Ad Network) | Ad Revenue LTV / User (Ad Network) | Total Ad Revenue estimated by Tenjin per User Amount ($) |
| UA | Ad Revenue LTV / User (Ad Mediation) | Ad Mediation LTV / User (Ad Mediation) | N-Day Ad Mediation LTV per user ($) |
| UA | N-Day Ad LTV (Ad Network) | N-Day Ad Revenue LTV (Ad Network) | Cumulative ad revenue N days after Install |
| UA | N-Day Ad LTV (Ad Mediation) ｜ N日广告LTV（聚合） | N-Day Ad Revenue LTV (Ad Mediation) | Cumulative Ad Mediation revenue N days after Install ($) |
| UA | N-Day Ad LTV / User (Ad Network) | N-Day Ad Revenue LTV / User (Ad Network) | Average N-Day Ad Revenue LTV estimated by Tenjin per User Amount ($) |
| UA | N-Day Ad ROAS (Ad Network ) | N-Day Ad ROAS (Ad Network) | Average N-Day ROAS Percentage (%) Amount of cumulative ad revenue (Ad Network) N days after Install divided by spend |
| UA | N-Day Ad ROAS (Ad Mediation ) | N-Day Ad ROAS (Ad Mediation) | Average N-Day ROAS Percentage (%) Amount of cumulative ad revenue (Ad Mediation) N days after Install divided by spend |
| UA | N-Day Ad ROI (Ad Network) | N-Day Ad ROI (Ad Network) | Average N-Day ROI Percentage (%) Amount of cumulative profit (ad revenue (Ad Network) N days after Install – spend) divided by spend |
| UA | N-Day Ad ROI (Ad Mediation) | N-Day Ad ROI (Ad Mediation) | Average N-Day ROI Percentage (%) Amount of cumulative profit (ad revenue (Ad Mediation) N days after Install – spend) divided by spend |
| UA | Lifetime Ad ROI (Ad Network) | Lifetime Ad ROI (Ad Network) | Average Ad Network revenue ROI Percentage (%) |
| UA | Lifetime Ad ROI (Ad Mediation) | Lifetime Ad ROI (Ad Mediation) | Average Ad mediation revenue ROI Percentage (%) |
| UA | Ad Revenue Profit Margin (Ad Mediation) | Ad Revenue Profit Margin (Ad Mediation) | Ad Revenue (Ad Mediation) – Spend |
| UA | Ad Revenue Profit Margin (Ad Network) | Ad Revenue Profit Margin (Ad Network) | Ad Revenue (Ad Network) – Spend |
| UA | All Revenue (Ad Network + IAP) | All Revenue (Ad Network + IAP) | All Revenue Amount (IAP + Ad Network) ($) |
| UA | All ARPDAU (Ad Revenue + IAP) | All Revenue per Daily Active Users (Ad Revenue + IAP) | Average amount of All Revenue (IAP + Ad Network) per DAU ($) |
| UA | All ARPDAU (Ad Mediation + IAP) | All Revenue Per Daily Active Users All ARPDAU (Ad Revenue + IAP) | Average amount of All Ad Revenue (Ad Mediation + IAP) per DAU |
| UA | N-Day All LTV (Ad Network + IAP) | N-Day All LTV (Ad Network + IAP) | Cumulative all revenue (IAP + Ad Network) N days after the Install |
| UA | N-Day All LTV (Ad Mediation + IAP) | N-Day All LTV (Ad Mediation + IAP) | Cumulative all revenue (IAP + Ad Mediation) N days after the Install |
| UA | N-Day All LTV / User (Ad Network + IAP) | N-Day All LTV / User (Ad Network + IAP) | Cumulative all revenue (IAP + Ad Network) N days after Install divided by total users on 0-Day |
| UA | N-Day All ROI (Ad Mediation + IAP) ｜N-Day总ROI (广告变现+内购) | N-Day All Ad Mediation LTV / User (Ad Mediation + IAP) | Cumulative all revenue (IAP + Ad Mediation) N days after Install divided by tracked installs |
| UA | All LTV (Ad Network + IAP) | All LTV (Ad Network + IAP) | All LTV (IAP + Ad Revenue) |
| UA | All LTV (Ad Mediation + IAP) | All LTV (Ad Mediation + IAP) | All LTV (Ad Mediation + IAP) |
| UA | All LTV / User (Ad Network + IAP) | All LTV / User (Ad Network + IAP) | All Revenue (IAP + Ad Network) per User Amount ($) |
| UA | All LTV / User (Ad Network + IAP) | All LTV / User (Ad Network + IAP) | All Revenue (IAP + Ad Network) per User Amount ($) |
| UA | N-Day All ROAS (Ad Network + IAP) | N-Day All ROAS (Ad Network + IAP) | Average N-Day ROAS Percentage (%) Amount of cumulative all revenue (Ad Network + IAP) N days after Install divided by spend |
| UA | N-Day All ROAS (Ad Mediation + IAP) ｜N-Day广告聚合ROAS （广告变现+内购） | N-Day All ROAS (Ad Mediation + IAP) ｜N-Day广告聚合ROAS （广告变现+内购） | Average N-Day ROAS Percentage (%) Amount of cumulative Ad Mediation revenue + IAP N days after Install divided by spend |
| UA | N-Day All ROI (Ad Network + IAP) | N-Day All ROI (Ad Network + IAP) | Average N-Day ROI Percentage (%) Amount of cumulative total profit (all revenue (Ad Network + IAP) N days after Install – spend) divided by spend |
| UA | N-Day All ROI (Ad Mediation + IAP) ｜N-Day总ROI (广告变现+内购) | N-Day All Ad Mediation ROI (Ad Mediation + IAP) | Average N-Day ROI Percentage (%) Amount of cumulative Ad Mediation + IAP Revenue (Total Revenue N days after Install – spend) divided by spend |
| UA | Lifetime All ROI (Ad Network + IAP) | Lifetime All ROI (Ad Network + IAP) | Average Lifetime ROI (Ad Network + IAP) Percentage (%) |
| UA | Lifetime All ROAS (Ad Network + IAP) | Lifetime All ROAS (Ad Network + IAP) | Average Lifetime All ROAS Percentage (%) |
| UA | Lifetime All ROI (Ad Mediation + IAP) | Lifetime All ROI (Ad Mediation + IAP) | Lifetime All ROI (Ad Mediation + IAP) |
| UA | Lifetime All ROAS (Ad Mediation + IAP) | Lifetime All ROAS (Ad Mediation + IAP) | Lifetime All ROAS (Ad Mediation + IAP) |
| UA | (Ad Mediation + IAP), 也就是N日总预测广告变现LTV | (Ad Mediation + IAP), 也就是N日总预测广告变现LTV | Cumulative predicted revenue (IAP + Ad Mediation Revenue) N-Days after Install (Currently up to 30-Days cohorts supported) |
| UA | N-Day All pROAS (Ad Mediation + IAP) | N-Day All pROAS (Ad Mediation + IAP) | Average N-Day Predicted ROAS Percentage (%) Amount of cumulative All pLTV (Ad Mediation + IAP) N days after Install divided by spend (Currently up to 30-Days cohorts supported) |
| UA | N-Day All pROI (Ad Mediation + IAP) | N-Day All pROI (Ad Mediation + IAP) | Average N-Day Predicted ROI Percentage (%) Amount of cumulative (All pLTV (Ad Mediation + IAP) N days after Install – spend) divided by spend (Currently up to 30-Days cohorts supported) |
| UA | All Profit Margin (Ad Mediation + IAP) | All Profit Margin (Ad Mediation + IAP) | All Revenue (Ad Mediation + IAP) – Spend |
| UA | All Profit Margin (Ad Network + IAP) | All Profit Margin (Ad Network + IAP) | All Revenue (Ad Network + IAP) – Spend |
| UA | DAU | Daily Active Users | Number of unique users (advertising_id) per day |
| UA | N-Day Users | N-Day Retained Users | Total number of users retained after N-Day of installing the app |
| UA | Lifetime Ret | Lifetime Retention | Cohorted N-day Retention Rate |
| UA | N-Day Ret % | N-Day Retention Rate | Average N-Day Retention Rate Percentage (%) |
| UA | Total Fraud Events | Total Fraud Events | Sum of blocked clicks and fradulent purchases |
| UA | Blocked Clicks | Blocked Clicks | The number of clicks we blocked based on mean time to Install(MTTI). We currently use 1 second for the MTTI threshold as default. |
| UA | Blocked Device Events | Blocked Device Events | Number of test device events |
| UA | Fradulent Purchases | Fraudulent Purchases | Number of purchases marked as fradulent |
| UA | Blocked Fradulent Rev | Blocked Fraudulent Revenue | Total Blocked Fraudulent Revenue Amount ($) |
| UA | Reported Clicks 报告点击 | Reported Clicks 报告点击 | Number of times the ad was clicked reported by Ad Networks |
| UA | Clicks Diff | Clicks Difference | Total Clicks Difference. Formula : Reported Clicks – Tracked Clicks |
| UA | Clicks Difference Percent | Clicks Difference Percent | Average Clicks Difference Percentage (%) Formula : 100 – 100 * Tracked Clicks / Reported Clicks |
| UA | Lifetime Cost / User | Lifetime Cost per Retained User | Cohorted Cost Per N-Day Retained User |
| UA | CPC | Cost-Per-Click (CPC) | Average CPC Amount ($) spend/reported clicks |
| UA | CPI | Cost-Per-Install (CPI) | Average CPI Amount ($) spend/Reported Installs |
| UA | CPM | Cost-Per-1000-Impressions (CPM) | Average CPM Amount ($) 1000 * spend/reported impressions |
| UA | CPR | Completion Rate (CPR) | Average CPR Percentage (%) 100 * Reported Installs / reported impressions |
| UA | CTR | Click-Through-Rate (CTR) | Average CTR Percentage (%) 100* reported clicks / reported impressions |
| UA | CVR | 转换率 (CVR) | Average CVR Percentage (%) 100 * Reported Installs / reported clicks |
| UA | Impressions | Reported Impressions 报告展示 | Number of times your ad was displayed |
| UA | Reported installs 报告安装 | Reported installs 报告安装 | Number of installs reported by Ad Networks |
| UA | Installs Diff | Installs Difference | Total Installs Difference. Reported Installs – Tracked Installs |
| UA | Installs Difference Percent | Installs Difference Percent | Average Installs Difference Percentage (%). 100 – 100 * Tracked Installs / Reported Installs |
| UA | Impressions (Ad Mediation) | 展示次数（广告聚合） | Total impressions in the given time period | Total impressions in the given time period |
| UA | IMPDAU (Ad Mediation) | 日活用户平均展示次数（广告聚合） | Average impressions per user in the given time period | Total Impressions divided by Total Daily Active Users |
| UA | Lifetime Active Days / User | Lifetime Active Days per User 单用户活跃天数 | Average number of active days for a user |
| UA | Sessions | Sessions | Average Sessions |
| UA | Lifetime Sess / User | Lifetime Sessions Per User | Average Sessions per User |
| UA | Spend 花费 | Spend 花费 | Amount spent to acquire users (in USD) |
| UA | tCPI | Cost-Per-Tracked Install (tCPI) | Average tCPI Amount ($) spend / tracked installs |
| UA | Tracked Clicks | Tracked Clicks | Number of times your ad was clicked (Tenjin tracked) |
| UA | Tracked CVR | Tracked Conversion Rate (CVR) | Average CVR Percentage (%) 100 * tracked installs / tracked clicks |
| UA | Tracked Impressions | Tracked Impressions | Number of impressions tracked by Tenjin |
| UA | Tracked Installs ｜ 追踪激活 | Tracked Installs ｜ 追踪激活 | Number of Installs tracked by Tenjin |
| UA | Tracked Reinstalls | Tracked Reinstalls | Number of Reinstalls tracked by Tenjin |
| UA | CP N-Day User | 每 N 天留存用户的成本 | Cost per users that comes back N days after Install (installs here are reported by the Ad Network). Formula – spend * (users_0d/Reported Installs) / users_Nd |
| UA | N-Day Sess | N-Day Sessions | Number of times an app was opened after post Install on the day of Install (N day) |
| UA | CP K N-Day Sessions | Cost per 1000 N-Day Sessions | Average Cost per 1000 N-Day Sessions Amount ($) |
| UA | Purchasers | Unique Purchasers | Number of the unique purchasers |
| UA | Transactions | Purchase Transactions | Number of the total purchase counts |
| UA | N-Day Cost / Purchase | N-Day Cost Per Purchase Transactions | Cost divided by cumulative total purchase counts N days after the Install |
| UA | N-Day Cost / Purchaser | N-Day Cost Per Returning Purchaser | Cost divided by returning purchase user N days after the Install |
| UA | N-Day Cumul Revenue | N-Day Cumulative Purchase Revenue | Cumulative purchase revenue N days after the Install |
| UA | N-Day Revenue / User | N-Day Cumulative Purchase Revenue per Acquired User | Cumulative purchase revenue N days after the Install, divided by the number of acquired users |
| UA | N-Day Cumul Txns | N-Day Cumulative Purchase Transactions | Cumulative purchase counts N days after the Install |
| UA | N-Day Txns per User | N-Day Cumulative Purchase Transactions per Acquired User | Cumulative purchase counts N days after the Install, divided by the number of acquired users |
| UA | N-Day Participation | N-Day Purchaser Participation | Percent of unique purchasers N days after the Install out of the number of acquired users |
| UA | N-Day Purchasers | N-Day Unique Purchasers | Cumulative unique purchasers N days after the Install |
| UA | Average | Average Purchase Value per Transaction | Total purchase revenue, divided by total purchase counts |
| UA | Revenue 收入 | Purchase Revenue | Total purchase revenue |
Ad Monetization Metrics #
| report type | abbreviated name | full name | description |
|---|---|---|---|
| AM | Reported Ad Revenue 报告广告收入 | Reported Ad Revenue 报告广告收入 | Total Ad Revenue reported by Ad Network ($) |
| AM | eCPC | Effective Cost per Click (eCPC) | Ad Revenue per Click ($) |
| AM | 什么是移动营销里的eCPM，以及如何计算？ | Effective Cost per Mille (eCPM) | Ad Revenue per 1000 Impressions ($) |
| AM | Reported Clicks 报告点击 | Reported Clicks 报告点击 | Total Clicks reported by Ad Network |
| AM | Impressions | Reported Impressions 报告展示 | Total Impressions reported by Ad Network |
SKAdNetwork Metrics #
| report type | abbreviated name | full name | description |
|---|---|---|---|
| SKAN | Conversions | Conversions | Number of Conversion postbacks forwarded by Ad Networks (includes redownloads and first downloads) |
| SKAN | Conversion Value Average | Conversion Value Average | Average of Conversion Values forwarded by Ad Networks (includes redownloads and first downloads) |
| SKAN | Conversion Value Total | Conversion Value Total | Sum of Conversion Values forwarded by Ad Networks (includes redownloads and first downloads) |
| SKAN | Ad Network SKAN Installs | Ad Network SKAN Installs | Number of Conversion postbacks received for first downloads forwarded by Ad Networks |
| SKAN | First Download CV Avg | First Download Conversion Value Average | Average Conversion Value for first downloads forwarded by Ad Networks |
| SKAN | First Download CV Total | First Download Conversion Value Total | Sum of Conversion Values for first downloads forwarded by Ad Networks |
| SKAN | Redownloads | Redownloads | Number of Conversion postbacks received for redownloads forwarded by Ad Networks |
| SKAN | Redownload CV Avg | Redownload Conversion Value Average | Average Conversion Value for redownloads forwarded by Ad Networks |
| SKAN | Redownload CV Total | Redownload Conversion Value Total | Sum of Conversion Values for redownloads forwarded by Ad Networks (includes redownloads and first downloads) |
| SKAN | Assists | Assists | Ad Network forwarded ad impressions that were shown to a user that ultimately downloaded the app, but were not awarded with an Attribution. Introduced in SKAdNetwork 3.0, this corresponds to postbacks with did-win=false. |
| SKAN | Redownload Assists | Redownload Assists | Number of Assist postbacks received for redownloads forwarded by Ad Networks |
| SKAN | First Download Assists | First Download Assists | Number of Assist postbacks received for first downloads forwarded by Ad Networks |
| SKAN | Apple Conversions | Apple Conversions | Number of Conversion postbacks forwarded by Apple (includes redownloads and first downloads) |
| SKAN | Apple Conversion Value Average | Apple Conversion Value Average | Average of Conversion Values forwarded by Apple (includes redownloads and first downloads) |
| SKAN | Apple Conversion Value Total | Apple Conversion Value Total | Sum of Conversion Values forwarded by Apple |
| SKAN | Apple SKAN安装数 | Apple SKAN安装数 | Number of Conversion postbacks received for first downloads forwarded by Apple |
| SKAN | Apple First Download CV Avg | Apple First Download CV Avg | Average Conversion Value for first downloads forwarded by Apple |
| SKAN | Apple First Download CV Total | Apple First Download CV Total | Sum of Conversion Values for first downloads forwarded by Apple |
| SKAN | Apple Redownloads | Apple Redownloads | Number of Conversion postbacks received for redownloads forwarded by Apple |
| SKAN | Apple Redownload CV Avg | Apple Redownload CV Avg | Average Conversion Value for redownloads forwarded by Apple |
| SKAN | Apple Redownload CV Total | Apple Redownload Conversion Value Total | Sum of Conversion Values for redownloads forwarded by Apple |
| SKAN | Apple Assists | Apple Assists | Apple forwarded ad impressions that were shown to a user that ultimately downloaded the app, but were not awarded with an Attribution. Introduced in SKAdNetwork 3.0, this corresponds to postbacks with did-win=false. |
| SKAN | Apple Redownload Assists | Apple Redownload Assists | Number of Assist postbacks received for redownloads forwarded by Apple |
| SKAN | Apple First Download Assists | Apple First Download Assists | Number of Assist postbacks received for first downloads forwarded by Apple |
报告类型：
UA: User Acquistion 用户获取
AM: Ad Monetization 广告变现
SKAN: SKAdNetwork
所有的N日指标都是基于归因分群（Cohort）的指标，并按用户获取日期（Acquisition Date）进行分组。其他非Cohort类指标则按日历日期（Calendar Date）分组。详情请参考下文。
面板上常用群组分析 #
由于一组用户可以被定义为一个群组（Cohort），Tenjin面板会重点关注那些最常用于分析营销数据的群组
以下是常用的群组分析：
- 以买量日期 - 按买量日期对用户进行细分和分组是应用营销人员最重要的工作之一。 它允许营销人员计算 x-Day 留存率和 x-Day LTV 等指标。
- 用户属性 - 按渠道、广告计划、国家等对用户进行细分和分组，允许营销人员查看不同维度的指标。 通过这些维度分析用户可以揭示哪些用户想要您的应用程序，哪些用户不想要您的应用程序。
对于所有自定义cohort分析和优化，DataVault是一个非常强大的工具，可以提供这些深度洞察。通过DataVault，营销人员可以基于各种维度和指标构建自定义cohort，而这些信息只有在访问原始数据（raw data）时才能获得。
例如，通过下载advertising_id级别的数据，营销人员可以构建lookalike audiences（相似受众），从而持续优化广告投放活动。
