Adjust by AppLovin vs. Oracle Moat Measurement

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

Moat Analytics is great when it comes to breaking down how creatives and total ad campaigns have performed. It gives us insight on what we can suggest to the client on what they can do better next time or continue to do that seemed to have attracted the most amount of interactions and clicks. Right now we do not use Moat for breaking down video metrics.

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

• Breaks down how well each creative has done in a campaign.
• Allows us to see the progress of a campaign through its time live.
• Can easily be organized to pull the data you're looking for.
• Can export into an excel doc to then dig deeper and format and look at data outside of Moat.

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

• I’ve experienced some issues exporting reports into an Excel doc and have to manually copy and paste data with can be very time-consuming.
• You have to manually wrap video tags with the MOAT pixel which can be a tedious process.
• Video and display are in separate interfaces so you have to export separately and then consolidate into one report.

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

Moat and IAS seem to be front-runners to measure viewability in the digital media space. Using Moat allows you to measure a number of different metrics but is limited to viewability. IAS offers the same capabilities when it comes to viewability but in addition offers brand safety and ad fraud.

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

• It has given the media and analytics team more granular metrics to measure for campaigns that may have awareness objectives and no KPIs.
• Measuring view ability ensures that clients media dollars are being viewed by the targeted audience.
• Moat allows you to gain metrics that can be very insightful and how users are interacting with placements, creative, etc.

Incentivized