Objective: Weigh the relative nuances of different game monetization models against each other.
Use material from Chapter 11: Efficient and Ethical Economies
QUEST: Choose at least 2 of the games you analyzed in previous steps and identify where they land on the Spectrum of Game Monetization, keeping in mind that “free to play” is rarely the only thing happening. Which quadrant does each game land in? Visit the Reddit forums for each of the games you’re analyzing. How does player sentiment support or contradict your analysis? For any games that offer loot boxes, take a moment to examine the loot drop tables.
For each game you select, complete the following tasks:
Plot the game on the spectrum of video game monetization.
Is it multiplayer or singleplayer? What is the relationship between the offers and gameplay benefits? What does this mean for the game’s monetization model: is it pay to play, pay to express, pay for power, or pay to accelerate? Does the game clearly fit into one of the four quadrants, or does it land in a grey zone? What could be done to move it into a quadrant you or players find more favorable?
Browse community forums for monetization sentiment.
Do players feel like they’re getting good value for their money? Look at social media, official forums, app store reviews, in-game chat, or game reviews. If not, what are the key issues? If so, what’s most popular?
Investigate any loot box offers.
Does this game sell randomized offers like loot boxes? If so, how are the chances of pulling an item conveyed? Is it clear what is possible? Is there a maximum number of pulls prior to getting the premium chase item? What agency does the player have if things go badly?
Once you’ve investigated at least 2 games, reflect on the following prompts:
Fairness
Do players feel offers are fair and that gameplay is fairly tuned alongside the economy? Is anything out of proportion?
Odds
How clearly is it indicated when an offer has low odds of returning a high value item? How much of the game’s offer pool relies on randomized offers?
Personalization
Is there any evidence that any of the offers you see are personalized to you? Does that influence your interest in the offers?
