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Metrics 指标
- 17 Dec 2024
- 10 阅读时间
- 打印
- 黑暗模式白天模式
Metrics 指标
- 更新于 17 Dec 2024
- 10 阅读时间
- 打印
- 黑暗模式白天模式
文章摘要
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Metrics 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。
以下是 Tenjin 面板上的常见指标清单。
指标清单
详细信息
用户增长-指标
| 报告类型 | 缩写 | 完整名称 | 描述 |
|---|---|---|---|
| UA | In App Purchase LTV | In App Purchase LTV | Average In App Purchase Amount ($) |
| UA | Lifetime IAP ROI | Lifetime IAP ROI | Average In App Purchase ROI Percentage (%) |
| UA | In App Purchase LTV / User | In App Purchase LTV / User | Average In App Purchase LTV per User Amount ($) |
| UA | N-Day IAP LTV / User | N-Day IAP LTV / User | Average N-Day In App Purchase LTV per User Amount ($) |
| UA | IAP Rev | IAP Revenue | Total In App Purchase Amount ($) |
| UA | N-Day IAP LTV | N-Day IAP LTV | Cumulative IAP revenue N days after install |
| UA | Ad Rev | Ad Revenue | Total Ad Revenue Amount estimated by Tenjin ($) |
| UA | Ad Mediation Revenue | Ad Mediation Revenue | Total Ad Mediation Value ($) |
| UA | Ad Revenue LTV | Ad Revenue LTV | Total Ad Revenue LTV Amount estimated by Tenjin ($) |
| UA | Lifetime Ad ROI | Lifetime Ad ROI | Average Ad ROI Percentage (%) |
| UA | Ad Revenue LTV / User | Ad Revenue LTV / User | Total Ad Revenue estimated by Tenjin per User Amount ($) |
| UA | Ad Mediation LTV / User | Ad Mediation LTV / User | N-Day Ad Mediation LTV per user ($) |
| UA | N-Day Adrev LTV | N-Day Ad Revenue LTV | Cumulative ad revenue N days after install |
| UA | N-Day Ad Mediation LTV | N-Day Ad Mediation LTV | Cumulative Ad Mediation revenue N days after install ($) |
| UA | N-Day Adrev LTV / User | N-Day Ad Revenue LTV / User | Average N-Day Ad Revenue LTV estimated by Tenjin per User Amount ($) |
| UA | Total ARPDAU | Total Revenue per Daily Active Users | Average amount of Total Revenue (IAP + Ad) per DAU ($) |
| UA | IAP ARPDAU | IAP Revenue Per Daily Active Users | Average amount of IAP Revenue per DAU ($) |
| UA | Ad ARPDAU | Ad Revenue Per Daily Active Users | Average amount of Ad Revenue per DAU ($) |
| UA | Ad Mediation ARPDAU | Ad Mediation Revenue Per Daily Active Users | Average amount of Ad Mediation Revenue per DAU ($) |
| UA | Total Ad Mediation ARPDAU | Total Ad Mediation Revenue Per Daily Active Users | Average amount of Total Ad Mediation Revenue per DAU |
| UA | Total Rev | Total Revenue | Total Revenue Amount (IAP + Ad) ($) |
| UA | Total LTV | Total LTV | Total LTV (IAP + Ad Revenue) |
| UA | Lifetime Total ROAS | Lifetime Total ROAS | Average Lifetime Total ROAS Percentage (%) |
| UA | N-Day Total Ad Mediation ROAS | N-Day Total Ad Mediation ROAS | Average N-Day ROAS Percentage (%) Amount of cumulative total Ad Mediation revenue N days after install divided by spend |
| UA | N-Day Total Ad Mediation ROI | N-Day Total Ad Mediation ROI | Average N-Day ROI Percentage (%) Amount of cumulative total Ad Mediation + IAP Revenue (total revenue N days after install - spend) divided by spend |
| UA | Total Ad Mediation LTV | Total Ad Mediation LTV | Total Ad Mediation LTV |
| UA | Total Ad Mediation ROAS | Total Ad Mediation ROAS | Total Ad Mediation ROAS |
| UA | Total Ad Mediation ROI | Total Ad Mediation ROI | Total Ad Mediation ROI |
| UA | Lifetime Total ROI | Lifetime Total ROI | Average Lifetime Total ROI Percentage (%) |
| UA | Total LTV / User | Total LTV / User | Total Revenue (IAP + Ad) per User Amount ($) |
| UA | N-Day Total LTV | N-Day Total LTV | Cumulative total revenue (IAP + ad revenue) N days after the install |
| UA | N-Day Total Ad Mediation LTV | N-Day Total Ad Mediation LTV | Cumulative total revenue (IAP + ad mediation) N days after the install |
| UA | N-Day ROAS | N-Day ROAS | Average N-Day ROAS Percentage (%) Amount of cumulative total revenue N days after install divided by spend |
| UA | N-Day ROI | N-Day ROI | Average N-Day ROI Percentage (%) Amount of cumulative total profit (total revenue N days after install - spend) divided by spend |
| UA | N-Day Total LTV / User | N-Day Total LTV / User | Cumulative total revenue (IAP + ad revenue) N days after install divided by total users on 0-Day |
| UA | Total LTV / User | Total LTV / User | Cumulative total revenue (IAP + ad revenue) divided by tracked installs Total Revenue (IAP + Ad) / Total Ad Mediation LTV/ User |
| UA | N-Day Total Ad Mediation LTV / User | N-Day Total Ad Mediation LTV / User | Cumulative total revenue (IAP + ad mediation) N days after install divided by tracked installs Total Revenue (IAP + Ad mediation) / Total Users on Nday |
| 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 | Reported Clicks | 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 ($) 1000 * spend/reported impressions |
| UA | CPR | Completion Rate (CPR) | Average CPR Percentage (%) 100 * reported installs / reported impressions |
| UA | CTR | Click-Through-Rate (CTR) | Average CTR Percentage (%) 100* reported clicks / reported impressions |
| UA | CVR | Conversion Rate (CVR) | Average CVR Percentage (%) 100 * reported installs / reported clicks |
| UA | Impressions | Reported Impressions | Number of times your ad was displayed |
| UA | Reported Installs | Reported Installs | Number of installs reported by Ad Networks |
| UA | Installs Diff | Installs Difference | Total Installs Difference. Reported Installs - Tracked Installs |
| UA | Installs Difference Percent | Installs Difference Percent | Average Installs Difference Percentage (%). 100 - 100 * Tracked Installs / Reported Installs |
| UA | Lifetime Active Days / User | Lifetime Active Days Per User | Average number of active days for a user |
| UA | Sessions | Sessions | Average Sessions |
| UA | Lifetime Sess / User | Lifetime Sessions Per User | Average Sessions per User |
| UA | Spend | Spend | Amount spent to acquire users (in USD) |
| UA | tCPI | Cost-Per-Tracked Install (tCPI) | Average tCPI Amount ($) 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 | Tracked Installs | Number of Installs tracked by Tenjin |
| UA | Tracked Reinstalls | Tracked Reinstalls | Number of Reinstalls tracked by Tenjin |
| UA | CP N-Day User | Cost per N-Day Retained User | 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 ($) |
| UA | Purchasers | Unique Purchasers | Number of the unique purchasers |
| UA | Transactions | Purchase Transactions | Number of the total purchase counts |
| UA | N-Day Cost / Purchase | N-Day Cost Per Purchase Transactions | Cost divided by cumulative total purchase counts N days after the install |
| UA | N-Day Cost / Purchaser | N-Day Cost Per Returning Purchaser | Cost divided by returning purchase user N days after the install |
| UA | N-Day Cumul Revenue | N-Day Cumulative Purchase Revenue | Cumulative purchase revenue N days after the install |
| UA | N-Day Revenue / User | N-Day Cumulative Purchase Revenue per Acquired User | Cumulative purchase revenue N days after the install, divided by the number of acquired users |
| UA | N-Day Cumul Txns | N-Day Cumulative Purchase Transactions | Cumulative purchase counts N days after the install |
| UA | N-Day Txns per User | N-Day Cumulative Purchase Transactions per Acquired User | Cumulative purchase counts N days after the install, divided by the number of acquired users |
| UA | N-Day Participation | N-Day Purchaser Participation | Percent of unique purchasers N days after the install out of the number of acquired users |
| UA | N-Day Purchasers | N-Day Unique Purchasers | Cumulative unique purchasers N days after the install |
| UA | Average | Average Purchase Value per Transaction | Total purchase revenue, divided by total purchase counts |
| UA | Revenue | Purchase Revenue | Total purchase revenue |
变现-指标
| 报告类型 | 缩写 | 完整名称 | 描述 |
|---|---|---|---|
| AM | Reported Ad Revenue | Reported Ad Revenue | Total Ad Revenue reported by Ad Network ($) |
| AM | eCPC | Effective Cost per Click (eCPC) | Ad Revenue per Click ($) |
| AM | eCPM | Effective Cost per Mille (eCPM) | Ad Revenue per 1000 Impressions ($) |
| AM | Reported Clicks | Reported Clicks | Total Clicks reported by Ad Network |
| AM | Impressions | Reported Impressions | Total Impressions reported by Ad Network |
SKAdnetwork 指标
| 报告类型 | 缩写 | 完整名称 | 描述 |
|---|---|---|---|
| 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 Installs | Apple SKAN Installs | 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
面板上常用群组分析
详细信息
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。
另外，营销人员也可以借助 DataVault 进行定制化的深度群组分析。 DataVault 允许营销人员通过原始数据访问的各种维度和指标构建自定义群组。 例如，设备层级的数据可以让营销人员建立相似的受众，以进行持续的广告活动优化。
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