Ad Intelligence

Ad Intelligence helps app marketers understand how mobile apps are using paid app-install campaigns to grow

Tracking Top Advertisers

Successful mobile-app advertisers are constantly looking for ways to improve marketing, remain ahead of their competitors, and acquire users with new creative strategies. Keeping up with the latest mobile advertising trends is the first step to understanding the performance of top advertisers running the most successful campaigns. 

This guide focuses on tracking Top Advertisers worldwide and uncovering who is spending the most on their advertising efforts, primarily focusing on the most seen campaigns across all networks.

Understanding Top Advertisers

Sensor Tower's Top Advertisers module in Advertiser Insights displays an aggregated view of top advertisers by highest to lowest Share of Voice (SOV) in ranking order. View the top mobile advertisers in any country, across the largest ad networks and category for your selected date range.

Slice the data to see weekly, monthly, or quarterly changes in the advertising landscape. Use these SOV and rankings to uncover who is spending the most on each Network. 

rtaImage_53.gifNote: We currently don't capture ad spend for each advertiser, however, a higher SOV% generally correlates with high spending levels and vice versa.

Tracking Top Advertisers Worldwide:

The Top Advertisers page is laid out in four sections, including two ways of viewing the leaderboard data:

🔎  Filters to narrow down your selection: 
Beneath the header, you’ll notice filters to select a preferred Date, Category, Game Taxonomy, Country, and Network.

Our list of Networks includes Apple Search Ads (ASA). Select ASA from the Network dropdown list to see which apps are advertising on their network. Here you can see the overall SOV across all keywords for each app to understand who is heavily advertising on ASA compared to any other apps. You can also view more keyword/term specific ASA data in our App Intelligence product.

Top Advertisers leaderboard is a great place to check for any Category to explore the top advertisers in other Countries. Use these filters to research and gauge the most successful players in the advertising space.

🔎  Use Global Fields and narrow down your leaderboard:
Filter advertisers with our Global and Custom fields to refine the selection. You can choose to include or exclude specific apps to find more meaningful results. 

Click 'Display All Fields’ to select from our preset filters or create Custom Fields to perform custom analysis. 

For instance, if you wanted to look at the performance of Hyper casual (gaming) advertisers in Canada, you'd apply the Date, Category, Country, Game Taxonomy filters and then narrow down your list using Global Fields. Some useful tags for this search can include; App Release Date, Most Popular Country by Downloads, Most Popular Country by Revenue, or Release Days Ago.  

Once you've refined your apps of interest, there are two ways of viewing the SOV leaderboard: 

📊  A ranking chart displays all apps in descending SOV%, hover over each bar to see an app’s SOV for the selected Network.


📊  A table below provides a breakdown of current SOV alongside Prior SOV for the same time range and additional detail on each advertiser. Check growth percentages in the far-right column to understand the impact of any app’s campaign.

rtaImage_57.gifBy default, you will see the SOV for the current time period selected, Prior SOV, SOV growth, and Growth percentage. Customize your table by configuring the columns to display meaningful data:

rtaImage_58.gifIf you have access to Store Intelligence, you might choose All-Time Downloads and Revenue to see the impact of paid marketing alongside SOV%. Add, remove, or replace columns with eight other column metrics, including App Info, App Ratings, App Updates, Store Intelligence, and Custom Fields.

💾  Export your findings via .CSV to further analyze or integrate these results into your workflow. 

Note: We discourage comparing SOV across all networks as it is nearly impossible to measure due to how the size of each network varies. Currently, there is no meaningful way to combine impressions for advertisers and total impressions per network across multiple networks. 

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