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On-Demand Audiences: Self Service - Sports Attributes

This section explores the available Sports attributes that help you better personalise audiences for marketing campaigns and promotions

Drive campaign impact with flexible, personalised audiences

Instantly create tailored audiences in the moments that matter most. Leverage powerful targeting attributes to personalise messaging, promotions and campaigns based on player behaviour, preferences and Sports activity - all driven by real-time, up-to-date data.

audiences_sports

  • Customer Country: If applicable, kick-off by filtering your audience by customer location - choose the countries they’re from.

  • Sport: Create audiences of customers based on specific sports. Examples in the pre-selected drop-down include Football, Horse Racing and Tennis.

  • Class: Look for particular classes when identifying audiences. For Football classed examples would include UK Football and European Major Leagues.
  • Competition: Enter competitions such as English Premier League and Wimbledon Singles to pick out customers who have bet on specific competitions.
  • Event Id, Market Id and Selection Id: Enter the specific ID’s to hone in on customers who have placed bets on specific events, markets and/or selections.

  • Market Name: Look to target customers who consistently bet on the same market. When in the naming convention, ensure to include the pipes when entering a market name, for example |Both Teams To Score|.

  • Bet Type: Gives you the ability to target customers who have placed a certain bet type. Examples include Single, Double, Accumulator, Lucky 15 and Yankee.
  • Bet Type Range: Same as Bet Type but allows you to select a range, from Single (SGL) to Accumulator 25 (ACCA-25).

  • Bet Builder: Target customers who have placed a bet builder.

  • Winners: Identify customers who have had at least one winning bet within a specified time-period.
  • Customer Profitability: Filter players based on the net profit they’ve generated for your business within a selected time range.
  • Negative Experience: This attribute lets you target players based on actual events, not predictions, using configurable variables such as minimum odds or the number of consecutive losses. The reason codes include:
    • Bad Beat: Targets players who narrowly lose a bet. A bad beat is defined as either a lost single bet with odds below a configurable threshold (default 1.25) or an accumulator bet with more than a configurable number of selections (default 3) where only 1 selection loses.
    • Consecutive Losses: Targets players who have experienced a configurable number of consecutive losses (default 3), helping identify those at risk of disengaging.
  • Active Users: Target players who have been active and placed at least one bet during the specified time period.
  • Active Days: Select customers based on how many days they have been active in a specific sport. This will help you target genuinely engaged customers.

With the integration of the Bonus Recommendation feed into the Audience Identifier feature, the following data points are also available and can be used as attributes to create audiences:

  • Bet Bonus Value: Target players whose recommended bonus values fall within a specified range, based on Amplifier AI’s bonus recommendation system.
  • Engagement Score: The engagement score is a personalised metric from 0 to 1, reflecting a player’s recent activity and level of engagement. Higher scores indicate highly engaged players and lower scores indicate reduced activity. Operators can use this metric to re-engage low-activity players or reward or upsell to highly engaged players to drive more relevant and effective campaigns.
  • GGR: Target players based on their GGR margin by selecting a custom value range. Use this to incentivise low-margin players to increase their activity, or focus on high-margin players who contribute significantly to revenue. This enables tailored offers that align with player value and business goals.
  • Player State: Players are categorised into Lapsed, Dormant and Churned based on their personalised inactivity thresholds rather than fixed time periods. Each player’s threshold is calculated from their historical activity, so the same period does not apply to all players. 

Player State example: If a player’s inactivity threshold is calculated at 7 days:

  • After 7 days without activity → Lapsed
  • After 14 days → Dormant
  • After 21 days → Churned

 This approach ensures targeting is tailored to each player’s behaviour. 

How do I get support on creating an audience?

Visit our 'here to help' form or contact your account manager and we will provide technical support.