Merge TopOn ULRD with Tenjin’s DataVault | LTV
Table of contents
Overview
How to merge data from the TopOn Reporting API for user-level revenue data (ULRD) with Tenjin’s DataVault
What these reports can be used for
Summary
What you will learn
How it works
Setup
TopOn User Level Revenue Data (ULRD) with Tenjin attribution
Step-by-step guide on how you can set up your dashboard
What you will need
How To
Get access to the anonymised Google Data Studio Dashboard template
Learn how to navigate the dashboard at different levels of granularity:
By App granularity
By Country granularity
By Network Granularity
By Campaign Granularity
By Site ID Granularity
Overview
Merge data from the TopOn Reporting API for user-level revenue data (ULRD) with Tenjin’s DataVault
Upon completion of this use case, you will have a comprehensive overview of the following:
- What a Google Data Studio dashboard with combined data and metrics from TopOn ULRD and Tenjin‘s Datavault looks like
- How you can create cohort views in this Google Data Studio dashboard
- How you can analyze the most important metrics in this dashboard
- How far you can go in the analysis of your app’s ULRD data in Google Data Studio
What can these reports be used for?
The revenue data from TopOn’s User Level Revenue Data (ULRD) is joined with Tenjin’s DataVault to show you user-level data sorted by install date and data source. These reports can be used to analyze how much revenue your apps are generating after an install.
Here’s a glimpse of what the Google Data Studio dashboard with combined data and metrics looks like:
Important Note: All our Paid trainings include SQL/dashboard/script for which access is only provided to customers who have a paid subscription to the service. You can get in touch with us if you would like to subscribe.
Summary
What you will learn
This Google Data Studio dashboard shows different tables and graphs that are built on top of the TopOn Reporting API for ULRD & Tenjin’s DataVault.
It helps you understand your app’s performance in terms of User Acquisition and Monetization, at different levels of granularity.
How it works
The data is pulled from the TopOn API and Tenjin’s attribution.
You could either use this dashboard on top of your own ETL view of the cohort data or use Growth FullStack’s managed ETL services to analyze the data.
Setup
TopOn User Level Revenue Data (ULRD) with Tenjin attribution
The goal of this use case is to allow you to analyze granular TopOn revenue data with Tenjin attribution. The Google Data Studio dashboard reports ULRD ARPDAU, ULRD LTV, Installs, Spend, ULRD ROAS, and ULRD Revenue on different levels of granularity:
- App
- Country
- Ad Network
- Campaign
- (with the option to add site_id)
Step-by-step guide on how you can set up your dashboard
Growth FullStack customers who want to use our managed ETL pipeline services can use this dashboard as a template. Follow the steps below to get started:
Step 1: Connect to your Google Data Studio account. If you don’t already have an account, you can create one here for free.
Step 2: Click on this link to view our anonymized template.
Step 3: In the template, click on the icon that allows you to make a copy of the report. This will show you a pop-up.
Step 4: Select a data source. You will need to replace the demo dataset with yours.
What you need
You need to have data from Tenjin’s DataVault and TopOn ULRD in your data warehouse environment (Redshift and BigQuery are supported). Please configure this in Growth FullStack’s interface or reach out to your account manager if you need help.
If you are using BigQuery, you can use Growth FullStack’s managed ETL to push the Tenjin DataVault data and TopOn ULRD data into BigQuery.
How To
Get access to the anonymized Google Data Studio Dashboard template below:
Note: This template is available for a wide range of BI tools such as Looker, Metabase or Tableau. Feel free to get in touch with your Growth FullStack Account Manager for any additional details on the matter.
Google Data Studio Dashboard views
The Google Data Studio dashboard has the following example views to see your TopOn ULRD data joined on user-level with Tenjin’s DataVault data.
Here are some examples of how to interpret its different metrics with different granularities selected:
By App granularity
If we select only 1 app, we can see the following result:
Here is what we can say about it: “For App 1 between 2021-10-10 and 2021-11-07”…
- Tracked Installs: “We have between 200 and 600 installs per day”
- Spend & Revenue: “overall ad_revenue_tenjin is more or less equal to ad_revenue_topon; overall spend and revenue per day are between $75 and $225”
- ROAS (& CPI): “d0_roas_topon (=ULRD data) is about 60% for the whole period. Prior to October 23, break-even was achieved on or before D3 – after this period, it seems like break-even was not achieved at all. Before October 23rd CPI was consistently below $0.25. After, it was consistently higher than $0.30. We can also note that there is not much discrepancy between tCPI and CPI”
- Spend by Dimension Selected (=by app here): “overall spend and revenue per day are between $75 and $225”
- ARPDAU (& CPI): “arpdau_tenjin is more or less equal to arpdau_topon. ARPDAU seems to be around $0.30. We reached a big ARPDAU spike at $0.55 on Nov 4.”
- LTV (& CPI): “d0 LTV increased from $0.12 on oct 11 to $0.20 on october 15. D90 LTV increased from $0.23 on october 11 to $0.30 on october 15. However, starting from October 23rd, CPI started becoming higher than $0.30, which seems unprofitable for this app as it is a disproportionate CPI increase compared to the LTV increase.”
By Country granularity
We can then try to understand what are the key drivers for this app’s loss in performance by analyzing its LTV and CPI by country.
Here we can see that this app primarily drives installs in the US.
So here, we can filter only on the US and analyze the LTV for this app in the US:
By Network Granularity
We can then keep our filter to concentrate only on the US and change the granularity level to see the various Networks in which we spent in the US: seems like most of our budget went towards Ad Network 1
So here, we can filter only on Ad Network 1 and analyze the LTV for this app in the US for Ad Network 1:
By Campaign Granularity
We can then check our LTV by campaign for Ad Network 1.
For example, campaign 10, which seems to be driving most of the spend:
Site ID Granularity
We can go even further by analyzing the LTV of this campaign at the site_id level.
For instance, Site ID 1 within campaign 10, which again seems to attract the bulk of the spend:
Going deeper in your analysis will enable you to take informed decisions regarding your User Acquisition. Growth FullStack’s integration with TopOn User-Level Ad Revenue Data enables you to get the most precise LTV for each of these granularities.
FAQ
Can this dashboard be personalized as per my requirements?
Yes. In the Calculated Fields section of Data Studio, you will be able to see the available fields, metrics and dimensions from the TopOn revenue reporting API & Tenjin DataVault.
Your Growth FullStack Account Manager will be able to show them how to personalize the dashboard.
Is this dashboard supported with other tools?
Yes, we can build something similar with Metabase. Contact your Growth FullStack Account Manager for more details.
Feedback
Do you have any feedback for us?
We at Growth FullStack are always happy to receive your valuable feedback. Whether it’s about requesting additional support on optimizing your workflows, building a customized dashboard, or anything else, feel free to reach out to us and let us know how we can support you further.
Iterate and Maintain
Iterate
This dashboard can be edited. Additionally, TopOn offers more granular Impression Level Revenue Data (ILRD) via a Server to Server (S2S) integration.
Maintain
Please be aware that TopOn frequently updates its API and this may break the template.
