71. Regularity
Article and discussion about Regularity, and why it matters more than e.g., basic Retention KPIs, and related basic metrics.
Regularity
The games industry talks endlessly about retention. D1, D7, D14, D30, D90, D180, D360, and so on. Retention curves. Funnels. And, as the list goes on… session counts, and session times. Sometimes, in some cases, even things such as re-engagement.
Yet, strangely, one of the most important long-term engagement concepts is rarely discussed directly: Regularity.
Not retention as an event. Regularity as a behavioral state and pattern.
Why it should be discussed more? In short, because there is a major difference between a player returning to a game and a game becoming part of a player’s life and habits.
Retention and regularity are not the same thing.
A player can technically be retained while having an unstable relationship with the game. They might binge heavily during updates, disappear for days, return through obligation, or only engage when e.g., event tension spikes. From a retention dashboard perspective, things may look acceptable. From a systems perspective, the ecosystem may still be unstable.
Regularity is different. Regularity is about consistency of emotional and behavioral connection over time. It is about how naturally a game embeds itself into routines, habits, rituals, social structures, and cognitive space.
The strongest live-service games rarely survive purely because they have good retention. They survive because they build regularity.
A game that quietly becomes part of somebody’s morning coffee, lunch break, evening unwind session, weekly social gathering, or persistent mental landscape is operating at a very different level than a game that simply manages to pull players back occasionally for e.g., entertainment purposes.
This distinction matters far more than many studios realize. Because regularity creates stability. And stability creates scalability.
Retention Measures Return, Whilst Regularity Measures Life Integration
One of the more interesting things about regularity is that the industry often measures fragments of it without explicitly treating it as the central objective.
Retention partially reflects regularity. Session counts partially reflect regularity. Session times partially reflect regularity. And even things like community activity partially reflects regularity.
But these metrics are usually analyzed separately, as disconnected KPI surfaces, instead of being understood as parts of a larger behavioral system. The result of this is that many games accidentally optimize for spikes instead of rhythms.
This becomes especially visible in modern live-service ecosystems. Large updates temporarily inflate engagement. Events create bursts of activity. Reward structures attract players back into the game. Some monetization moments artificially create urgency. And the list goes on.
But underneath those spikes, the underlying behavioral regularity may actually be weak. This is why some games feel constantly alive while others feel temporarily activated.
The difference is not always retention. Often, it is cadence stability.
Session Interval Variance (SIV)
One useful way to conceptualize regularity is through something I would call Session Interval Variance, or SIV.
At a high level, SIV measures how consistent player engagement rhythms are over time. Think about two players:
Player A
Plays eight hours on Saturday
Disappears for four days, and returns after an update or event
Engagement for Play A is highly volatile.
Player B
Plays twenty to thirty minutes almost every evening
Maintains stable engagement timing
Player B naturally integrates the game into routine behavior.
Traditional metrics may value Player A heavily because total playtime is high. But, from a systems perspective, Player B represents far stronger regularity. The game has successfully synchronized itself with that player’s life rhythm.
Lower variance between play intervals often signals stronger behavioral embedding. The game no longer relies entirely on stimulation spikes or external reactivation pressure. It becomes naturally integrated into routine behavior.
This matters because routine-based engagement tends to be more resilient, emotionally sustainable, predictable, and healthier for long-term ecosystems.
Habit Persistence Score (HPS)
Retention asks whether players returned.
Habit persistence asks whether behavioral rituals survived.
There is a meaningful difference.
A player logging in every day does not necessarily mean a stable habit exists. They may simply be responding to e.g., missing rewards.
But, if players consistently participate in the same social activities, progression loops, market behaviors, guild interactions, co-op sessions, crafting routines, and such, then the game has created recurring behavioral anchors. This is where games become sticky.
Easy examples of habit persistence:
Weekly MMO guild raid nights
Nightly extraction runs with friends
Morning auction house checking
Seasonal reset / prestige preparation
Daily community interaction during e.g., work breaks
These are not merely engagement loops anymore. Instead, they are recurring structures inside players’ lives. The strongest ecosystems often succeed because they maintain these rituals for years. Not because they maximize short-term engagement spikes.
Baseline Engagement Stability (BES)
One of the major blind spots in modern live-service design is that many ecosystems optimize around peaks instead of stability. Big events, big updates, big collaborations, and other big “beats”.
But regularity-oriented ecosystems often optimize around cadence consistency instead. This is where Baseline Engagement Stability, or BES, becomes useful.
At a high level, BES measures how stable player engagement remains without major external stimulation. In other words, it asks: "How healthy is the ecosystem when nothing extraordinary is happening?”
This matters enormously because many games unknowingly rely on continuous stimulation injections to maintain engagement. Once event cadence slows down, engagement collapses because underlying regularity was never truly established.
Healthy ecosystems tend to maintain:
Stable concurrency
Stable social activity
Stable progression engagement
Stable return behavior
Stable community participation
Even between major updates.
Cadence Amplification Ratio (CAR)
Obviously, baseline stability alone is not enough for live-service ecosystems.
There is another important layer: How effectively do updates and events amplify existing regularity instead of artificially replacing it?
This is where something I call as Cadence Amplification Ratio, or CAR, becomes useful conceptually. CAR measures how much engagement rises during updates and events relative to the baseline regularity, or BES, of the ecosystem.
A healthy ecosystem usually has:
A stable baseline
Controlled amplification during updates
Smooth stabilization afterward
An unhealthy ecosystem often has:
Weak baseline activity
Massive event spikes
Rapid collapse after content consumption
The difference matters enormously. One creates long-term ecosystem health. The other creates dependency on perpetual stimulation.
This becomes especially visible in games where players are highly active during launches but psychologically disconnected between updates. The game starts feeling less like a living world and more like temporary content consumption.
The strongest ecosystems avoid this trap because updates amplify habits instead of replacing them.
Cognitive Occupancy
There is also a more abstract layer to regularity that is harder to measure directly but incredibly important: Cognitive occupancy.
This refers to how much mental and emotional space a game occupies even when players are not actively playing. Some games remain alive inside players’ minds continuously. Others disappear immediately after logout.
This often becomes visible through e.g.,:
Discord participation
Theorycrafting
Community activity
Fan culture
Content creation
Social discussions
Market speculation
Identity attachment
This layer is difficult to universally quantify because every ecosystem expresses it differently.
What matters is recognizing that these signals often move in parallel with long-term ecosystem health. In some cases, community weakening even appears before major engagement decline becomes visible inside the game itself.
Communities frequently detect ecosystem fatigue earlier than dashboards do. Because regularity is not merely mechanical. It is also emotional.
Regularity, Immersion, and Proximity Design
This is also why regularity connects deeply to immersion.
Immersion is often discussed aesthetically:
Graphics
Audio
Worldbuilding
Narrative fidelity
But behavioral immersion may actually matter more for long-term ecosystem health.
A truly immersive game maintains continuity inside the player’s cognitive world. The player never fully disconnects from it emotionally. Their relationship with the game persists between sessions.
This is also why regularity often strengthens monetization willingness in healthier ways than aggressive extraction systems do. Players who maintain stable emotional continuity with a game tend to spend more naturally over time because the ecosystem feels persistent and personally meaningful.
The relationship becomes less transactional and more infrastructural. The game starts functioning more like a long-term environment than a temporary product. This also strongly connects to proximity design.
Note: Interested about what I’ve wrote about Proximity Design? See more from below article (https://gamesalchemy.substack.com/p/59-the-power-of-proximity):
The closer a game positions itself to e.g.,:
Emotional rhythms
Social identity
Cognitive habits
Lifestyle structures
Recurring behavioral patterns
The stronger regularity tends to become. Games stop competing purely through stimulation. They begin competing through relevance to lived experience.
Regularity Creates Predictability
This eventually leads toward one of the most important business implications of all: Predictability.
Regularity creates predictability across the ecosystem, including:
Predictable concurrency
Predictable economy behavior
Predictable matchmaking quality
Predictable social activity
Predictable monetization
Predictable content demand
And, predictability is one of the foundations of scalability.
A game with stable behavioral rhythms is significantly easier to:
Operate
Expand
Balance
Monetize
Sustain long-term
Than a game built entirely around volatility spikes.
Ironically, many studios become obsessed with highly granular KPIs while overlooking the larger systemic question: Is the game actually becoming part of players’ lives?
Because ultimately, that is what many of the greatest long-term games achieved. Not merely retention, but behavioral permanence.
Ethical Regularity
There is an important ethical dimension to regularity that designers should think about more carefully. Because there is a meaningful difference between building healthy behavioral permanence and building unhealthy dependency.
Regularity itself is not inherently good.
Games can absolutely create regularity through:
anxiety
obligation pressure
aggressive FOMO
social punishment
compulsive reward structures
excessive scarcity pressure
behavioral exhaustion loops
And many modern systems unfortunately do exactly that.
This is especially important to realize because regularity is psychologically powerful. Once a game successfully integrates itself into somebody’s daily rhythms, emotional structures, and routines, it begins influencing real behavioral patterns at scale.
That creates responsibility.
The healthiest forms of regularity usually emerge when players genuinely want to return because the ecosystem provides:
comfort
meaning
social belonging
emotional continuity
self-expression
relaxation
mastery
curiosity
creative or social fulfillment
Not because players feel psychologically trapped. This distinction matters enormously.
There is a major difference between a game becoming part of somebody’s life in a healthy, enriching way vs. becoming behaviorally compulsive through pressure-driven design.
As designers, it is important to think carefully about where that line exists for each ecosystem. Because ultimately, the strongest long-term ecosystems are usually not the ones that maximize extraction.
They are the ones players genuinely want to keep living inside.
Regularity Index (RI)
This is where a larger framework like a Regularity Index, or RI, becomes useful conceptually.
Not as a single perfect KPI, but as a systems-level perspective combining:
Cadence consistency
Ritual persistence
Baseline stability
Update amplification health
Cognitive occupancy
Social continuity
Behavioral predictability
The goal is not to reduce regularity into one number. The goal is to stop viewing engagement as fragmented surfaces and start understanding it as ecosystem behavior.
Because games are not only content systems. They are also behavioral systems. And the strongest behavioral systems do not merely retain attention, they become rhythms people live inside.
Thank you so much for this post. I've been writing about MMOs for over a decade, and I've often made various arguments in favor of what you call "regularity," but they always felt partly subjective and partly intuitive. Your post explains all of this from a systems perspective. This is excellent work: a very cohesive explanation of what matters most to the core MMO audience.