Acquisition
New Users AdGyde lets you know, how many users installed your application through various campaigns in real time. Through this feature you are able to compare the performance of your campaigns and analyze the traffic for your applications.
Organic v/s Non-organic Downloads AdGyde provides segregated data for Organic and Non-Organic downloads
Organic App download: An organic download is a type of download wherein the user has reached to your application on Application Store searching through keywords provide by you.
Non-organic app download: An non-organic install is one where the user has come to your app download page for a reason, they may have been recommended by a friend or they have seen some form of promotion of your app. Somebody has directed the user to your application
User Flow Organic App download: An organic download is a type of download wherein the user has reached to your application on Application Store searching through keywords provide by you.
Non-organic app download: An non-organic install is one where the user has come to your app download page for a reason, they may have been recommended by a friend or they have seen some form of promotion of your app. Somebody has directed the user to your application
'User Flow' allows the Application Developer to gauge the movement of its users through the activities defined in the application. By analyzing the user flow Sankey diagram, the App developer can predict which activity is most popular among its users and where the drop-off rates are high.
User Flow in detail
Uninstall Tracking User Flow in detail
AdGyde's Uninstall Tracking functionality allows you to track the number of uninstalls for a specified application.
Un-Install tracking in detail
Re-AttributionUn-Install tracking in detail
Re-attribution is the attribution of a re-install to a partner who has re-acquired the user using a new campaign. When a user is re-acquired from a New Channel then it can be termed as re-attribution but the credit for same is not given to New Channel.
Credit of re-attribution of a user is given to new campaign when the same was done using re-attribution campaign.
New User per Publisher Credit of re-attribution of a user is given to new campaign when the same was done using re-attribution campaign.
If an advertiser, partner wants to track the sub-publishers of the new users, they can pass the sub-publisher value in the campaign link and same will be reflected under the graph.
Example : http://log2.adgyde.com/intf/b/1/u?c=20180605702947&p=1046&clickid={clickid}&pub={Publisher}
RetentionExample : http://log2.adgyde.com/intf/b/1/u?c=20180605702947&p=1046&clickid={clickid}&pub={Publisher}
1. Overview
Returning back to the application is an index to measure user loyalty.
For applications - Weekly returning rate to measure application performance would be the expected criteria. E.g. For an online bookshop, we expect user should open application at least once weekly. If online bookshop got 100 new users today, and 60 users open the application at least once in this week, then weekly returning rate is 60%. It can be considered good for an online bookshop.
For games - The returning rate of +1 day should be more important than weekly returning rate. This is because the developer expects the user should be attracted to their game and should play the game day and night. If the user doesn’t play the game the next day, this signifies that user has not like the game and the user could be lost.
2. Definition of returning For applications - Weekly returning rate to measure application performance would be the expected criteria. E.g. For an online bookshop, we expect user should open application at least once weekly. If online bookshop got 100 new users today, and 60 users open the application at least once in this week, then weekly returning rate is 60%. It can be considered good for an online bookshop.
For games - The returning rate of +1 day should be more important than weekly returning rate. This is because the developer expects the user should be attracted to their game and should play the game day and night. If the user doesn’t play the game the next day, this signifies that user has not like the game and the user could be lost.
In Below Depiction +n specifies number of days since Install. Assuming the number of New Users on Apr 1, 2016 was 100. +1 would mean Apr 2, 2016 and Users on +1 mean that How many users who installed application on Day 0 (Apr 1, 2016) have again returned on / opened the application on +1 (Apr 2, 2016). Similarly, +2 means Apr 3, 2016 and users on +2 mean that How many users who installed application on Day 0 (Apr 1, 2016) have again returned on / opened the application on +2 (Apr 3, 2016).
On Apr 2, 2016, 5 out of 100 new users opened the application, the number of users returned is 5. From Apr 2, 2016 to Apr 3, 2016, total 15 users opened the application, system will remove duplicate users, so number of users returned will be distinct(5, 10).
Note : This data in real life is descending as number of users returning decrease as the days pass.
3. How to read report | Date | Count of Active Users (Out of New Users of 1st Apr) | Count of users returned | |
| Apr 1, 2016 | 100 (New Users) | ||
| +1 | Apr 2, 2016 | 5 | =5 |
| +2 | Apr 3, 2016 | 10 | =distinct(5, 10) |
| +3 | Apr 4, 2016 | 15 | =distinct(5, 10, 15) |
| +4 | Apr 5, 2016 | 20 | =distinct(5, 10, 15, 20) |
| +5 | Apr 6, 2016 | 25 | =distinct(5, 10, 15, 20, 25) |
| +6 | Apr 7, 2016 | 30 | =distinct(5, 10, 15, 20, 25, 30) |
| +7 | Apr 8, 2016 | 35 | =distinct(5, 10, 15, 20, 25, 30, 35) |
| +14 | Apr 15, 2016 | 40 | =distinct(5, 10, 15, 20, 25, 30, 35, 40) |
| +30 | May 1, 2016 | 45 | =distinct(5, 10, 15, 20, 25, 30, 35, 40, 45) |
On Apr 2, 2016, 5 out of 100 new users opened the application, the number of users returned is 5. From Apr 2, 2016 to Apr 3, 2016, total 15 users opened the application, system will remove duplicate users, so number of users returned will be distinct(5, 10).
Note : This data in real life is descending as number of users returning decrease as the days pass.
User Retention data is NOT processed on real time and can take up to 24 Hours to show in Dashboard.
1. Login to AdGyde Dashboard
2. Select Retention section from Attribution heading in left navigation menu
1. Login to AdGyde Dashboard
2. Select Retention section from Attribution heading in left navigation menu