Nick Yee (Co-founder & Analytics Lead at Quantic Foundry - Game Analytics Consulting Practice) take a deep dive into each of the 12 motivations in the Gamer Motivation Model to 1) describe their psychological underpinnings, 2) identify specific game mechanics/features they are linked to, 3) provide specific game examples along the spectrum of the motivation, and 4) surface idiosyncratic aspects of each
If you haven’t seen it, check out the initial “Gamer Motivation Profile” talk.
People tend to treat a higher motivation on a spectrum as being more important or valuable than the lower end. But that's a mistake. Example: think that "hardcore games" > “casual” gamers, when in reality not everyone needs to be a hardcore gamer.
There’s an important difference between introverts and extroverts in terms of tolerance to novelty (entertaining vs. overwhelming), that usually traces back to when they were babies.
In reality most people fall in the average, even for something like introvert vs. extrovert: 68% of people are in the average. Only 5-10% fall at the extreme. See chart.
It’s a player’s delta from the average that largely defines a player and makes him memorable. Always visualize motivation from the norm. See chart.
One way to think of the appeal of competition is that it’s a way to hack your own bio-chemistry to get the adrenaline and endorphin rushes without actually being in danger.
Chinese gamers score much higher on competition and completion and lower on fantasy, story discovery and design.
The average Chinese gamer (Niko sample) cares more about competition than 75% of US gamers (Quantic Foundry sample).
Across the age span in China, the variation in motivations are very low. In general, there are very little differences based on demo.
Destruction is most appealing to younger gamers, particularly men. This motivation only starts dropping after age 40.
The best indicators of adoption of VR are destruction and excitement. This is important because VR is expensive and excitement and destruction drop with age, which limits adoption.
VR adoptors that also care about fantasy are more likely to be satisfied with their VR purchase.
The appeal of challenge lies in wanting to get better at something. There has to be a skill.
Challenge is the only motivation that rebounds after age 45 (it peaks for men around age 20, before declining). Older gamers might be more interested in mastering skill-based games and practicing over and over again than we might assume.
At the extremes of each personality factor or motivation spectrum model, you have players who are impossible to cater to and please. In a normal distribution, the extremes are rarely a good thing. Example with neuroticism (low: calm and relaxed, high: anxious and nervous) in regards to compliance to medical regimen where the mid-level neuroticism had the best outcome.
If you’re trying to port a game in China, one of the things you need to make sure of is that there is a PvP mode.
Before letting machine learning do predictions on motivations, make sure you have a broad base of behavioral telemetry in the game to ensure the best potential coverage and projectors of the motivations. Some motivations are easier to infer based on the gameplay (e.g. competition based on participation in PvP and ranks).
People tend to treat a higher motivation on a spectrum as being more important or valuable than the lower end. But that's a mistake. Example: think that "hardcore games" > “casual” gamers, when in reality not everyone needs to be a hardcore gamer.
There’s an important difference between introverts and extroverts in terms of tolerance to novelty (entertaining vs. overwhelming), that usually traces back to when they were babies.
In reality most people fall in the average, even for something like introvert vs. extrovert: 68% of people are in the average. Only 5-10% fall at the extreme. See chart.
It’s a player’s delta from the average that largely defines a player and makes him memorable. Always visualize motivation from the norm. See chart.
One way to think of the appeal of competition is that it’s a way to hack your own bio-chemistry to get the adrenaline and endorphin rushes without actually being in danger.
Chinese gamers score much higher on competition and completion and lower on fantasy, story discovery and design.
The average Chinese gamer (Niko sample) cares more about competition than 75% of US gamers (Quantic Foundry sample).
Across the age span in China, the variation in motivations are very low. In general, there are very little differences based on demo.
Destruction is most appealing to younger gamers, particularly men. This motivation only starts dropping after age 40.
The best indicators of adoption of VR are destruction and excitement. This is important because VR is expensive and excitement and destruction drop with age, which limits adoption.
VR adoptors that also care about fantasy are more likely to be satisfied with their VR purchase.
The appeal of challenge lies in wanting to get better at something. There has to be a skill.
Challenge is the only motivation that rebounds after age 45 (it peaks for men around age 20, before declining). Older gamers might be more interested in mastering skill-based games and practicing over and over again than we might assume.
At the extremes of each personality factor or motivation spectrum model, you have players who are impossible to cater to and please. In a normal distribution, the extremes are rarely a good thing. Example with neuroticism (low: calm and relaxed, high: anxious and nervous) in regards to compliance to medical regimen where the mid-level neuroticism had the best outcome.
If you’re trying to port a game in China, one of the things you need to make sure of is that there is a PvP mode.
Before letting machine learning do predictions on motivations, make sure you have a broad base of behavioral telemetry in the game to ensure the best potential coverage and projectors of the motivations. Some motivations are easier to infer based on the gameplay (e.g. competition based on participation in PvP and ranks).
People tend to treat a higher motivation on a spectrum as being more important or valuable than the lower end. But that's a mistake. Example: think that "hardcore games" > “casual” gamers, when in reality not everyone needs to be a hardcore gamer.
There’s an important difference between introverts and extroverts in terms of tolerance to novelty (entertaining vs. overwhelming), that usually traces back to when they were babies.
In reality most people fall in the average, even for something like introvert vs. extrovert: 68% of people are in the average. Only 5-10% fall at the extreme. See chart.
It’s a player’s delta from the average that largely defines a player and makes him memorable. Always visualize motivation from the norm. See chart.
One way to think of the appeal of competition is that it’s a way to hack your own bio-chemistry to get the adrenaline and endorphin rushes without actually being in danger.
Chinese gamers score much higher on competition and completion and lower on fantasy, story discovery and design.
The average Chinese gamer (Niko sample) cares more about competition than 75% of US gamers (Quantic Foundry sample).
Across the age span in China, the variation in motivations are very low. In general, there are very little differences based on demo.
Destruction is most appealing to younger gamers, particularly men. This motivation only starts dropping after age 40.
The best indicators of adoption of VR are destruction and excitement. This is important because VR is expensive and excitement and destruction drop with age, which limits adoption.
VR adoptors that also care about fantasy are more likely to be satisfied with their VR purchase.
The appeal of challenge lies in wanting to get better at something. There has to be a skill.
Challenge is the only motivation that rebounds after age 45 (it peaks for men around age 20, before declining). Older gamers might be more interested in mastering skill-based games and practicing over and over again than we might assume.
At the extremes of each personality factor or motivation spectrum model, you have players who are impossible to cater to and please. In a normal distribution, the extremes are rarely a good thing. Example with neuroticism (low: calm and relaxed, high: anxious and nervous) in regards to compliance to medical regimen where the mid-level neuroticism had the best outcome.
If you’re trying to port a game in China, one of the things you need to make sure of is that there is a PvP mode.
Before letting machine learning do predictions on motivations, make sure you have a broad base of behavioral telemetry in the game to ensure the best potential coverage and projectors of the motivations. Some motivations are easier to infer based on the gameplay (e.g. competition based on participation in PvP and ranks).
Notes for this resource are currently being transferred and will be available soon.
A player that is not motivated by grinding and leveling up is a contentment player. Someone who is comfortable with his status and doesn’t want to be caught up in the rat race.
A non-achiever can’t be placed on the X chart. It’s a blind spot that’s quite common across most motivation representations. But once someone points it out, you can’t miss it anymore.
400k gamers have filled the Quantic Foundry Gamer Profile survey, which includes the themes below.
Filling up the negative space is like figuring out what the 3 things below have in common (they love capes).
Strategy is about the decision complexity in the gameplay, the amount of information you need to make the next decision.
The below is not about measuring how a game could be played but how the core audience typically plays, how the “average” profile plays.
[💎@9:10] People tend to treat a higher motivation on a spectrum as being more important or valuable than the lower end. But that's a mistake. Example: think that "hardcore games" > “casual” gamers, when in reality not everyone needs to be a hardcore gamer.
Babies have temperamental differences in how they react to new things, new people or new sounds. On one extreme there are babies that remain calm and entertained when dangling a toy in front of them. On the other end there are babies that become distressed.
[💎@15:3] There’s an important difference between introverts and extroverts in terms of tolerance to novelty (entertaining vs. overwhelming), that usually traces back to when they were babies.
[💎@18:21] In reality most people fall in the average, even for something like introvert vs. extrovert: 68% of people are in the average. Only 5-10% fall at the extreme. See chart below.
“No one remembers you for having 10 fingers”
[💎@20:55] It’s a player’s delta from the average that largely defines a player and makes him memorable. Always visualize motivation from the norm. See below.
[💎@25:40] One way to think of the appeal of competition is that it’s a way to hack your own bio-chemistry to get the adrenaline and endorphin rushes without actually being in danger.
[💎@28:30] Completion is the motivation that changes the least when players age.
[💎@29:32] Chinese gamers score much higher on competition and completion and lower on fantasy, story discovery and design.
[💎@29:55] The average Chinese gamer (Niko sample) cares more about competition than 75% of US gamers (Quantic Foundry sample).
[💎@30:55] There is almost no difference in motivation for Chinese gamers depending on gender.
[💎@32:15] Across the age span in China, the variation in motivations are very low. In general, there are very little differences based on demo.
Chinese gamers as a whole are very different from US gamers but within Chinese gamers there are very little differences based on demo.
[💎@37:35] Destruction is most appealing to younger gamers, particularly men. This motivation only starts dropping after age 40.
[💎@39:44] The best indicators of adoption of VR are destruction and excitement. This is important because VR is expensive and excitement and destruction drop with age, which limits adoption.
[💎@41:00] VR adoptors that also care about fantasy are more likely to be satisfied with their VR purchase.
“What gets people through the door is not what keeps them inside.”
[💎@43:00] The appeal of challenge lies in wanting to get better at something. There has to be a skill.
[💎@44:00] Challenge is the only motivation that rebounds after age 45 (it peaks for men around age 20, before declining). Older gamers might be more interested in mastering skill-based games and practicing over and over again than we might assume.
[💎@47:30] At the extremes of each personality factor or motivation spectrum model, you have players who are impossible to cater to and please. In a normal distribution, the extremes are rarely a good thing. Example with neuroticism (low: calm and relaxed, high: anxious and nervous) in regards to compliance to medical regimen where the mid-level neuroticism had the best outcome.
On surveys becoming shorter and more direct hence biased (e.g. “Do you like strategic decisions”)
One part is to assess if you’re average or if you’re on the extreme. The other is that you also have to ask precise questions to get to the bottom of things.
On the gender differences USA vs. China in the real world: examples of games who have completely revamped from one country to another?
Big companies in China trying to expand in the US: a lot of Chinese games are very grindy MMOs that are less palatable for people in the west.
US companies trying to expand in China: variety of gameplay modes (collaborative and competitive) and one thing they had identified is that competitive was more successful. This was before they had this kind of data.
[💎@54:29] If you’re trying to port a game in China, one of the things you need to make sure of is that there is a PvP mode.
How to solve for the potential disconnect between who you can run the survey on vs. real players?
It’s tough because not all games express our motivations (can not track someone’s interest in stories in a game that has no narrative).
[💎@56:20] Before letting machine learning do predictions on motivations, make sure you have a broad base of behavioral telemetry in the game to ensure the best potential coverage and projectors of the motivations. Some motivations are easier to infer based on the gameplay (e.g. competition based on participation in PvP and ranks).
Challenge and concept of “fun failure”: does it require a “fail state” or helping players understand that there is a better way to do things?
You need to express that failure is ok but both “fail state” and “explanations” fall on the same end of the spectrum.
China vs. US: sample size was enough?
More details on the website in this article.
In the Chinese context, playing on mobile phones is not an indicator of casual games, and the sample might be biased more towards casual-core hardcore gamers.
The US data is biased on core players. The Niko data almost sets the lower bounds on the differences.
How is the population distributed along the five personality traits?
Have that in one of their previous slides. For men, destruction and excitement might have ranked the highest.
How does this expand beyond games (e.g. career, education)?
They also have a board game profile. They’re also working on a broader motivation profile that is more of a life aspiration profile, somewhere between a society profile and value profile. Example: someone who desires knowledge and curiosity or someone that cares about family and nurturing.
A player that is not motivated by grinding and leveling up is a contentment player. Someone who is comfortable with his status and doesn’t want to be caught up in the rat race.
A non-achiever can’t be placed on the X chart. It’s a blind spot that’s quite common across most motivation representations. But once someone points it out, you can’t miss it anymore.
400k gamers have filled the Quantic Foundry Gamer Profile survey, which includes the themes below.
Filling up the negative space is like figuring out what the 3 things below have in common (they love capes).
Strategy is about the decision complexity in the gameplay, the amount of information you need to make the next decision.
The below is not about measuring how a game could be played but how the core audience typically plays, how the “average” profile plays.
[💎@9:10] People tend to treat a higher motivation on a spectrum as being more important or valuable than the lower end. But that's a mistake. Example: think that "hardcore games" > “casual” gamers, when in reality not everyone needs to be a hardcore gamer.
Babies have temperamental differences in how they react to new things, new people or new sounds. On one extreme there are babies that remain calm and entertained when dangling a toy in front of them. On the other end there are babies that become distressed.
[💎@15:3] There’s an important difference between introverts and extroverts in terms of tolerance to novelty (entertaining vs. overwhelming), that usually traces back to when they were babies.
[💎@18:21] In reality most people fall in the average, even for something like introvert vs. extrovert: 68% of people are in the average. Only 5-10% fall at the extreme. See chart below.
“No one remembers you for having 10 fingers”
[💎@20:55] It’s a player’s delta from the average that largely defines a player and makes him memorable. Always visualize motivation from the norm. See below.
[💎@25:40] One way to think of the appeal of competition is that it’s a way to hack your own bio-chemistry to get the adrenaline and endorphin rushes without actually being in danger.
[💎@28:30] Completion is the motivation that changes the least when players age.
[💎@29:32] Chinese gamers score much higher on competition and completion and lower on fantasy, story discovery and design.
[💎@29:55] The average Chinese gamer (Niko sample) cares more about competition than 75% of US gamers (Quantic Foundry sample).
[💎@30:55] There is almost no difference in motivation for Chinese gamers depending on gender.
[💎@32:15] Across the age span in China, the variation in motivations are very low. In general, there are very little differences based on demo.
Chinese gamers as a whole are very different from US gamers but within Chinese gamers there are very little differences based on demo.
[💎@37:35] Destruction is most appealing to younger gamers, particularly men. This motivation only starts dropping after age 40.
[💎@39:44] The best indicators of adoption of VR are destruction and excitement. This is important because VR is expensive and excitement and destruction drop with age, which limits adoption.
[💎@41:00] VR adoptors that also care about fantasy are more likely to be satisfied with their VR purchase.
“What gets people through the door is not what keeps them inside.”
[💎@43:00] The appeal of challenge lies in wanting to get better at something. There has to be a skill.
[💎@44:00] Challenge is the only motivation that rebounds after age 45 (it peaks for men around age 20, before declining). Older gamers might be more interested in mastering skill-based games and practicing over and over again than we might assume.
[💎@47:30] At the extremes of each personality factor or motivation spectrum model, you have players who are impossible to cater to and please. In a normal distribution, the extremes are rarely a good thing. Example with neuroticism (low: calm and relaxed, high: anxious and nervous) in regards to compliance to medical regimen where the mid-level neuroticism had the best outcome.
On surveys becoming shorter and more direct hence biased (e.g. “Do you like strategic decisions”)
One part is to assess if you’re average or if you’re on the extreme. The other is that you also have to ask precise questions to get to the bottom of things.
On the gender differences USA vs. China in the real world: examples of games who have completely revamped from one country to another?
Big companies in China trying to expand in the US: a lot of Chinese games are very grindy MMOs that are less palatable for people in the west.
US companies trying to expand in China: variety of gameplay modes (collaborative and competitive) and one thing they had identified is that competitive was more successful. This was before they had this kind of data.
[💎@54:29] If you’re trying to port a game in China, one of the things you need to make sure of is that there is a PvP mode.
How to solve for the potential disconnect between who you can run the survey on vs. real players?
It’s tough because not all games express our motivations (can not track someone’s interest in stories in a game that has no narrative).
[💎@56:20] Before letting machine learning do predictions on motivations, make sure you have a broad base of behavioral telemetry in the game to ensure the best potential coverage and projectors of the motivations. Some motivations are easier to infer based on the gameplay (e.g. competition based on participation in PvP and ranks).
Challenge and concept of “fun failure”: does it require a “fail state” or helping players understand that there is a better way to do things?
You need to express that failure is ok but both “fail state” and “explanations” fall on the same end of the spectrum.
China vs. US: sample size was enough?
More details on the website in this article.
In the Chinese context, playing on mobile phones is not an indicator of casual games, and the sample might be biased more towards casual-core hardcore gamers.
The US data is biased on core players. The Niko data almost sets the lower bounds on the differences.
How is the population distributed along the five personality traits?
Have that in one of their previous slides. For men, destruction and excitement might have ranked the highest.
How does this expand beyond games (e.g. career, education)?
They also have a board game profile. They’re also working on a broader motivation profile that is more of a life aspiration profile, somewhere between a society profile and value profile. Example: someone who desires knowledge and curiosity or someone that cares about family and nurturing.
A player that is not motivated by grinding and leveling up is a contentment player. Someone who is comfortable with his status and doesn’t want to be caught up in the rat race.
A non-achiever can’t be placed on the X chart. It’s a blind spot that’s quite common across most motivation representations. But once someone points it out, you can’t miss it anymore.
400k gamers have filled the Quantic Foundry Gamer Profile survey, which includes the themes below.
Filling up the negative space is like figuring out what the 3 things below have in common (they love capes).
Strategy is about the decision complexity in the gameplay, the amount of information you need to make the next decision.
The below is not about measuring how a game could be played but how the core audience typically plays, how the “average” profile plays.
[💎@9:10] People tend to treat a higher motivation on a spectrum as being more important or valuable than the lower end. But that's a mistake. Example: think that "hardcore games" > “casual” gamers, when in reality not everyone needs to be a hardcore gamer.
Babies have temperamental differences in how they react to new things, new people or new sounds. On one extreme there are babies that remain calm and entertained when dangling a toy in front of them. On the other end there are babies that become distressed.
[💎@15:3] There’s an important difference between introverts and extroverts in terms of tolerance to novelty (entertaining vs. overwhelming), that usually traces back to when they were babies.
[💎@18:21] In reality most people fall in the average, even for something like introvert vs. extrovert: 68% of people are in the average. Only 5-10% fall at the extreme. See chart below.
“No one remembers you for having 10 fingers”
[💎@20:55] It’s a player’s delta from the average that largely defines a player and makes him memorable. Always visualize motivation from the norm. See below.
[💎@25:40] One way to think of the appeal of competition is that it’s a way to hack your own bio-chemistry to get the adrenaline and endorphin rushes without actually being in danger.
[💎@28:30] Completion is the motivation that changes the least when players age.
[💎@29:32] Chinese gamers score much higher on competition and completion and lower on fantasy, story discovery and design.
[💎@29:55] The average Chinese gamer (Niko sample) cares more about competition than 75% of US gamers (Quantic Foundry sample).
[💎@30:55] There is almost no difference in motivation for Chinese gamers depending on gender.
[💎@32:15] Across the age span in China, the variation in motivations are very low. In general, there are very little differences based on demo.
Chinese gamers as a whole are very different from US gamers but within Chinese gamers there are very little differences based on demo.
[💎@37:35] Destruction is most appealing to younger gamers, particularly men. This motivation only starts dropping after age 40.
[💎@39:44] The best indicators of adoption of VR are destruction and excitement. This is important because VR is expensive and excitement and destruction drop with age, which limits adoption.
[💎@41:00] VR adoptors that also care about fantasy are more likely to be satisfied with their VR purchase.
“What gets people through the door is not what keeps them inside.”
[💎@43:00] The appeal of challenge lies in wanting to get better at something. There has to be a skill.
[💎@44:00] Challenge is the only motivation that rebounds after age 45 (it peaks for men around age 20, before declining). Older gamers might be more interested in mastering skill-based games and practicing over and over again than we might assume.
[💎@47:30] At the extremes of each personality factor or motivation spectrum model, you have players who are impossible to cater to and please. In a normal distribution, the extremes are rarely a good thing. Example with neuroticism (low: calm and relaxed, high: anxious and nervous) in regards to compliance to medical regimen where the mid-level neuroticism had the best outcome.
On surveys becoming shorter and more direct hence biased (e.g. “Do you like strategic decisions”)
One part is to assess if you’re average or if you’re on the extreme. The other is that you also have to ask precise questions to get to the bottom of things.
On the gender differences USA vs. China in the real world: examples of games who have completely revamped from one country to another?
Big companies in China trying to expand in the US: a lot of Chinese games are very grindy MMOs that are less palatable for people in the west.
US companies trying to expand in China: variety of gameplay modes (collaborative and competitive) and one thing they had identified is that competitive was more successful. This was before they had this kind of data.
[💎@54:29] If you’re trying to port a game in China, one of the things you need to make sure of is that there is a PvP mode.
How to solve for the potential disconnect between who you can run the survey on vs. real players?
It’s tough because not all games express our motivations (can not track someone’s interest in stories in a game that has no narrative).
[💎@56:20] Before letting machine learning do predictions on motivations, make sure you have a broad base of behavioral telemetry in the game to ensure the best potential coverage and projectors of the motivations. Some motivations are easier to infer based on the gameplay (e.g. competition based on participation in PvP and ranks).
Challenge and concept of “fun failure”: does it require a “fail state” or helping players understand that there is a better way to do things?
You need to express that failure is ok but both “fail state” and “explanations” fall on the same end of the spectrum.
China vs. US: sample size was enough?
More details on the website in this article.
In the Chinese context, playing on mobile phones is not an indicator of casual games, and the sample might be biased more towards casual-core hardcore gamers.
The US data is biased on core players. The Niko data almost sets the lower bounds on the differences.
How is the population distributed along the five personality traits?
Have that in one of their previous slides. For men, destruction and excitement might have ranked the highest.
How does this expand beyond games (e.g. career, education)?
They also have a board game profile. They’re also working on a broader motivation profile that is more of a life aspiration profile, somewhere between a society profile and value profile. Example: someone who desires knowledge and curiosity or someone that cares about family and nurturing.
