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In a nutshell

Our analysis reveals 3 critical insights for the game's monetisation strategy:

1. The 15+ Match Threshold: Players who reach 15+ matches demonstrate 3-5x higher purchase likelihood and spend 31% more on their first purchase. This threshold represents a critical engagement milestone where players have invested enough time to develop strong game affinity and willingness to pay.
2. Game Mode Impact: Analysis shows significant variation in monetisation across match types. While 1v1 is most popular, Mode C shows 23-60% higher conversion than other modes in the same team configuration. More importantly, players who primarily engage with 2v2 in Mode B demonstrate 71% higher conversion rates compared to Mode A, making it the single highest-converting configuration.
3. Ad Impact Paradox: While heavy ad exposure correlates with higher engagement (and thus purchases), showing ads too early (particularly on day 0) reduces first purchase rates by 50%. This suggests ads don't harm monetisation when players are already engaged, but can disrupt the critical early experience.

Key Recommendations:

• Drive players to 15+ matches within their first few days through: (a) easy progression for early matches with quicker match pacing, (b) daily rewards and streak bonuses to encourage daily play, and (c) progression hooks that unlock new features around the 10-15 match mark.
• Promote 2v2 Mode B through targeted events, quests, and discounted add-ons. Establish 1v1 Mode C as the flagship competitive experience through UI prominence as first mode option, Mode C-specific challenges featured in onboarding tutorials.
• Eliminate or minimise ad exposure on day 0 to protect first impressions. Introduce ads gradually starting day 1-2, increasing frequency as players demonstrate engagement and reach 5+ matches to avoid disrupting the critical early experience. </aside>

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Summary of the problem

The game is a turn-based tabletop sports mobile game featuring multiple match types, human and bot opponents, in-app purchases, and various ad formats. With an upcoming game update, the product team needs data-driven insights to understand how current game design, monetisation strategies, and player behaviour happen. This analysis will identify opportunities to enhance both player experience and revenue generation.

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Objective of the assignment

Analyse the available datasets, develop and test hypotheses, and translate findings into clear, actionable game design recommendations supported by data.

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Hypotheses

Based on the data provided, we have formed the following hypotheses:

1. Players who engage more deeply are more likely to make their first purchase and tend to spend more on that purchase.
2. Different match types and team configurations may correlate with different monetisation behaviours, with certain game modes potentially driving higher spending.
3. Early ad exposure (days 0, 3, 7, 14) can negatively impact first purchase conversion rates.

Resources

🐍 Python Script:

TapSlam analysis.py

Insights:

1. Players who engage more deeply are more likely to make their first purchase and tend to spend more on that purchase

• The data shows a clear correlation between engagement depth and purchasing behaviour. Players who reach match 15+ demonstrate a 3x higher likelihood of making their first purchase compared to those who play fewer matches.
  • This likelihood increases to 5x for players who exceed 17 matches, indicating strong progressive engagement.
• Moreover, engaged players don't just purchase more frequently, they also spend 31% more on their first purchase on average, demonstrating higher initial willingness to pay.

Do many players reach match 15+ during their playing experience?