> 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/bonus-eligibility-model.md).

# Bonus Eligibility Model

## Bonus Eligibility - Help Guide

### What it is

Bonus Eligibility tells you, for each player and every day, whether it makes sense to give them another bonus.

It looks at how a player has been behaving lately (their real-money play, their deposits, and the bonuses they've had) and gives you a simple answer you can act on: yes, no, or not enough information yet.

It's there to guide your decisions, not to make them for you. Nothing is granted or blocked automatically. You choose how to use the answer in your journeys, host tools, and reports.

### What you get

One row per player, per brand, refreshed every day. Each row gives you two things:

* A verdict, the short answer: Eligible, Suppress, or Unknown.
* The reasons behind it, written in plain terms (for example "Self Funded" or "Loses over time"), so you can see why the player got that verdict.

| Verdict  | What it means                                 | What you might do                                 |
| -------- | --------------------------------------------- | ------------------------------------------------- |
| Eligible | Recent behaviour supports another bonus       | Go ahead and grant                                |
| Suppress | Recent behaviour argues against another bonus | Hold off, or try a non-bonus offer instead        |
| Unknown  | Not enough data to decide                     | Fall back on your usual rules. This is not a "no" |

<figure><img src="/files/WJOwAfD6r7RhUdmaOjQ8" alt=""><figcaption></figcaption></figure>

Every brand only ever sees its own players.

### How the verdict is decided

The verdict comes from four separate signals, each looking at the player from a different angle. Each one has a weight, so some count more than others:

* Profitability - 35%
* Bonus Effectiveness - 30%
* Bonus-to-Deposit Ratio - 25%
* Bonus Share - 10%

A player is only given a verdict when at least three of the four signals have enough data to run. The scores that did run are then re-balanced so the missing one doesn't skew the result. This keeps things fair, so a player is never judged on a single signal.

Here's what each signal asks, and what a good or bad answer looks like:

<table><thead><tr><th width="131">Signal</th><th width="96">Weight</th><th width="207">The question it asks</th><th width="149">Good sign (leans Eligible)</th><th>Warning sign (leans Suppress)</th></tr></thead><tbody><tr><td>Profitability</td><td>35%</td><td>Does the player win or lose over time?</td><td>Loses over time, so bonusing is sustainable</td><td>Wins over time, so bonusing eats into margin</td></tr><tr><td>Bonus Effectiveness</td><td>30%</td><td>Do bonuses lead to extra real-money play, or just replace money the player would have spent anyway?</td><td>Bonus drives extra real-money activity</td><td>Bonus replaces the player's own spend</td></tr><tr><td>Bonus-to-Deposit Ratio</td><td>25%</td><td>Is the player taking a normal amount of bonus for what they deposit, compared with others?</td><td>In line with peers</td><td>Bonus-heavy for what they put in</td></tr><tr><td>Bonus Share</td><td>10%</td><td>Is the player mostly funding their own play, or leaning on bonuses?</td><td>Self Funded</td><td>Bonus Dependent, likely just chasing bonuses</td></tr></tbody></table>

Profitability carries the most weight because it's the clearest sign of whether it's worth keeping the bonuses going. Bonus Share counts the least, because on its own it only tells you how a player funds their play, not whether bonusing them pays off.

### How each score is worked out, and what it needs

Each signal only runs when the data behind it is coming through your integration. If that data isn't there, the signal sits out. And if fewer than three signals can run, the player comes back as Unknown. The model would rather say "I don't know" than guess.

**Profitability (35%)** Looks at how much the player is worth to the brand over the last 30, 60, and 90 days: what they bet against what they won, what they deposited against what they withdrew, and the same again after bonus costs. It needs betting and deposit/withdrawal records. It sits out if the player has had no activity to score.

**Bonus Effectiveness (30%)** Compares the player's deposit behaviour on days they got a bonus against similar days they didn't (within two weeks either side of a bonus), over the past year. If they fund more of their own play around bonuses, the bonus is helping. If they fund less, the bonus is just standing in for their own money. It needs at least one bonus day and at least three comparable non-bonus days for that player. It sits out if there aren't enough of either to compare.

**Bonus-to-Deposit Ratio (25%)** Looks at how much bonus a player takes relative to what they deposit, compared with their peers. Where the bonus amount is known, it uses that. Where only the bonus itself is recorded with no value attached, it counts bonuses against deposits instead. It needs bonus records and deposit records. Amounts make it sharper but aren't essential.

**Bonus Share (10%)** Measures how much of a player's play is funded by bonuses rather than their own money, over the last 30 days. For this to work, the player's bets need to be cleanly split into real money and bonus money. If a brand's bets can't be split cleanly, this signal sits out. That's the single most common reason a whole brand shows up as Unknown.

#### What the model needs from your integration

| Data coming through the integration               | What it powers                                                        |
| ------------------------------------------------- | --------------------------------------------------------------------- |
| Redeemed bonuses                                  | Effectiveness, Bonus-to-Deposit, Bonus Share                          |
| Bets cleanly split into real money vs bonus money | Bonus Share                                                           |
| The value of each bonus                           | The sharper version of Bonus-to-Deposit (otherwise it counts instead) |
| Bets and wins (casino and sport)                  | Profitability                                                         |
| Deposits and withdrawals                          | Profitability, Bonus-to-Deposit                                       |
| Recent activity                                   | Whether the player is scored at all                                   |

### When the answer is "Unknown"

A player shows as Unknown when fewer than three signals could run. This is a real "we can't tell", not a quiet "no". Treat it as a cue to use your normal rules, not a reason to hold back.

It usually comes down to one of these:

* The player is new or barely active, so there isn't enough recent history to read.
* The brand's bets can't be cleanly split into real and bonus money, so Bonus Share and the other real-money reads can't run. This is the most common cause at the brand level.
* Bonus Effectiveness isn't available for that player or brand yet. When that happens, the other three signals carry the verdict between them, and the player picks up the fuller picture automatically once Effectiveness is available. There's nothing you need to do.

### Each of the four signals also works on its own

The combined verdict is one way to use this, but each of the four signals is also a player property in its own right. You can use any of them directly without going through the verdict. All four sit alongside the verdict in Lightdash and the user-property feed, ready to segment, target, or report on.

<figure><img src="/files/KSlUZ6cFpYF3UfEcfscE" alt=""><figcaption></figcaption></figure>

<figure><img src="/files/pEsXyoHzQlggydeZLSoK" alt=""><figcaption></figcaption></figure>

A few ways people use them on their own:

* Bonus Share (Self Funded or Bonus Dependent) tells self-funding players apart from bonus-chasers, which is handy for VIP, retention, or abuse checks.
* Bonus Effectiveness (helping or replacing spend) gives you a responsiveness group: the players who actually react to bonuses. Useful for targeting and planning campaigns.
* Bonus-to-Deposit Ratio (in line or out of line) is a quick read on bonus efficiency and possible abuse.
* Profitability (wins or loses over time) is a straight value-and-margin read, useful anywhere you'd otherwise reach for a value score.

Each one refreshes daily, is per player, and shows Unknown when the data isn't there, exactly like the combined verdict.

### Using it in your CRM

The output is available to your CRM journeys, host tools, Lightdash reports, and the user-property feed. Common ways to use it:

* Only run a bonus journey for players marked Eligible.
* Send Suppress players down a non-bonus path instead, such as a tournament or a content offer.
* Let Unknown players fall through to your existing rules rather than blocking them.

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

### What good looks like

You'll know the model is doing its job when, over time, your bonus spend and the number of bonuses go down while play stays flat. In short, you spend less on bonuses without losing activity, because you've stopped bonusing the players who don't need it, don't respond to it, or already cost you money.

### Common questions

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

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

**Why is one of my best players marked Suppress?** Usually because of profitability. A player who keeps winning gets flagged to protect your margin, even if they play a lot. The reasons on the row will show you which signal drove it.

**Why is a player Unknown?** Fewer than three signals had enough data, usually because of thin history or because Effectiveness isn't available for that brand yet. It isn't a suppression.

**Does Suppress mean the player is a problem?** No. It just means another bonus isn't the right move for that player right now.


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