Tag: Playnomics

There's no question that the free-to-play model is here to stay in the gaming industry. After all, there's no better way for developers to get more people to check out their latest game than by using that alluring "Free" label. And for gamers, well who doesn't love getting free games? But then of course, the big question for free-to-play developers quickly arises: "How do I get users to actually spend money while playing my game?" The sad truth of the matter is that for many of today's smaller game developers, getting a lot of people to play their games for free doesn't necessary put money in their bank accounts. But luckily for them, Playnomics is here to help bridge that gap: by introducing their innovative PlayRM suite that serves as a platform for developers to analyze their users' in-game spending and staying habits, while effectively creating marketing campaigns to cater to these different individual monetization segments.I recently had a chance to send some questions to Chethan Ramachandran, the co-founder and CEO of Playnomics, and find out some more about the latest additions to the PlayRM suite, how the company sees the relationship between game developers and their high-value users, and of course, how the future of free-to-play games factors into the equation. Well for starters, Ramachandran chocks up the challenge of creating a free-to-play game that is constantly able to draw in monetization from users over long periods of time as being dependent upon two overarching industry problems. This realization ultimately led Playnomics to introduce two brand new features into their PlayRM suite in order to address these problems head-on: the Acquisition Value Predictor and the Churn Predictor."The first problem, as he tells me, is that "games must buy new users constantly to remain profitable." What's more, developers will tend to waste precious money and resources on marketing these new-user channels, only to bring in more players (acquisitions) who are unlikely to even spend anything in the long run. One way that the Acquisition Value Predictor aims to alleviate this problem is by displaying each player's Lifetime Value rating (or LTV) only a few days after they initially start playing. This way, the marketing team can quickly shift their efforts to key in on these higher-value users, as a result of determining the overall ROI of each player source or channel. The AVP also predicts the likelihood of player spending for a 90-day period after they've entered into a game, and it continues these predictions throughout the entire lifespan that a player stays with the game.