Audience segmentation for app developers is essential to understand who is engaging and how. See four ways to use audience segmentation with myTracker here.
Learn how to predict app revenue based on SKAdNetwork data when classic mobile marketing analytics tools no longer work: 3 easy steps with screenshots!
In this post, we’re going to go over everything you need to know about the SKAdNetwork’s conversion values and how you can use that data to your benefit.
This Guide to Analyzing Drop in User Engagement describes 8 scenarios of why user activity drops based on our assumptions and how myTracker can effectively address them.
Access to large amounts of historical data gives companies the advantage of being able to predict user actions. In this article, we will walk you through the benefits of myTracker's predictive analytics model.
With myTracker, you now have access to detailed analytics and ad revenue attribution on AdMob, a global ad monetization platform.
myTracker has released an update that enables you to set up revenue data uploads to your account from server to server (S2S) on your own. Read on to find out more about the update.
In order to know more about site visitors and mobile application users, you need to use data segmentation tools. A segment is a group of users selected according to specified parameters. Segments allow you to highlight the data you need, compare it with the overall metrics, and begin a detailed analysis of your audience.
Mobile analytics is the easiest way to see how your strategy is performing. How much do you earn from new users as compared to your advertising costs?
After an app is installed, users often become dormant or even uninstall it from their devices. Dedicated campaigns are initiated to return such users, including push notifications, retargeting and mailouts. In this case, attribution turns into reattribution.
Gathering and analysing ad costs have never been easier with myTracker's single interface. A real time saver, it will spare you the effort of downloading data manually from multiple sources to consolidate into a spreadsheet. All needed data are already in myTracker. All it takes is specifying the ad rates, and you gain insight into your overall ad costs and key performance metrics such as ROI and ARPU.
Metrics such as the number of installs or LTV can say a lot about your app, revealing how effective your traffic-driving techniques are, how good the traffic turns out to be and whether your promotional efforts are actually paying off. But you can hardly use this information to improve the product as it lacks specificity. What's a new user’s journey like in the app? At what point does the number of users plummet? What purchases are least frequent, and which levels remain unbeaten?
myTracker combines product and marketing metrics in a single interface and allows you to break them down by channel. There are tables and charts at your disposal that’ll tell you how the newly released feature is affecting user interest (for both existing and new audiences). You can see how well the update is doing with users, if it has made them more engaged, and if there are problems that urgently need fixing.
Any marketing campaign for a mobile app essentially aims at finding the most effective, highest-conversion advertising strategy encouraging app purchases and installs at the lowest cost. Advertising channel performance can be assessed directly with post-click attribution. Each app install is matched to a click on a link or banner to help conclude which advertisement performs better.
However, the user does not always take an immediate interest in the product or app after viewing the banner or reading the advertisement. A few hours later, having read the entire news feed, the user thinks back about the product he has taken interest in. Then the user finds the app in the app store and decides to install it.
In such a case, it would be reasonable to attribute this action of the user to that particular advertisement since it caught his attention and made him install the app. Attribution of the user's actions to particular advertisements, even if not clicked immediately, is called post-view, or view-through, attribution.
Every business, big or small, wants to know its real customer base and not be preoccupied with devices or platforms. But fragmented content consumption on multiple mobile devices is here to stay. What happens is that most tracking systems and attribution providers falsely detect multiple app users, which results in unreliable statistics and renders further data analysis less useful.
We are launching a beta test of a new function that brings you user-level statistics and believe that it will further improve your product and business.
What if you could predict your app’s expected revenue a few weeks or months in advance? Or know which ads will pay off rather than falling short of the target, and whether a customer is worth the acquisition costs?
To help you figure all this out, myTracker introduces a new, unique feature — LTV predictions for in-app purchases coming first as part of a broader set of predictive analytics capabilities. Leveraging data on billions of past events and their patterns, and based on your app’s individuality, predictive algorithms make it possible to predict the value of the users you acquire. The future is already here, all you need is to run myTracker and look at what is has to offer!