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Factor Samurai: From Zero to Profitability in the Educational App Market

After pouring our time and energy into building a game we loved, we saw it flop on the App Store. But some patience and a willingness to experiment with price allowed us to build strong demand and learn some important lessons along the way.

Third Rail Games was founded in 2010 by myself and programmer Jake Gundersen. We formed the studio around the notion that gameplay and learning go hand in hand.  After publishing a few experimental apps to test the App Store waters, we began to discuss ideas for our first real game. We theorized that a good educational game would pair a solid game mechanic with a solid learning concept, capitalizing on parallel structures between the two.

Around this time, Corona Labs released an amazing sample app wherein a basic fruit-slicing game was executed in under 500 lines of code. So we wondered: “What is a learning concept with a similar structure?” The notion of splitting a composite number into its factors seemed like a good fit and from that, Factor Samurai was born.

 

We built Factor Samurai in seven weeks. I had started learning Corona SDK only four months prior with no coding experience, but because Corona enabled such rapid development, the code was almost entirely complete within the first few weeks. Knowing Corona quite a bit better now, I suspect I could now build Factor Samurai from start to finish in a week or so. We hired an illustrator to create some great graphics and spent the rest of the seven weeks playtesting, polishing transitions, and refining the leveling system by which the numbers increase over time. We published the game to the App Store on September 13, 2011 for $0.99.

Despite our belief that Factor Samurai was a great game, initial download stats were disappointing. We had a few dozen downloads on the first few days, and then settled at about 15 a day. At this point we figured we could keep the app paid, collect a few hundred dollars a month, and hope for some eventual long term traction as downloads accumulated, or we could switch the app to free. We hypothesized that this would increase downloads and build demand so that we could eventually switch back to paid. We also figured that Factor Samurai would make a good portfolio piece if we could point to a big number associated with it. ("Over 100,000 downloads!", etc.). We switched Factor Samurai to free on September 26, 2011, 13 days after initial release.
 

Upon switching to free, downloads increased by two orders of magnitude. We had a few thousand a day for the first few days, and then it settled in at around 350 downloads daily. It was clear that at this rate, 100,000 downloads would be attainable in the next year or so. That number seemed like a decent benchmark where we could stop and reassess, so we decided to sit tight and continue development on other projects. We also added a few small features to the game and did some marketing here and there: Game Center integration, getting written up on various review sites, etc. While some of these endeavors improved the app for end users, none affected downloads in a significant way.

In August of 2012, Factor Samurai crossed 100,000 downloads. Our Flurry data indicated that it was mostly on iPads, and our AppFigures data indicated that most downloads were from educational institutions. The game appeared to be building up decent exposure in schools. We surmised that it was on enough devices and in enough schools that it might be enjoying legitimately strong demand from teachers and students, but that the demand (and willingness to pay) was masked by the fact that the app was free.

On August 30, 2012 we put our theory to the test and upped the price to $0.99. Our suppositions were correct: downloads dipped only slightly, but now these were paid downloads. The app was making money! On October 17 we raised the price to $1.99. Downloads dipped only slightly; revenue increased even more.

At this point we had enough data to do a rudimentary calculation of elasticity of demand - in other words, we were able to see how a change in price affected demand and, more importantly, what price point produced optimal revenue. For example, we’d rather have 100 downloads at $3 each (with a revenue of $300) than 120 downloads at $2 each (with a revenue of $240). Based on these calculations, we arrived at an optimal price: $2.99. Pricing the app at anything higher or lower would leave money on the table. We adjusted the price accordingly on November 4 and, once again, downloads dipped while revenue increased.

It has now been two years since we released Factor Samurai, and one year since we started charging for the app. The downloads have been consistent with what they were a year ago and I’m happy to say that the app brings in over $3,000 a month on average.

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