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The mighty MMM concept in hyper-casual game design

This article discusses an approach to make more interesting and pleasurable hyper-casual games. The aim is to achieve both higher retention rates and lower CPI numbers for hyper-casual games.


This article discusses an approach to make more interesting and pleasurable hyper-casual games. The aim is to achieve both higher retention rates and lower CPI numbers for hyper-casual games. The article discusses general approaches to design interesting games, and then projects that knowledge on hyper-casual genre by considering its peculiarities. It is based on several psychological experiments presented by professor Daniel Kahneman in his book Thinking, Fast and Slow [1], who received the 2002 Nobel Prize in Economic Sciences for his pioneering work with Amos Tversky on decision making.



Today hyper-casual game genre is very popular among players and game developers. Although there are predictions that the market is shifting from hyper-casual to hybrid-casual games [2] but this does not mean hyper-casual games are dying. This means the genre is actively transforming and evolving. Nowadays there are hundreds of game development studios and teams that make hyper-casual games, and dozens of publishers who offer hyper-casual game publishing services. Therefore, it is critical to analyze and understand the reasons behind successful titles.

So why some games succeed and make to the tops and others - don’t? What key points we might miss while making a game - hyper-casual games specifically? Why are some games good, but they never make that important transition from good to great?

In 2008 the App Store was born. There was a time when people could make a game or an app overnight and earn money. In 2017 App Store featured over 2.1 million apps [3]. At that time App Store was already so saturated and the competition for exposure and attention was so high that developers had to work long and hard on their games and also had to get significant download traffic obtained by marketing or store featuring to hope for something. It looked like those dream days were gone, when small teams with very small budgets had a chance to succeed. But, fortunately, life is not linear.

In 2017 Voodoo significantly contributed to popularizing hyper-casual genre. Although Voodoo didn’t pioneer making hyper-casual games, it took a couple of important steps towards establishing the genre: it understood customer needs, created design guidelines for the genre, a successful marketing and monetization scheme, named that genre and started to educate development studios how to make good hyper-casual games. Soon also created a dashboard where hundreds of studios can test their games quickly and transparently. The latest is also a big step forward, as even today some well known publishers test a game’s KPIs and hide from the developer what creatives have been used for testing or even hide the CPI numbers by giving a vague information. 

Pioneering of hyper-casual games is usually attributed to Ketchapp, sometimes people argue that this is not a new genre, this is just the renaissance of arcade games of the 70s [4]. But in this context it is not important when the first blossoms appeared. It is important that thanks to Voodoo in 2017 hyper-casual genre has become a well formed and established genre and captured the top charts of US App Store.

This was really a second breath for small game studios like us to get back their hopes to make small games and earn a significant amount of money [5,6]. Soon many other publishers joined the new trend and offered publishing services for hyper-casual games. 

Today, only 2 years later, hyper-casual game market is estimated at about 2.5 billion in annual revenue. There are hundreds of millions of dollars invested in hyper-casual games, [6] and dozens of well known and unknown publishers are looking for game development studios.

But how much game studios are in control of making hyper-casual games? Are they rolling the dice or professional game designers are able to craft the desired experience for the audience and make a hit game for the market? One particular problem with hyper-casual games is that those are so small and so simple that usually it is hard to understand how it is possible to apply the historically accumulated game design knowledge to such games [7]. One of such knowledge is the concept of interest curve. In this article interest curves are discussed and it is explained how a game designer can make his game more interesting even when the game is very small.

The Interest Curve

Jesse Schell in his book The Art of Game Design discusses an interest curve of an entertainment experience [8]. Interest curve is a simple concept - it is the dependence of the customer interest over time while consuming the entertainment experience. 

In that chapter Jesse Schell tells a very exciting story. At the age of 16 he started his career as a professional entertainer in an amusement park. One day the head of his show troupe, a magician named Mark Tripp, has taught him how the interest curve of a performance should be. Namely, he taught that keeping the same content (events) but re-ordering them might significantly enhance the quality of the experience for a magic or juggling show. Based on that advice Jessie Shell describes a good pattern of an interest curve of a well thought entertainment experience (see Figure 1 - taken from the book).

Figure 1,  An example of an interest curve for a successful entertainment experience


The main takeaways from this graph are that:

  1. The customer (game player, theme park guest, movie/theatre customer) comes with some initial non-zero interest, maybe because of the Ads, or because of friends’ referrals (point A).
  2. As an entertainer, during the first moments you need to increase his interest in order to create some expectations for the whole show. This is called “the hook”. (point B)
  3. Later there should be no flat part on the interest curve, because otherwise the consumer may leave the experience. The interest should rise and fall, but only to rise again (points C, D, E, F).
  4. The last part of the experience should be the grand climax. This is where the experience should become the most interesting and this is where the story is resolved (point G). It is desirable that the customer leaves the experience with some interest still left, in order to return again. Jesse Schell mentions that the leftover interest is what show business veterans say “leave them wanting more” (point H).

This is a very important lesson for a game designer to know how to order interesting moments along the experience timeline. 

This topic is also discussed in “Game Design Workshop” [9]. Tracy Fullerton describes how a classic dramatic arc is constructed (see Figure 2 - taken from the book).

Figure 2: Classic dramatic arc

It all starts with an exposition, where the consumer gets acquainted with the characters, the situation and the initial conflict, i.e. the premise. This creates a tension for the consumer to engage and wait for its resolution (the hook). This is a psychological phenomenon called Need For Closure (NFC) that describes “an individual's desire for a firm answer to a question and an aversion toward ambiguity” (from Wikipedia). [10]. The further development of the plot is being done by escalating the conflict. At some point the tension is on its maximum - the climax point. And then the resolution follows where the built tension is released.

So, basically, this is the same concept - no matter how you call it the interest curve or the dramatic arc. 

But what if I make a hyper-casual game? There is no story, no plot, a very small amount of narrative is present - if present at all. How can we use this very important knowledge in hyper-casual games?


What does psychology teach us? 

To understand what tools we have to operate with player’s interest in the scope of hyper-casual games, we need to understand some psychology. Here I will refer to results described by prof. Daniel Kahneman in his book Thinking, Fast and Slow. In this book he writes about many-many concepts and experiments that are directly useful to game designers. Those experiments are covering many important aspects of decision making, and game designers must know about those experiments for the following reasons:

  1. While making games we make decisions, and we need to understand what hidden forces may act on us while we make our decisions.
  2. While making games we work with a multi-profile team, with diversity of opinions and ways of thinking. We need to understand how our colleagues make their decisions, and how we can help them make better decisions.
  3. While playing a game a player needs to make decisions. If the player does not make decisions while playing a game, the game playing is becoming a static content consumption such as a book or a movie consumption is [11]. Hence the designers should understand how players make decisions and nudge them to make better, more pleasurable ones. As Sid Meier once said, we need to protect the players from themselves [12].

In the following 2 subtitles I will present psychological experiments that, hopefully, will change your attitude towards game development forever. I strongly recommend reading the book Thinking, Fast and Slow, if not the whole book then at least Chapter 35 “Two Selves”, to fully understand the obtained results. Here I will summarize the main details only and cite some experiments from the book. We will learn about two concepts - Peak-End rule and its generalization Less Is More rule. Let’s examine them one by one starting with Peak-End rule.


Peak-End rule

Prof. Kahneman wanted to understand how people experience pain (or pleasure) and how they remember them. For that reason, during experiments they were measuring the intensity of pain of colonoscopy patients. Back then when they were doing those experiments, colonoscopy was not administered with an anesthetic as well as an amnesic drug and was painful.

Citing from the book:

The patients were prompted every 60 seconds to indicate the level of pain they experienced at the moment. The data shown are on a scale where zero is “no pain at all” and 10 is “intolerable pain.” As you can see, the experience of each patient varied considerably during the procedure, which lasted 8 minutes for patient A and 24 minutes for patient B (the last reading of zero pain was recorded after the end of the
procedure). A total of 154 patients participated in the experiment; the shortest procedure lasted 4 minutes, the longest 69 minutes.

Next, consider an easy question: Assuming that the two patients used the scale of pain similarly, which patient suffered more? No contest. There is general agreement that patient B had the worse time. Patient B spent at least as much time as patient A at any level of pain, and the “area under the curve” is clearly larger for B than for A. The key factor, of course, is that B’s procedure lasted much longer.

When the procedure was over, all participants were asked to rate “the total amount of pain” they had experienced during the procedure. The wording was intended to encourage them to think of the integral of the pain they had reported, reproducing the hedonimeter totals. Surprisingly, the patients did nothing of the kind. The statistical analysis revealed two findings, which illustrate a pattern we have observed in other experiments:

  1. Peak-end rule: The global retrospective rating was well predicted by the average of the level of pain reported at the worst moment of the experience and at its end.

  2. Duration neglect: The duration of the procedure had no effect whatsoever on the ratings of total pain.

You can now apply these rules to the profiles of patients A and B. The worst rating (8 on the 10-point scale) was the same for both patients, but the last rating before the end of the procedure was 7 for patient A and only 1 for patient B. The peak-end average was therefore 7.5 for patient A and only 4.5 for patient B. As expected, patient A retained a much worse memory of the episode than patient B. It was the bad luck of patient A that the procedure ended at a bad moment, leaving him with an unpleasant memory.


Prof. Kahnemen explains that we have two selves - experiencing and remembering, i.e. we experience a process differently than we remember. Now the question rises, which self is deciding? If there will be a choice for us, which experience we want to repeat who will decide -  our experiencing or remembering self? Prof. Kahneman explains that the decision-making power is in the hand of our remembering self and here is a clear experiment to demonstrate that. Again citing from his brilliant book Thinking, Fast and Slow.

To demonstrate the decision-making power of the remembering self, my colleagues and I designed an experiment, using a mild form of torture that I will call the cold-hand situation (its ugly technical name is cold-pressor). Participants are asked to hold their hand up to the wrist in painfully cold water until they are invited to remove it and are offered a warm towel. The subjects in our experiment used their free hand to control arrows on a keyboard to provide a continuous record of the pain they were enduring, a direct communication from their experiencing self. We chose a temperature that caused moderate but tolerable pain: the volunteer participants were of course free to remove their hand at any time, but none chose to do so.
Each participant endured two cold-hand episodes:

  1. The short episode consisted of 60 seconds of immersion in water at 14° Celsius, which is experienced as painfully cold, but not intolerable. At the end of the 60 seconds, the experimenter instructed the participant to remove his hand from the water and offered a warm towel.

  2. The long episode lasted 90 seconds. Its first 60 seconds were identical to the short episode. The experimenter said nothing at all at the end of the 60 seconds. Instead he opened a valve that allowed slightly warmer water to flow into the tub. During the additional 30 seconds, the temperature of the water rose by roughly 1°, just enough for most subjects to detect a slight decrease in the intensity of pain.

Our participants were told that they would have three cold-hand trials, but in fact they experienced only the short and the long episodes, each with a different hand. The trials were separated by seven minutes. Seven minutes after the second trial, the participants were given a choice about the third trial. They were told that one of their experiences would be repeated exactly, and were free to choose whether to repeat the experience they had had with their left hand or with their right hand. Of course, half the participants had the short trial with the left hand, half with the right; half had the short trial first, half began with the long, etc. This was a carefully controlled experiment.

The experiment was designed to create a conflict between the interests of the experiencing and the remembering selves, and also between experienced utility and decision utility. From the perspective of the experiencing self, the long trial was obviously worse. We expected the remembering self to have another opinion. The peak-end rule predicts a worse memory for the short than for the long trial, and duration neglect predicts that the difference between 90 seconds and 60 seconds of pain will be ignored. We therefore predicted that the participants would have a more favorable (or less unfavorable) memory of the long trial and choose to repeat it. They did. Fully 80% of the participants who reported that their pain diminished during the final phase of the longer episode opted to repeat it, thereby declaring themselves willing to suffer 30 seconds of needless pain in the anticipated third trial.

The subjects who preferred the long episode were not masochists and did not deliberately choose to expose themselves to the worse experience; they simply made a mistake. If we had asked them, “Would you prefer a 90-second immersion or only the first part of it?” they would certainly have selected the short option. We did not use these words, however, and the subjects did what came naturally: they chose to repeat the episode of which they had the less aversive memory. The subjects knew quite well which of the two exposures was longer — we asked them — but they did not use that knowledge. Their decision was governed by a simple rule of intuitive choice: pick the option you like the most, or dislike the least. 


Prof. Kahneman mentions that this is a particular case of Less Is More rule - i.e. less overall torture was remembered as more in the remembering self. He then wraps up the chapter writing that there were classic studies on rats experiencing both pain and pleasure. Those experiments have also shown the same results - duration neglect, only the intensity was important. This was a huge finding for me as a game designer. But before I summarize this knowledge and go further there is something more about Less Is More rule that I have read in this book and I want to share with you.


Less Is More rule

In 1998 social psychologist Christopher Hsee has published a paper titled "Less Is Better: When Low-value Options Are Valued More Highly than High-value Options" in Journal of Behavioral Decision Making [13]. Prof. Kahneman has accumulated not only his experiments in his book, but also other groundbreaking experiments to explain the current state of knowledge in psychology of decision making. Here I have copied the parts about Hsee’s above mentioned experiment as well as an experiment done by experimental economist John List related to this topic:

Christopher Hsee, of the University of Chicago, asked people to price sets of dinnerware offered in a clearance sale in a local store, where dinnerware regularly runs between $30 and $60. There were three groups in his experiment. The display below was shown to one group; Hsee labels that joint evaluation, because it allows a comparison of the two sets. The other two groups were shown only one of the two sets; this is single evaluation. Joint evaluation is a within-subject experiment, and single evaluation is between-subjects.

  Set A: 40 pieces Set B: 24 pieces
Dinner plates 8, all in good condition 8, all in good condition
Soup/salad bowls 8, all in good condition 8, all in good condition
Dessert plates 8, all in good condition 8, all in good condition
Cups 8, 2 of them broken -
Saucers 8, 7 of them broken -


Assuming that the dishes in the two sets are of equal quality, which is worth more? This question is easy. You can see that Set A contains all the dishes of Set B, and seven additional intact dishes, and it must be valued more. Indeed, the participants in Hsee’s joint evaluation experiment were willing to pay a little more for Set A than for Set B: $32 versus $30.
The results reversed in single evaluation, where Set B was priced much higher than Set A: $33 versus $23. We know why this happened. Sets (including dinnerware sets!) are represented by norms and prototypes. You can sense immediately that the average value of the dishes is much lower for Set A than for Set B, because no one wants to pay for broken dishes. If the average dominates the evaluation, it is not surprising that Set B is valued more. Hsee called the resulting pattern less is more. By removing 16 items from Set A (7 of them intact), its value is improved.

Hsee’s finding was replicated by the experimental economist John List in a real market for baseball cards. He auctioned sets of ten high-value cards, and identical sets to which three cards of modest value were added. As in the dinnerware experiment, the larger sets were valued more than the smaller ones in joint evaluation, but less in single evaluation. From the perspective of economic theory, this result is troubling: the economic value of a dinnerware set or of a collection of baseball cards is a sum-like variable. Adding a positively valued item to the set can only increase its value.

Now when we already know about Less Is More rule and Peak-End rule, we surely can discuss how to make our games more interesting.

So here are the main takeaways: 

  1. Humans feel but don’t remember the duration of the pain or pleasure. Instead they remember the intensity of the peak.
  2. People decide not based on how they have experienced, but how they remember their experience.
  3. Adding smaller value items may decrease the value of the overall thing.

So while making a game it is really important to make the peak as high as possible. And we should remove all the flat parts from the interest curve, as they might damage the overall experience. 

Jesse Schell even talks about Less Is More in his book. He explains how they have enhanced Aladdin’s Magic Carpet VR experience for Disneyland by removing (providing a shortcut) the flat part of the interest curve from the experience (see Figure 3 - taken from Art of Game Design)

Figure 3: Interest curve for Aladdin’s Magic Carpet VR experience for Disneyland

You can consider this as another proof of Less Is More rule taken from the entertainment industry. 

One more exciting thing that I would like to mention about The Art of Game Design book is that in its first edition it was missing one concept, which was added in the second edition. It is called The Lens of Moments. Here it is shown in Figure 4


Figure 4: The Lens of Moments from The Art of Game Design: A Deck of Lenses, Second Edition


Basically, Schell is telling us to create key moments - memories. He is suggesting us to use the properties of remembering self - the one that is responsible for our decisions. In this context, I think, Jesse Schell has described surprisingly good what needs to be done to enhance the interest curve of an experience considering that he didn’t use the theoretical basis that psychology is providing. As we already know the more precise, scientific picture is described by the Peak-End and the Less Is More rules.

Projection of psychological knowledge onto hyper-casual games: The MMM concept

Now, finally, let's discuss this in the context of hyper-casual games. There is no story in them, no interconnected levels, no chain of dramatic events. What can we do to make them interesting? At this point the answer should be pretty obvious. In hyper-casual games we deal with one or two simple and intuitively understandable mechanics. What we can do is to make that mechanics very memorable by creating emotional peaks through that mechanics. 

If that sounds unclear let me give you some examples. When someone talks about The Matrix movie what do you recall from that movie first? Maybe this?

In order to be more on the subject, let’s discuss hyper-casual hit games published this year by Voodoo. When you talk about what is the first thing you recall? Maybe these shortcut jumps?

What about Crazy Kick!? 

These are not just my guesses. There is an available data proving that adding those mechanics to the game changed its KPIs significantly. Below I will present some examples of games published by Voodoo. I have a permission from Voodoo to present retention rates but, unfortunately, I can’t present CPIs in absolute numbers. But I will present here the relative improvement of CPIs in percents which will be enough to understand how much the game has been affected by the change.

The first version of without the jump mechanics had D1 47%, CPI C1. With the jump (as Voodoo calls it - the hack) and a bit refinement to make the jump more understandable (adjusting sea color, in order to make the character visible during a jump; adjusting the jump, so that it does not land and rotate) Cassette Studio achieved D1 48%, CPI C2. For calculating the relative improvements I use the following formula:

\(RelativeImpr =\frac{|C1 - C2|}{C1} \cdot 100\%\)

According to this formula the relative improvement of CPI has been about 44%. With further enhancing the avatar and making the jump even more satisfying (jumping right into the pool), they have achieved D1 47%, relative improvement of CPI was 59%. I think the numbers talk themselves.

What about Crazy Kick! metrics? The first test with dribbling mechanics has shown pretty good results: D1 25%, CPI C3. But when a kicking mechanics, shown in the GIF above, (the hack) has been added the numbers have changed as follows: D1 36%, CPI C4. Here the relative improvement of CPI has been 38%.

Another case - Roller Splat! First test had only 6 levels, 6 puzzles and D1 was 35%. When Neon Play made the view part more exciting

  1. Replaced the paint roller (the avatar) with a ball
  2. Made the ball movement much more reactive (respond to the input faster, move faster)
  3. Feeling of hitting a wall
  4. The paint trail effect

the same game changed D1 from 35% to 55%, i.e. 57% improvement in D1, just by my making the same thing more exciting and memorable - by enhancing the peak pleasure. No level design was changed, no levels were added.

You might think that the amount of content is what creates the retention. But I think this is not the only way to go. Indeed, the amount of content might help for a long term retention, because people get hedonic fatigue from experiencing the same pleasure again and again [8 Sellers]. But for D1 retention you need a very pleasurable moment. in it’s initial test had only 1 level with D1 equal to 47%. Voodoo’s Roller Splat! had only 6 puzzles - only 6 levels and D1 was 35%. Think this way, when you listen to a great song, what does make you listen to it the next day again? Did the content change? What about eating a very tasty apple every morning? The content is the same, you just wish to experience it again.

Therefore, while making hyper-casual games think about what would be the Most Memorable Moment of your game - the MMM. Make it more exciting, enhance the peak of the feelings created by that episode. This is because the peak of the feelings stays in the memory and then becomes the deciding factor for wanting more. Make the Triple-M of your game shine and both D1 and CPI will improve significantly.

I want to outline clearly that games are complex systems. I am not saying that you need to take your game and put there a bunch of memorable moments. It should all be nicely connected and deliver a single experience as a whole (keep the gestalt). Especially hyper-casual games have two other very important components the clarity and choices. These are also very important concepts and they are not understood identically by everyone.  By clarity I mean how clear is:

  1. The goal of the game
  2. The means of pursuing the goal - the mechanics and the control.

And by choices I mean:

  1. Breadth - The number of different things you can do within a game (e.g. dribble and kick, or slide and jump)
  2. Depth - The number of reasons you have to do the same thing (e.g. in you can slide in order to 1) dodge an obstacle, 2) catch a speeder boost, 3) jump from the slide and 4) kick an opponent)

Sometimes operations and mechanics can be combined to create even more choices - this is called synergy.



In every experience people remember the peak of their feelings and the end. The deciding factor both for downloading and for returning to your game is what remains in the players memory after seeing the game's Ad or playing the game. In hyper-casual games there are no clear endings, hence we really need to think about building the Most Memorable Moment. Games are being significantly affected by the MMM. Particularly, in the examples above, the corresponding changes resulted in improvements both in CPI and D1 results. The improvements have varied from 38% to 59%, which is a significant factor from transforming a good game to a great  one.  

For a good retention and marketability of your game you should consider introducing one very exciting and, hence, a memorable moment to the player’s experience -  the MMM.



  1. Thinking, Fast and Slow by Daniel Kahneman, 2013
  8. The Art of Game Design: A Book of Lenses by Jesse Schell, 2nd edition, 2015, Chapter 16 Experiences Can be Judged by Their Interest Curves
  9. Game Design Workshop: A Playcentric Approach to Creating Innovative Games by Tracy Fullerton, 4 edition 2018, Chapter 4 Working with Dramatic Elements
  11. Advanced Game Design: A Systems Approach, by Michael Sellers, 1st edition, 2017
  13. Hsee, Christopher K. (1998). "Less Is Better: When Low-value Options Are Valued More Highly than High-value Options" (PDF). Journal of Behavioral Decision Making. 11 (2): 107–121

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