Most tech companies have a marketing department and some form of analytics. After all, everyone wants more users and everyone wants to see how those users behave. Many times those departments can be isolated from each other. At SGN, we regard analytics as the lifeblood of our company. Almost every action a user takes in our games is logged and stored so we can review it later. We do this for the benefit of improving our games, making them more fun, and encouraging better monetization. So how does this help the marketing department?
Example: Mary from our marketing team has been promoting one of our most popular games, Cookie Jam. On average she can acquire users for $2 each. This is great because when we run predictive analytics on our users in Cookie Jam, their lifetime Value (LTV) is north of $3. This means she can continue to acquire users at $2 and we can stay profitable! However, it’s not that simple. Mary is running hundreds of different campaigns from different sources in different countries. She’s also noticed that different countries are producing different LTVs, women are monetizing better than men, and certain ad partners seem to be giving us bogus users. How is she able to manage all of this?
This is all part of the data driven marketing machine we’ve built at SGN. As soon as a new user enters a game, they are tagged with a marketing source, a geo-location, and any demographic information they are willing to share. Then the real fun begins: monitoring the user’s behavior in the game. We look at KPIs like retention, engagement, and monetization. These values are then plugged into a predictive data model to determine the real value or LTV of those users. Now Mary can look at each of the campaigns and decide which source and which type of users are performing best.
Taking this one step further: When the product team finds ways of improving the user experience in the game, or finds a monetization breakthrough that encourages users to spend more, this all boils up to the marketing team. Now if a user’s LTV gets boosted to $5 on average, Mary can start spending even more for higher quality users and plan more creative campaigns to reach new people.
All of this requires a highly specialized team that understands data, the tools to manipulate data, and the way to visualize what we’re processing. It also takes a culture of recognizing the importance of data inside your company. We encourage everyone in the company to take a look at what’s going on inside a game every day. This facilitates better communication, faster execution, and higher profitability in the long run.
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