Universal App Campaign
UAC is an abbreviation for Universal App Campaign, which is the campaign type used in Google Ads for app promotion. The UAC algorithm, at its heart, uses machine learning and automation to assist marketers in driving app installations and in-app conversions across all of Google's inventory. As a result, the term " Universal" was coined
The value of App Campaigns resides in the compounded impact that results from having a wide variety of ad placements, all pushing together for the same campaign goal. Each advertisement acts as a vital spot for audiences to find the concerned app.
Advertisers may now choose between two types of UAC campaigns.
Setup Campaigns: Within this option, one may target all users or those likely to execute an in-app activity. Both campaigns will strive for a specific cost-per-install (tCPI).
All Users: Maximize the bids on this campaign to achieve the most app installations feasibly.
Install Advanced Campaign: Optimize installation volume amongst consumers who are likely to take a specific in-app activity. The total number of installations with this choice may be smaller, and the CPI may be greater than for all users, but one gets to select the one in-app activity critical to their marketing objectives.
In-App Action Campaign: The campaign will streamline for clients who will probably do a specific action inside the application and secure them at a foreordained expense for each obtaining (tCPA). This action may be the one that ultimately assists the company with satisfying their KPIs, or it very well may be the underlying advance in driving clients to that action (intermediary actions). Since this campaign is based on tCPA bidding, the calculation will target individuals bound to play out that in-application action after installing. Along these lines, absolute introduce numbers might be lower, and CPI might be higher, yet one will acquire quality clients who will drive the ROI.
Because all optimization is automatic, the absence of targeting options pontificates the importance of deep learning, advertisers may be concerned about brand safety due to a lack of placement or a keyword report. However, Google addresses the issue by allowing advertisers to eliminate irrelevant content categories and labels on an account-by-account basis.
Each organization endeavoring to trade its image to worldwide markets faces a scope of challenges: for instance, various languages, cultures, and user conduct. Data can serve as an indispensable apparatus to help brands beat these challenges. Chinese gaming organization, 37Games, used Google's Universal App Campaign (UAC) to uncover critical insights through data and machine learning and used this data smartly in different areas — from game design and item operations to mark marketing — to increase the number of individuals playing its game, eventually prompting better profits.
By using UAC, the company was able to assemble game brand acknowledgment, increase numbers of game downloads and players, increase player degrees of consistency and collaboration and find all the more high-esteem users and increase by and large game profits.
By distinguishing target-user conduct by utilizing massive data, rapidly searching for and reaching other similar users, and increasing numbers of game downloads and players; fostering marketing solutions based on player behaviors and levels they came to in the game, the company was able to boost its sales.
Further, it won Google Play 2016 " Best Popular Phone Game of the Year" and increased both degrees of consistency and player levels of action and connection with the game by half.
