Why Do New Zealand Casinos Hire Data Science Staff?

With ever-increasing competition casinos have diversified their gaming ranges beyond video slot machines and table games into various offshoots like golf, theatre, and retail. Given the range of gaming, those who spend a lot only on casinos are losing out and the more significant players are the ones who participate in varied property offerings.

Analysis of spending behaviour and preferences leads to a total understanding of player profiles. Casinos are aware of the plagiarism that high rollers commit against them currently. They are now going deeper into the play base to identify gamers who go beyond the gambling floor using data analytics and customising themselves to the requirements.


The Expectation of a Player's Loss of Value in the Future?

Expectation of a Player's Loss of Value

Loss minimisation is fundamental to any business. Measurements like average daily theoretical loss or average theoretical loss are calculated by CasinoDeps sites with the fastest withdrawals predicated on historical behaviour, which yields a reliable database of future worth. The estimated average daily theoretical loss at Las Vegas is $500 – $600 in a year.

For example, a model can be made to foresee if potential gaming trip value could be generated on the basis of historical data on the basis of the credit line, theoretical win, actual win, nights spent, time, and average bets. Machine learning can be applied based on factors of race, sex, and ethnicity as well.

This sector contributed 35% to the revenue generated from entertainment in 2012 with an impressive $174m and has seen a healthy rise since.


What is the Worth of Each Individual Player

The value of a player is of note to casinos since their future spending behaviour cannot be foreseen. The data of variables it depends on are not available to casinos like ethnicity, income, and reason for taking a trip, either convention or vacation.

A team of university students working on the application of data science in the gambling industry shared their field notes.

It showed a player is  20% more likely to invest in a casino that accepts cryptocurrency and 34% more likely to place bets if the ads are customised.

Upon ascertaining the worth of a gamer, they are slotted into groups based on their pattern, and effective market strategies are planned around it. The gross returns from expenditure on online casinos have increased from $157m in 2016 to $206m in 2019.


Which Players are the Most Valuable

Other than the models discussed, there are ways to determine the worth of a player. The most common one being, trying to separate out the talented and the unqualified. This can be achieved by calculating the percentage of wins and losses of individual players in the gambling trips they take.

For example, if a player takes five trips and loses money in all of them then two valuable conclusions can be derived from it:

  1. They are poor players.
  2. They play until all their money is exhausted.

Given this background the player can be classified into the appropriate categories and knowledge of their behaviour can stimulate market planning and further analysis.


What Players Move Together?

What Players Move Together

The second consideration to determine a player's value is their household worth, defined as “the combined worth of a group of players who are likely to make their trips together.” This variable is tricky to determine since the value varies on changes as minor as:

  • whether the players stay in one room or opt for separate rooms.
  • It gets further complicated based on the situation. A player may play only when followed by another.
  • Additionally, a player can participate even without the company of others.

Household worth is difficult to determine yet can prove to be rewarding if achieved. Data that looks distinct and individual can get clubbed into households. Various player management systems have the functionality to join accounts so the players who move in groups, like spouses, get identified.

Taking the example of Las Vegas, two individual players’ losses (say, $500 and $600) can get clubbed together to give rise to $500 + $600 =  $1100 if the data is available that they are a couple and move in unison. Sadly for data scientists, business policies and system limitations do not always allow players to run multiple accounts based on taxing or gaming drawbacks.


Conclusion

Data science is a vibrant and fascinating field that can extract meaningful information out of random masses of data generated every second at casinos, gaming and gambling sites. Such applications provide unthinkable advantages and potential gains that could not be tapped into in the past.

Casinos can gainfully use it for their advancement but to be able to do so they must understand how to use this branch of science in their favour. NZ has seen a compound annual growth rate of 3.4% in this sector and in 2020 the net return will exceed $350m.

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