Amplifier AI Glossary

The total number of active users who have placed at least one bet in the selected time period. These are users who have placed bets before the selected time period.

Audience History

An audit log of your recently created audiences and get an overview on your total audience reach.

Average Bet

Average bet is defined as turnover generated per round. The formula for this calculation is average bet = turnover/rounds.

Bad Beat

This reason code indicates the percentage of users who were predicted churn due to losing a near win bet. A bad beat is defined as a lost single bet with odds lower than 1.25 or a lost accumulator that has more than 3 selections with only one losing selection.

Bets/ Stake/ Wager

Daily Bets: median daily player stake on a game

Total Bets: sum of stakes

Bet Builder

A feature that allows a customer to create custom bets. This is an attribute that can be selected to create custom audiences on dynamic audience product.

Bet Type

An attribute that helps you select customers who have placed a certain bet type. Examples include Single, Double, Accumulator, Lucky 15 and Yankee.

Big Wins Multiplier

Spot players with high-value wins to power VIP campaigns, reward loyalty and deepen engagement.

Bet Type Range

Similar to bet type but this attribute allows users to select a range, from Single (SGL) to Accumulator 25 (ACCA-25).

Bonus Bet Value

Target players whose recommended bonus values fall within a specified range, based on Amplifier AI’s bonus recommendation system.

Bonus Spins

Bonus spins are assigned to players to encourage more spins. It is the same as Promotional Free spins.

Bonus Turnover

The turnover per player is calculated based on their usage of bonus spins. This will not be considered as a part of real money turnover.

Churn Predictions

This reason code indicates the total number of churn predictions that were sent to the operator via the API in the selected time period.

Churn Prediction % - Active Users

This indicates the percentage of users who were at risk of churning in comparison to all the users who have placed bets in the selected time frame.

Churn Prediction % - Settled Bets

This indicates the percentage of users at risk of churning from the total number of users who had a settled bet and no active bets.

Clusters

Future Anthem splits players into groups using behavioural clustering (unsupervised learning models). Player behaviour is assessed across a variety of attributes including daily game sessions, total spins, total stakes, bonus stakes, and session length.

Anthem uses this method to cluster players by game, by day, to provide a consistent framework, and to compare games.

Competition

Specific league, tournament, or championship filter within selected sports such as English Premier League and Wimbledon Singles to pick out customers who have bet on specific competitions.

Customer Profitability

it is a filter for players based on the net profit they’ve generated for your business within a selected time range, available in Dynamic Audience product.

Consecutive Losses

This reason code indicates the percentage of users who have three or more consecutive losses.

Daily Active Players (DAP)

Daily distinct player count

Engagement Drop

An attribute to Identify players showing a significant decline in engagement score to drive targeted re-engagement campaigns.

Engagement Score

Target players based on their engagement score, which is powered by Amplifier AI. Use this attribute to re-engage low activity players or to connect with highly engaged players for better campaign performance and relevance.

Event ID

A specific event identifier to target customers who have placed bets on particular matches, games, or races. This unique identifier allows operators to hone in on customers with activity on specific sporting events for precise audience targeting and marketing campaigns.

Favourite Game, Most Played Game, Most Recent Game

Target players based on their favourite, most played or most recent game to deliver highly personalised promotions and content.

GGR

Gross Gaming Revenue

Formula: Total Stakes – Total Payouts

High-Value Clusters

High-Value players do not usually play as many spins as High-Value Multi Session clusters, however, they place bets of similar average size. They contribute the most to total GGR and NGR due to their sheer player volume, and usually have second highest RTP

High-Value Multi-Session Clusters

High-Value Multi Session players tend to have the highest number of rounds, sessions, highest bet value, and highest RTP. They are termed multi-session for playing multiple sessions of the same game per day

Hit Rate

Formula: (spins with payout > 0)/ total spins

Key Performance Indicator

A quantifiable measure of performance over time for a specific objective. For example, revenue.

Low-Value Players

Low-value players have the lowest contribution to all the metrics compared to other clusters

Market ID

Enter the specific Market identifier to target customers who have placed bets on particular betting markets within events (e.g., Match Winner, Over/Under Goals, First Goalscorer). This identifier enables operators to segment audiences based on customers' preferred betting market types and risk profiles.

Mid-Value Multi-Session Players

Mid Value Multi-session players play fewer rounds than High-Value clusters, place smaller daily bets, have smaller session lengths and less RTP than the High-Value clusters and play multiple sessions of one or more games.

Mid-Value Players

Mid-Value players play even fewer rounds than Mid-Value Multi-Session players, place smaller bets, or have similar session lengths but usually play one session for the respective game.

Monthly Active Players (MAP)

Monthly distinct player count

Month Till Date (MTD)

Month Till Date (MTD) stands for values on the latest day of the current month. For example, a column for GGR Month Till Date will show the GGR values accumulated until the current day of the month.

Most Player Increases

This visualisation in Optimise lists top 5 operators in terms of increase in daily average players on a week on week basis, for the last 7 days.

Negative Experience

This option will help you target customers who are identified through the Real-time Churn Prediction Engine based on the following reason codes:

- Bad Beat for Single and Accumulator bets
- Consecutive Losses

NGR

Net Gaming Revenue

Formula: GGR – Promotional Free Spins Payouts

New Active Users

Total number of new users who placed their first bet in the selected time period

New/Retained Player

New Players: players within their 10 days of tenure (current date – registration date)

Retained Players: all the rest

New Registered Users

Total number of users who have registered in the time period. These are users with newly created accounts who did not place any bets in the selected time period.

Operator Opportunity

This page in Optimise allows studios to see the total bets placed for each game, for each operator. Values are only shown for games that have been released.

Other (reason code)

The percentage of users for which churn was predicted and no clear reason code could be identified for churn.

Players

There are many different classifications of players, the is usually unique players as opposed to daily average players.

Related terms: Turnover per player & Rounds per player

Player Retention Rate

Retention rates are derived from a weekly cohort analysis. The analysis considers the return of players on the same game, from the first time the player plays a game.

Standard retention KPIs shown in the report are:

W1 retention: average retention rate 1 week across all cohorts
W4 retention: average retention rate 4 weeks across all cohorts
W8 retention: average retention rate 8 weeks across all cohorts

Player State

This attribute categorises players into actionable states; Lapsed, Dormant and Churned, based on their individual inactivity patterns. There is no fixed time period for each state. Instead, an inactivity threshold is calculated uniquely for each player based on their historical betting frequency.

Promotional Free Spins

Total promotional free spins stakes

Real Money Bets

Total Bets placed without considering bonus bets.

Real Spins

Total spins without counting bonus spins.

Real Stakes

Stakes placed without bonus stakes.

Reason Code

Every churn prediction provides a contextual reason code to enable marketing teams to build tailored player messages, they include:

Reduction in spend
Reduction in frequency
Reduction in activity
Significant loss
Bad beat
Consecutive losses
Other

Reduction in Activity

This reason code indicates the percentage of users who were predicted churn due to a reduction in their betting activity. This reason code is triggered when the number of bets in the last 7 days is lower than the number of bets in the 7 days prior to that (day 7 - day 14)

Reduction in Frequency

This reason code indicates the percentage of users who were predicted churn due to a reduction in their betting frequency. The reason code is triggered when the number of active days (days bet placed) in the last 7 days is less than the number of active days in the 7 days prior to that (day 7 - day 4)

Reduction in Spend

This reason code indicates the percentage of users who were predicted churn due to a reduction in their spending. Their total stakes in the last 24 hours were less than their average daily stake.

Rounds

Daily Rounds: median daily player spins on a game

Total Rounds: total number of spins

Rounds per Player

Average number of rounds per player

RTP

Return to Player (actual)

Formula: Total Payouts /Total Stakes

Selection ID

Enter the specific ID’s to hone in on customers who have placed bets on specific events, markets and/or selections

Session

Game-session, i.e. if a player plays three different games consecutively we classify them as three different sessions. For the purpose of reporting, the sessions end after 30 minutes of inactivity.

Daily sessions: median daily player sessions on a game

Session Length

Median player session length

Session per Player

Average number of sessions per player.

Share of Turnover

The share of turnover is the percentage turnover for the release (based on selections made) against total turnover across all releases.

Significant Loss

This reason code indicates the percentage of users who were predicted churn due to a significant loss. A significant loss churn prediction is triggered when the amount lost by the user in his last bet is 50% or higher compared to the maximum of the 5 previous losses.

Spin Banding

In Optimise, we observe certain KPIs by their volume within specified ranges of spins, or bands of spins. For example, total spins can be arranged into the following bands: <5. 5-20. 20-50. Spin banding allows us to observe how much stakes were placed for these bands for each game.

Sport

In Dynamic Audiences, you can create audiences of customers based on specific sports. Examples in the pre-selected drop-down include Football, Horse Racing and Tennis.

Same Period Last Month (SPLM)

Same period last month. For example, the GGR SPLM column will show GGR values on the same day of the month, but last month.

Stake Banding

In Optimise, we observe certain KPIs by their volume within specified ranges of stakes, or bands of stakes. For example, total stakes can be arranged into the following bands: < £5, £5-20, £20-50. Stake banding allows us to observe KPIs, such as the volume of players who placed bets, within these ranges.

Tourists

Tourists contribute the least in terms of NGR and GGR, playing on average one session, placing the smallest daily bets, and tending to have the lowest RTP. But tend to be slightly higher than Low-Value players.

Turnover per player

This is calculated using ‘daily average players’. At present this value is a median.

Users with Settled Bets

The total number of users who had at least one bet settled in the selected time period and had no active bets after the bet settlement.

Volume

Player distinct count

Win Rate

Formula: (spins with payout > stake)/ total spins

Winners

Customers who have had at least one winning bet within a specified time-period.