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Seo Master present to you:
This guest post was written by Beau Harrington, Senior Development Director, Kabam

Cross-posted with the Google Commerce Blog

Kabam was part of the initial launch of Google+ Games with two game titles, Dragons of Atlantis and Edgeworld, and we recently added Global Warfare. For these games, we integrated Google In-App Payments and we’re pleased with our games’ monetization to date. There are a couple things we learned along the way that we’re happy to share with the community.

Integrating In-App Payments

Integrating In-App Payments in our games was very simple, especially when compared to other payment platforms. There is excellent documentation available, complete with examples for each step of the purchase flow. We also used open-source libraries such as ruby-jwt to generate the tokens required for each purchase option.

We designed our games and purchase pages around the expectation of instant feedback, making sure to incorporate page loads or refreshes wherever possible. For example, in Edgeworld, a player attacking an enemy base can load the list of Platinum options instantly, without waiting for the list of payment options to load. After their Platinum purchase, the player is immediately brought back to the game, with their new currency and items waiting for them.

Pro tip: strive to reduce purchaser friction

One of the keys to maximizing revenue is to remove as much friction as possible from the purchase flow, making sure as many people as possible get from one step of the flow to the next. Many payment platforms send players to their own website and multi-page checkout flow. The Google In-App Payments approach allows us to keep players on our game page for the entire flow, making sure we can manage more of the process and reduce abandonment.

Additionally, the player's credit card information is stored securely, so once a player has made a purchase anywhere using In-App Payments, their information is available for future purchases without additional data entry. Finally, JavaScript callbacks provided by In-App Payments allow us to show the effects of the purchase immediately, improving customer satisfaction.

General recommendations

For those experienced in this space, the following may seem rudimentary. At the same time, I’d be remiss not to include these recommendations as they are important to developing a successful game payments system:

• Make sure your payment flow is as seamless as possible, never giving the player the opportunity to get bored waiting for something to load. 
• Record and monitor each step of the payment flow in order to identify potential problems. 
• Run A/B tests on your purchase option page to optimize the number of players who make a purchase, as well as the amount of the average purchase. 

We are proud to be among the first companies on Google’s exciting new monetization platform, and we look forward to the continuing growth in features, functionality and developer tools.

Beau Harrington is Senior Development Director of Kabam

Posted by Scott Knaster, Editor

2013, By: Seo Master

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Seo Master present to you:
By Pradeep Kumar, redBus

This guest post was written by Pradeep Kumar. Pradeep is a technical architect at redBus, an online travel agency in India that provides a unified online bus ticketing service. We recently published a business case study for redBus and wanted to dive into some more technical detail for the readers of the Google Developers Blog.


Our company has been providing Internet bus ticketing for India since 2006. There are more than 10,000 bus routes available for booking, and we have dozens of machines processing booking requests. Each step in the booking process produces a lot of data – on search terms, route availability, server health and more. We needed tools to to be able to process this data quickly and easily to determine whether decreases in customer bookings are the result of server problems or simply less demand.

While we typically use relational databases to store and analyze data, we knew we needed something more powerful if we wanted to analyze 500GB or more, so we started to look at open source frameworks like Hadoop and analysis platforms like Hive and Pig. We found that these frameworks require considerable in-house expertise and infrastructure investments and wouldn’t give us answers to our questions as fast as we wanted. We decided to try out Google BigQuery as a trusted tester, with hopes that it would give us the ability to perform quick iterative analysis without much up-front investment. Our initial tests went very well, so we started building our analysis tools on top of BigQuery.

BigQuery allows us to run SQL-like queries to understand the bus routes in highest demand and what types of searches users are performing. We’ve also used it to build internal dashboards that give us a snapshot of system health.


For more information on how we structured our immutable tables, pipelined our data into BigQuery for analysis using RabitMQ, and to see example SQL queries we’ve used, check out my article on developers.google.com.


Pradeep Kumar is a technical architect at redBus.

Posted by Scott Knaster, Editor

2013, By: Seo Master