by kScope guest contributor
Tyler York, Marketing and Customer Development, Betable

It’s becoming clear that casino games are the next big social game genre.

Take a look at the image above, provided by Kontagent. Casino games are surpassing farm games as the darlings of social networks: The growth of monthly active users (MAUs) for farm games is slowing, while that of social casino games is generating higher revenues–seven times, to be precise–than the casual games category.

Furthermore, with downward pressure on Facebook’s stock from its falling revenues, it’s become increasingly likely that it will soon allow real-money gambling on its platform. Couple that with evidence that legislation may open up parts of the U.S. market to online gambling, and you have a perfect storm forming that game developers would be foolish to ignore.

The smart gambling companies have already made their moves into the social space. With IGT‘s purchase of Double Down Interactive and Caesar‘s purchase of Playtika,* gambling companies have snapped up the two largest existing social casino games. The savviest social game companies aren’t far behind them, with multiple companies creating their own casino games and Zynga aggressively moving into real-money gaming.

The threat comes from both sides. Social game companies have intricate knowledge of social game mechanics and their existing user bases. They can also “flip on” real-money play in their existing games and be a huge threat. Gambling companies can afford to spend hundreds of dollars per player to acquire users, and they are experts in capturing and retaining whales. They can bring massive war chests and marketing knowledge to any fight.

So game companies, if social gambling games are the new battlefield, how do you plan on win the war? Arming yourself with the right tools can make the difference between victory and defeat.

Analytics
In wartime, information is power. Going into this fight without analytics is like flying blind through enemy territory. You want the equivalent of the USSSN. When your company’s future is on the line, you want the best analytics available on your side so you can make the most informed decisions possible. Analytics is something that gambling companies are already experts on, but only within the context of gambling-only websites. You have the upper hand on Facebook and mobile platforms, for now. Leverage that as much as possible now to get the most distance between you and the invading force.

Betting mechanics
When you’re fighting tooth and nail for market share, those who use the best tactics have an inherent advantage. That’s why optimizing the betting mechanics in your social gambling game is key to victory. If your opponent is converting better than you are or keeping players more engaged, you’re going to be fighting an uphill battle for eyeballs and dollars. Instead, you should follow Blitzoo’s lead by using A/B testing recorded by robust analytics to continuously optimize your betting mechanics.

Real money
In any battle, resources are the key to victory. The two key resources for any game company are players and money, and they have become increasingly fluid with the advent of the freemium game model and modern distribution platforms. This makes real-money gaming the ultimate weapon: real-money casino games earn more than $300 per player per month. Real-money monetization is so powerful because with it, you have more ammunition that you can use to build games, acquire more players, and retain your most valuable players over the long term. Without it, you will always be outgunned by those that are using real-money gaming mechanics.

With a new battleground set to define the future of the social gaming space, you may need anywhere from one to all of these tools to succeed. Good luck, soldier.

*Playtika is a Kontagent customer.

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About the author: Tyler York does marketing and customer development at Betable, the first-ever platform that lets game developers create innovative new games by legally adding engaging real-money play. Prior to Betable, Tyler was a member of True Venture’s TEC 2010 program before joining Lookout Mobile Security as their third marketing employee.

Be the Brad Pitt Billy Beane of the Social and Mobile Web

What do Kontagent data scientist Martin Colaco and Billy Beane have in common?

On the surface, probably not much. But, when it comes to analytics, Beane changed the game for baseball. Colaco could be doing the same for business.

Moneyball is based on Michael Lewis’s book, Moneyball: The Art of Winning an Unfair Game. Faced with a relatively meager budget, Oakland Athletics manager Billy Beane (played by Brad Pitt) uses a groundbreaking, sabermetric approach—the specialized analysis of baseball through objective, empirical evidence that measures in-game activity—to recruit a competitive baseball team. (Read more on how sabermetrics works.)

Beane goes against convention, taking advantage of more empirical gauges of player performance to build a team that could successfully compete in Major League Baseball. He analyzes stats that are not generally considered top priority in the traditional scouting process. While most managers pored over stats like running speed, stolen bases and batting averages, the sabermetric approach, developed by baseball statistician Bill James, predicts other factors are better indicators of a player’s offensive success, e.g., on-base and slugging percentages.

Beane basically stared the “old guard” of baseball recruiting in the face and said, “Suck it.” And it worked.

Using sabermetrics, the Oakland A’s were able to put together a competitive team on a $41 million salary; by comparison, the New York Yankees spent more than $125 million in payroll in the same 2002 season. It paid off: the Athletics led a 20-game winning streak, and Beane shifted the paradigm of baseball scouting forever.

When it comes to Web business analytics, it’s not a bad idea to take a page out of the Moneyball book. Sometimes you have to look at data through a different lens in order to better make predictions and optimize opportunities. In baseball, Beane approached player stats differently and got different results. In business, data scientists like Colaco say there’s a similar shift happening in the world of Web 3.0.

Moneyball lesson #1: Challenge the status quo.
There’s a scene in Moneyball where Beane and his scouts are arguing over which players to recruit. His scouts want the highly sought-after players. Beane can’t afford them. Frustrated, he says, “You guys are talking the same non-sense. We’ve got to think differently.” Thinking differently, it turned out, made all the difference in the world.

It’s a good lesson to remember when it comes to business. With the explosion of social and mobile applications, we have to move away from the “old guard” of analytics and begin measuring KPIs around virality, engagement, retention, and monetization. It’s no longer about page views; it’s about users. What are these users doing within your applications? Every click of every action of every second. How can we use that information to win? We’ve got to think differently.

Moneyball lesson #2: You can compete with the New York Yankees.
Companies like Zynga, Playdom and CrowdStar aren’t wildly successful just because they’re in the social gaming space. No, these companies are behemoths when it comes to data. And, they’ve figured out how to collect, store, analyze and optimize all this data to succeed.

But what about the little guys who are trying to compete in this space? They may not have the infrastructure to support such massive amounts of data (or the hundreds of thousands of dollars needed to get that infrastructure in place). How do they (think: Oakland A’s) go up against Zynga (think: New York Yankees with the deep pockets)?! Luckily, analytics platforms like kSuite by Kontagent now provide the infrastructure needed to access data for organizations of all sizes.

Okay, great—you have access, but now what?

Moneyball lesson #3: Look at the data that really matters; it may not be obvious at first.
In Moneyball, Beane relied on Yale economics graduate Peter Brand (Jonah Hill) to help him make sense of all of the stats. It was Brand who took the core data and interpreted it so that Beane could make better scouting decisions.“Your goal shouldn’t be to buy players; your goal should be to buy wins,” he says.

The lesson here? Good data is useless if it’s mismanaged.

The right analytics solution needs to give you not only access to big-data analytics, but also an easy-to-understand dashboard and support from data scientists (your own team of Peter Brands!).

Data scientists can help you understand what the patterns of data are telling you to find the users with the greatest potential for monetization and lifetime value. What might appear obvious could be deceiving when you slice the information differently. And it’s these users that you want to understand and develop. It’s these users you need to understand. In. Order. To. Win.

Call it leveling the playing field.

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About the author: Catherine Mylinh is a member of Kontagent’s storytelling team, where she is head of content marketing. In her former life, Catherine was a news anchor for CBS and NBC. She credits her journalism and computer science roots—she was once a programmer!—for her love of learning and writing about all things high tech. You can contact Catherine at @cat_mylinh.