The Product Dashboard and All Product Dashboard are designed to track and analyze key product metrics, providing insights into their performance and trends over time. These dashboards help monitor changes in core KPIs, allowing for data-driven decision-making and product optimization.
The All Product Dashboard functions similarly to the Product Dashboard, with the key difference being that it allows the selection of multiple applications in the filter, enabling a comparative analysis across multiple products.
Key Features:
- Product Performance Monitoring – Tracks key metrics of a product and their changes over time.
- Multi-Product Analysis (All Product Dashboard) – Allows selection and comparison of multiple applications in one view.
- Dynamic Trend Evaluation – Visualizes changes in key KPIs to identify patterns and trends.
- Customizable Filters – Enables filtering by various dimensions to focus on specific insights.
- Comprehensive Data Overview – Provides a structured and easy-to-read interface for product performance evaluation.
These dashboards empower teams to assess product health, compare multiple applications, and make informed strategic decisions based on real-time data.
Below is a detailed list of the filters available in the dashboards, each accompanied by a description to clarify its purpose and usage:
Filter | Description |
|---|
App | The name of the application. |
Country | The country where the ad was served. |
Below is a detailed list of the metrics available in the dashboards, each accompanied by a description to clarify its purpose and usage:
Metric | Description |
|---|
DAU | The number of daily active users. |
Installs | The number of app installations. |
Retention | The percentage of users who returned to the app on Day X after installation. Retention Day X is calculated for the cohort as the value for a specific date (D - X day). For example, Retention Day 4 on July 22 in the graph represents Retention Day 4 for the cohort from July 18. |
In-Apps | The number of in-app purchases (based on data from the validator by Magify. Alternatively, we support data validation from RevenueCat). |
ARPDAU | Average revenue per daily active user, calculated based on monetization grabbers. |
Revenue | The total revenue generated during the selected time period. Data sources: RevenueCat (in-apps and subscriptions), monetization grabbers (ads). |
Sessions per User | The average number of sessions per user, calculated as Sessions / User. |
Avg. In-Apps Check | The average in-app purchase value (based on data from the validator by Magify. Alternatively, we support data validation from RevenueCat). |
Sessions Statistics | Includes median session duration, average session length, and average time spent per user. |
Subscriptions | The number of subscriptions tracked (based on data from the validator by Magify. Alternatively, we support data validation from RevenueCat). |
ARPU D0 | The average revenue per user on Day 0. |
ARPU D4 | The average revenue per user on Day 4. |
% Paying Users | The percentage of paying users relative to the cohort of users who installed the app. |
Uninstalls | The number of app uninstalls tracked via Adjust. |
Adoption Rate | The adoption rate of the app version during the selected time period. |
Rolling Retention | Rolling Retention Day X includes users from the cohort who were active on any day between Day X and Day X+30 of their app lifecycle. For example, Rolling Retention Day 4 on July 22 in the graph represents Rolling Retention Day 4 for the cohort from July 18. |
Predicted Revenue | The forecasted revenue. |
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