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Pre-Match Alerts - Favorite Type

Blair Matheson
  • Updated

The Pre-Match Alerts - Favorite Type feature allows you to create campaigns tailored to your customers' preferences by highlighting upcoming events that match their favorite league or type. By leveraging betting history, you can deliver personalized recommendations that drive engagement and enhance conversion rates before the event begins.

Functionality

This feature identifies users' preferred category-class-type combinations based on their betting history, monitors upcoming events that match these preferences, and sends personalized recommendations before the event starts.

  • Identify Favorite Types: Analyzes betting history to determine each user's favorite league or type.
  • Monitor Upcoming Events: Scans for events that match users' favorite type preferences.
  • Send Timely Recommendations: Alerts are delivered before match start time for popular events.

How it Works

  1. Analyze Betting History: The system reviews past activity to determine each user's favorite sport type (category-class-type combination).
  2. Identify Popular Events: It scans the inventory for upcoming events that match these preferences.
  3. Match Preferences: Users are matched with events that feature their favorite type combinations.
  4. Exclude Duplicate Bets: Users with existing bets on an event are excluded from receiving alerts.
  5. Produce Recommendations: Selection-level recommendations are generated and sent before the event starts.

Configurable Parameters & Terminology

  • Activity Window: Determines how recent a user's activity should be considered.
  • Type Lookback: Days over which to analyze type preferences.
  • Type Threshold: Minimum number of bets required to qualify a type as a favorite.
  • Min Hours Before: Minimum hours before event start when alerts can be sent.
  • Max Hours Before: Maximum hours until event start for sending alerts.
  • Minimum users per event to be popular: Minimum user engagement required for the event to qualify.

Outputs & Data Points

When the system generates a recommendation, it provides the following outputs:

  • userid: Identifier of the targeted recipient.
  • category_name: Category for the event.
  • class_name: Class for the event.
  • type_name: Type for the event.
  • event_key: Unique identifier for the event.
  • event_name: The title of the event.
  • selection_key: Unique identifier for the recommended selection.
  • selection_name: Name of the recommended betting option.
  • event_date_time: Scheduled date and time of the event.
  • odds: Betting odds for the selection.
  • event_popularity: A score representing the event's popularity based on user engagement.

Data Integration Requirements

For proper operation, this feature integrates with the following data sources:

  • Bet Place (Mandatory): Contains key fields such as user ID, category name, class name, type name, event key, bet action, and event date/time.
  • Inventory Snapshot: Provides essential fields such as eventKey, eventName, categoryName, className, typeName, selectionKey, selectionName, decPrice, and eventDateTime.

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