> For the complete documentation index, see [llms.txt](https://help.smartico.ai/welcome/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.smartico.ai/welcome/products/ai-models/gamification-penetration-model.md).

# Gamification Penetration Model

#### What it is

Gamification Penetration tells you, for each player and every day, how deeply they use each of your five gamification features: Missions, Tournaments, Jackpots, Minigames and the Store.

It gives you two things you can act on:

1. Where the player stands on each feature.
2. Which single feature is worth pushing them on next.

#### What you get

One row per player, per brand, refreshed every day. Each row contains:

* **A position on each of the five features**, from Not started up to Power user.
* **One recommended feature** to focus on for that player.
* **A suggested action** in plain terms.

#### The five positions

Each feature is a ladder. Every player stands on one of five rungs.

| Position    | What it means                  | What you might do                               |
| ----------- | ------------------------------ | ----------------------------------------------- |
| Not started | Never used this feature        | Introduce it for the first time                 |
| Lapsed      | Used it before, has gone quiet | Win them back, reference what they used to play |
| Starter     | Tried it, no habit yet         | Remove the blocker, see below                   |
| Engaged     | Regular user, not at the top   | Show them how close the top rung is             |
| Power user  | Fully embedded in the habit    | Stop promoting. Recognise and protect           |

Starter splits in two, and the two need opposite messages:

* **Starter A** was active in only one of the last three months. They came once. Prompt them to come back.
* **Starter B** was active across months but at low volume. The habit exists, the intensity doesn't. Push frequency.

#### How the position is decided

The model looks at the **last 90 days, split into three separate months**. For each feature it asks three questions:

1. **Did they show up at all?**
2. **How often did they take part?**
3. **Did they come back month after month?**

Showing up puts a player on the ladder. Frequency and consistency then decide how far up. This matters: a player who plays heavily for one month lands somewhere different from one who plays lightly across all three. Most reporting counts both as simply "active".

**Who gets scored.** A player is scored if they were active in the last 90 days and deposited at least once in the last 180 days. Players who have disengaged completely are left out.

#### Only conscious engagement counts

**The model measures what a player chose to do. If your platform entered someone into a tournament automatically, or assigned them a mission they never opted into, none of it counts. Being enrolled in something is not the same as being interested in it.**

The five features differ in how much of this needs filtering out:

| Feature                    | How participation happens                                                           | What the model does                   |
| -------------------------- | ----------------------------------------------------------------------------------- | ------------------------------------- |
| Minigames, Jackpots, Store | The player has to act. There is no way to take part without choosing to             | Counts everything                     |
| Missions, Tournaments      | Mixed. Some participation is chosen by the player, some is assigned by the platform | Counts only the part the player chose |

#### How the recommended feature is chosen

Every player sits on five ladders at once. For each one, the model measures the **value gap**: the difference in typical 30-day deposits between players at that player's current rung and players one rung up. The feature with the largest gap is the one recommended.

The gap is measured in absolute terms, not percentages. A big percentage jump on a small base is worth less real money than a small jump on a large one.

**One exception.** A player who is a Power user on all five features is flagged **Protect**. No campaign is recommended. These are your most engaged players, and more promotions risk the relationship rather than growing it.

#### What each feature needs from your integration

A feature only produces positions if its data reaches the model. If it doesn't, every player shows as Not started for that feature.

| Feature     | What counts as engagement                                               | What it needs                                                                 |
| ----------- | ----------------------------------------------------------------------- | ----------------------------------------------------------------------------- |
| Missions    | Missions the player opted into and completed, and in how many months    | Mission opt-ins and completions                                               |
| Tournaments | Tournaments the player chose to enter, how many, across how many months | Tournament registrations, with auto-enrolments marked so they can be excluded |
| Jackpots    | Distinct days with qualifying jackpot bets, across how many months      | Jackpot bets                                                                  |
| Minigames   | Spins taken, months they span, and how many different game types        | Minigame spins with game type                                                 |
| Store       | Items purchased, how many, across how many months                       | Store transactions                                                            |

Two inputs sit behind all five:

| Data            | What it powers                                             |
| --------------- | ---------------------------------------------------------- |
| Deposits        | Whether a player is scored, and the size of each value gap |
| Recent activity | Whether a player is scored                                 |

#### When there is no answer

Two cases look like a gap but aren't faults.

**A whole feature shows 100% Not started.** Usually the feature isn't live for your brand, so nothing is being sent and nothing can be scored. Check whether it's switched on before reading anything into it. If it is live, then the number is real, and it's a reach problem rather than a player problem.

**A player has no recommended feature.** Either they're a Power user everywhere and flagged Protect, or the value gap can't be measured. To size a gap, the model needs enough of your players to have already reached the next rung. Where only a handful have, the comparison would be noise, so the model leaves it out rather than reporting a number it doesn't trust. It comes back on its own as more players reach that rung.

Both are a real "we can't tell", not a quiet "no".

#### Each position also works on its own

The recommendation is one way to use this. Each of the five positions is also a player property in its own right.

* **Lapsed on any feature** is a warm re-engagement audience. They already tried it, so you can reference what they played instead of introducing it cold.
* **Starter A vs Starter B** separates "came once" from "comes often but lightly".
* **Power user on a single feature** finds your genuine enthusiasts per product. Useful for beta access, seeding tournaments, or community work.
* **Not started everywhere** flags players who have never touched gamification at all. For most brands this is the largest group you have.

Each refreshes daily, is per player, and counts deliberate engagement only.

#### Using it in your CRM

The output is available to your CRM journeys, backoffice reports, and the user-property feed. Common uses:

* Run a feature-introduction journey only for players Not started on that feature.
* Route Lapsed players into a win-back path referencing their past activity.
* Split Starter A and Starter B into different messages.
* Show Engaged players how close they are to the top rung.
* Exclude Protect players from promotions and hand them to your VIP team.
* Use the recommended feature to decide which product widget to pin in a player's lobby.

The recommendation is always a suggestion. Your campaign rules, budget limits, and responsible-gambling and affordability controls come first.

#### What good looks like

Over time, the share of players at Not started falls, the share at Lapsed falls, and players move up the rungs on the features you've been pushing.

The clearest early sign is that campaign spend becomes more concentrated. Instead of promoting five features to everyone, you promote one feature per player, and get more movement for the same budget.

Your own best feature is the benchmark. If a quarter of your players are Power users on one feature and almost none have started another, that gap isn't about your players. They have already shown they go deep when a feature reaches them.

#### Common questions

**How often does it update?** Every day.

**Can I override it?** Yes. It's a suggestion. Your campaign rules and your responsible-gambling and affordability controls always take priority.

**Why is my engagement number higher than the one here?** Auto-enrolment. If your platform enters players into tournaments or assigns missions automatically, your figures count those and this model doesn't. It will only ever affect Missions and Tournaments.

**Why aren't leaderboards or raffles included?** Players usually end up in them without doing anything, so there's no way to tell real interest from passive inclusion. Scoring them would produce a number that doesn't mean anything.

**A player's recommended feature changed since last week. Is that a problem?** No. Players move between rungs as their behaviour changes, and the recommendation follows.

**Why does one feature show 100% Not started?** Usually because it isn't live for your brand. Check that first.

**Does Not started mean the player won't like the feature?** No. It means they haven't tried it. For most brands this is the biggest opportunity you have.

**Why would I not promote to a Power user?** They are already doing what you would be asking them to do. Promoting to them spends budget for no change in behaviour, and risks fatigue with your most valuable players.

**What does the value gap actually tell me?** It compares what players typically deposit at one rung against players at the next rung up. It shows where the largest differences sit across your player base, which is how features are ranked against each other. It is a guide to where opportunity is concentrated, not a forecast of what one campaign will return.


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