Network Requests by Ad Unit metric counts the number of ad requests made by a specific ad unit of an app to AdMob servers, which gives insights on ad load, user behavior, and revenue optimization.
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Used to show comparisons between values.
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To track Network Requests by Ad Unit using Databox, follow these steps:
The Network Requests by Country metric in GoogleAdMob measures the number of ad requests from different countries. It helps advertisers understand their audience and optimize ad campaigns for better performance.
The Impressions CTR by Format metric measures the click-through rate (CTR) of ad impressions on different ad formats such as banner, interstitial, and rewarded video ads. It helps to understand which ad format is performing better in terms of engagement and user interaction.
The Network Requests Matched by App metric measures the number of requests that were sent by the app to AdMob servers and resulted in an ad being served. It indicates the effectiveness of the app's ad implementation and the relevance of ads being shown to users.
The Network Requests Matched by Format metric tracks the number of ad requests that successfully matched ad formats offered by the AdMob network.
Match Rate by App is a measure of the percentage of ad requests for a specific app that result in a filled ad. It indicates how well the app's inventory is being matched with relevant ads.
The Show Rate by Ad Unit metric measures the percentage of times an ad unit was shown in relation to the number of ad requests made for that unit. It helps evaluate the performance and effectiveness of ad units in terms of displaying ads to users.
Show Rate by Format is a metric that measures the percentage of ads that were shown to users out of the total number of ad requests made, broken down by ad format (e.g. banner, interstitial, rewarded video).
Network Request RPM by Ad Type is a metric that shows the revenue per thousand ad requests per ad type. It helps to analyze the performance and profitability of individual ad types and make informed decisions to optimize the ad inventory.