As we dive into the world of mobile gaming analytics, it's crucial to stay ahead of the curve. With the rapid evolution of mobile marketing trends, predicting player behavior has become a critical component of success in the industry. In this article, we'll explore the insights of Vasiliy Sabirov, Head of Analytics at devtodev, on the most important trend in 2020: predictive player behavior.

A Glimpse into Vasiliy's Background

At devtodev, Vasiliy and his team provide a range of services to game developers, focusing on analytics and player support. Their main product is the devtodev game analytics platform, which offers insightful reports that highlight both game problems and opportunities for improvement. As Head of Analytics, Vasiliy develops new reports, advises clients, and provides analytical consulting.

The Journey Begins

Vasiliy's adventure in mobile apps and games started nine years ago when he joined Xsolla. He later worked as a Lead Analyst at AlternativaGames, where he gained expertise in gaming economics. For over five years now, Vasiliy has been helping other games succeed at devtodev.

Can Developers Succeed Without Analytics?

Although it's possible to launch a game without analytics, Vasiliy believes that further managing a free-to-play project this way becomes nearly impossible. In today's mobile marketing landscape, data analytics plays a vital role in understanding player behavior and making informed decisions.

The Challenges of Mobile Game Development

Vasiliy highlights the shift from IAP-monetization to Ad Monetization as a significant challenge in 2020. While Ad Monetization offers higher revenues, it's essential to develop detailed analytics to estimate the impact of ad viewing on company revenue. As Vasiliy notes, "We even can't always estimate how much money a particular player viewing a particular ad brings the company."

Top 5 Quality Indicators for Games and Mobile Apps

Vasiliy shares his top 5 quality indicators:

  1. Lifetime Value (LTV) – a qualitative metric that calculates the value of each player over time.
  2. Cumulative N-days ARPU – an average income from one active user over their first N days in the project, used for A/B testing.
  3. Long-term retention – measuring players who stay engaged with the game and bring the main income.
  4. Short-term retention – a fast metric that helps optimize tutorials, onboarding, and traffic quality.
  5. Sticky factor – calculated as DAU / MAU, showing how well players stick to the game.

Soft-Launch Insights

During the soft-launch stage, Vasiliy recommends measuring various analytics metrics, including:

  • Retention
  • Conversion to payment
  • ARPPU (income from paying users)
  • Cumulative ARPU for at least a week

He suggests keeping the game in soft-launch mode for at least two weeks and 10-20 thousand users to ensure accurate data.

Acquisition Campaign Signals

Vasiliy emphasizes the importance of measuring both short-term and long-term signals during a soft-launch:

  • Short-term: DAU, MAU, retention rates
  • Long-term: KPIs that require at least 1 week to calculate, such as retention metrics and conversion to payment

By understanding predictive player behavior, mobile game developers can make data-driven decisions to optimize their games and achieve success in the competitive mobile marketing landscape.