> 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/bi-and-reporting/favorite-product.md).

# Favorite Product

## 📘 Overview

The Favorite Product Dashboard provides an overview of the [Favorite Product Segmentation](https://help.smartico.ai/welcome/products/ai-models/favorite-product-game-game-type-and-game-provider#favorite-product), allowing you to monitor the activity distribution as well as the quality of the segments and the health of the business.

### Product Preference Categories

The dashboard categorizes users based on their 30-day betting activity across gaming verticals, applying an exponential time-decay model where recent wagers have greater weight:

* **Casino Only**: 100% of turnover generated in Casino games.
* **Sport Only**: 100% of turnover generated in Sports betting.
* **Lottery Only**: 100% of turnover generated in Lottery products.
* **More Casino, Less Sport**: Player wagers on both verticals, with Casino turnover strictly higher than Sports.
* **More Sport, Less Casino**: Player wagers on both verticals, with Sports turnover strictly higher than Casino.
* **Casino and Sport**: Equal turnover split between Casino and Sports.
* **Mixed Preferences**: Activity split across multiple verticals or involving Lottery combinations.

**🔍 How to Access the Favorite Product Report**

1. Navigate to Reports → Insights → Favorite product
2. Select: Period
3. Explore the Dashboard for detailed insights.

### Section 1: Value Scores split by Product Preference (%)

Use this chart to understand what differs between your Top, High, Medium and Low Value Score users in terms of the Product Preferences.

This chart displays a 100% stacked bar breakdown of each 30-day Value Score tier (Top, High, Medium, Low) across the seven product preferences. It helps identify which verticals drive the highest player lifetime value and where low-value players concentrate.

<figure><img src="https://77049817-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FfS5hl0PiysHtKAKMsQTe%2Fuploads%2Fgit-blob-30bced04573feb44fc37576d4feeb7900a3428e5%2Fimage.png?alt=media" alt=""><figcaption></figcaption></figure>

### Section 2: Product Segmentation split by RFM Models

Use these 3 charts to further understand the distribution of the Product Segmentations, referring to them as a business funnel from New Customers, moving to Promising, moving to Champions.

The three donut charts display the product preference distribution within each core RFM lifecycle stage:

* **New Customers**: Preferred products of newly onboarded players, revealing acquisition channel tendencies.
* **Promising**: Product preferences of players showing increasing engagement and frequency.
* **Champions**: The vertical mix of your most loyal, high-monetary players.

<figure><img src="https://77049817-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FfS5hl0PiysHtKAKMsQTe%2Fuploads%2Fgit-blob-1fff9623884ff3aaefd4765ce2eb7a5397651575%2Fimage.png?alt=media" alt=""><figcaption></figcaption></figure>

### Section 3: Weekly Distribution by Product Preference

Once you have an understanding on which distribution is healthiest for the business, based on the charts in sections 1 and 2, use this chart in order to understand whether the business moves in the right direction to increasing the value of the user base.

<figure><img src="https://77049817-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FfS5hl0PiysHtKAKMsQTe%2Fuploads%2Fgit-blob-3a8106af19fb00ec462298e9199965e3597e3c82%2Fimage.png?alt=media" alt=""><figcaption></figcaption></figure>

## 💡 Actionable Insights & Next Steps

* **Targeted Promotional Campaigns**: Build segments using Favorite Product Type to deliver vertical-specific offers (such as sports free bets to Sport Only players or free spins to Casino Only players).
* **Cross-Vertical Upselling**: Identify Casino Only Champions or High-Value players and introduce them to Sportsbook via tailored onboarding promotions.
* **Gamification Personalization**: Align dynamic mission tasks, tournaments, and mini-games to match the dominant product preference of your player segments.

### Frequently Asked Questions

**Q: How is a player's Favorite Product determined?**

A: Smartico analyzes 30 days of betting turnover across Casino, Sports, and Lottery using an exponential time-decay calculation where recent bets carry greater weight than older activity.

**Q: How often is the Favorite Product report updated?**

A: The underlying models recalculate nightly between 02:30 and 04:30 AM UTC. Dashboard visualizations and user profile properties reflect these updated classifications daily.

**Q: What happens if a player has not placed any bets in the last 30 days?**

A: For inactive users with no recent bets, the system preserves their last known favorite product classification rather than resetting it.

**Q: What is the difference between Favorite Product and Favorite Games?**

A: Favorite Product identifies the macro vertical preference (Casino, Sport, Lottery), whereas Favorite Games identifies the specific game titles, game categories, and game providers a player interacts with most.

**Q: Can I filter campaigns and journeys using Favorite Product?**

A: Yes. In the Segment Builder, use the condition Favorite Product Type to target specific preference groups, or filter by percentage share properties (such as Favorite Product Casino % or Favorite Product Sport %).


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