Adjust by AppLovin vs. Attribution in Google Analytics

It is very well-suited for big apps that have lots of users. They scale very well and are a little bit less expensive than other alternatives. They have API connections that are suitable for internal attributions and data. I recommend other solutions in some cases, such as cohorts and UI/Agency access.

Incentivized

The very first point where Google Analytics is well suited is it's ease of implementation as it does not require a developer to integrate it with the source. The real time reporting is very beneficial. Accuracy (too many robot clicks) and missing information are areas where Google Analytics has a room for improvement.

Incentivized

• Tracking installs on mobile app campaigns on Android or iOS, as well as UAC campaigns.
• Tracking in-app actions on our mobile campaigns.
• Showing more accurate numbers, since it counts pure installs from new users only without counting re-installs,
• Counts installs only after first opening of the app, while Google and Apple count also downloads even if the app doesn't get installed or opened after.

Incentivized

• Data Dashboard.
• Connects directly to Google Ads.
• Can export data.

Incentivized

• UI is very confusing and needs a refresh.
• Reports are very limited and need more granularity.
• Onboarding program for agencies lacks concrete information.

Incentivized

• There is a large learning curve for coming up to speed on ensuring proper setup, reviewing data sets, & understanding the user interface
• custom reports take expertise to set up for all of our needs
• default last-click attribution isn't what should be considered the standard. I would expect google's default to be more well-rounded

Incentivized

We are happy to use Adjust by AppLovin in our measurements and effects on the business, so the company would like to renew our use.

Incentivized

Adjust Attribution is great on Amplitude if tagged/integrated right.

Incentivized

Each MMP has its own set of advantages and disadvantages. What I like about Adjust is that it blocks the postbacks for invalid traffic without triggering an install which helps reduce fraud, as the fraudulent party does not get paid. Other systems count the install and then you need to go into the logs to subtract it but Adjust does it automatically. However, Adjust is by far the MMP with the worst UI and UX.

Incentivized

GA is less user-friendly, and organizations with fewer resources benefit from more intuitive platforms.

Incentivized

• As a positive impact it helped us create dashboards for every aspect of the business.
• It made us more data-oriented with the possibility to study retention and activation of specific cohorts.

Incentivized

• giving more insight into our ROI
• i can trust what i see in GA

Incentivized