Tips to Avoid Accidental Clicks in Mobile App Ads; Slice & Dice GitHub Data Using Google BigQuery

In a May 3 post on Google Ads Developers blog, Google shared some tips on placing ads in moble applications to prevent accidental clicks.This post help you understand how you can monetize your mobile applications while following ad placement guidelines (AdSense policies and AdMob policies) to ensure a good experience for your users."One of the […]

In a May 3 post on Google Ads Developers blog, Google shared some tips on placing ads in moble applications to prevent accidental clicks.

This post help you understand how you can monetize your mobile applications while following ad placement guidelines (AdSense policies and AdMob policies) to ensure a good experience for your users.

"One of the most common policy violations is placing ads in a way which can trigger accidental clicks. Your ads' proximity to the other elements within your application can influence whether or not users click on ads by accident," Maiko Fujita, AdMob Team, said. Please double check your ads' implementation with the tips below.

An example of a placement to avoid (left) : A recommended ad placement in this scenario (right):

With the right implementation, you'll be able to monetize your application properly without accidental clicks.

  1. "Ads should not be right next to interactive buttons, such as a "next" button, or on a game play screen where users are interacting continuously with the application. We have seen that when a user is clicking or tapping repeatedly within an application and there is an ad near or within the interaction area, there is a much higher rate of invalid activity.
  2. If the space within your application is limited, it helps to then delineate the ad from the application content by creating a thick border between the ad and the application's interactive portion," explains Fujita.

In other Google developers news,

GitHub Archive bring the Dataset to Google BigQuery

Open-source developers all over the world contribute to millions of projects every day. The data generated from this activity can reveal interesting trends across many industries, including popularity of programming languages over time, defect rates, contribution metrics, and popularity of specific frameworks and libraries.

The challenge in extracting these trends is gathering the data from the 2.6M+ public projects hosted on GitHub. Hence, earlier this year GitHub Archive was born!

"GitHub Archive is a project to record the public GitHub timeline, archive it, and make it easily accessible for further analysis. Each day it archives over 120,000 public activities, ranging from new commits and fork events to opening and closing tickets, each with detailed metadata," writes Scott Knaster, on Google Developers blog.

The best news is that thanks to collaboration from the GitHub and BigQuery teams, the GitHub dataset is now public and available to slice and dice in any way you like.

If you are curious, sign up for BigQuery and follow the instructions on githubarchive.org to access the GitHub dataset.

You can use the free 100GB query quota to run your analysis and perhaps even win some of the prizes from the GitHub Data Challenge!

GitHub Archive Dataset Google BigQuery