Size of a Casino Business in 2009 Markeitng Models Assignment

Size of a Casino Business in 2009 Markeitng Models Assignment Words: 1532

Introduction Poker has become extremely famous all around the globe. Especially many TV channels start to present live tournaments where an unknown person transforms into a millionaire in Just a single week. Movies, like Rounder’s with Matt Damon of Lucky You also helped to spread the word around the globe. Once Poker is not very profitable for Casinos, the online alternative is became a very successful business. Besides some legal issues, on the on-line sites you can find people from all around the world.

Also on-line sites allow people to play as low as 1 .NET of a dollar or even free games with prizes. While on a Casino the bets used to star at 3 to 5 dollars with a minimum buy in of IIS$OHIO. In addition, the online web sites invest high money on TV ads’ and also sponsor famous players on live tournaments. All together creates an environment for online poker to be a very successful business. A word from the author After thinking about many markets to size or to diffusion, and almost giving up the assignment, I found out how fun would be to size the market of poke online.

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Start by playing some poker online, reading about the millionaire gambling industry, and even going to a real Casino in Tunics, was all I needed to do to learn more about this game and get inspired to start crunch some numbers. However, the intent of this paper is more to explain the background and the variables that affect this billionaire market, all the tables and numbers used can be found on the appendix. Objective A very good article at Wisped, mentions about the online market to be somewhere around $200 million.

I found this amount to be extremely conservative, especially regarding all the amount of money this websites invest on media and sponsoring professional players. One of the reasons might be that this number only considers websites placed on the United States. In 2005 the North Dakota House of Representatives authorized the online game inside the state, under many conditions. On legal matter the online game is very controversial, and because this, and also tax incentives, many of the online game companies are based on the Bahamas, and this might be the other main reason why the number is so small.

So the objective of this paper is to get a close look to the market and come up with a more realistic number. Sizing Players Hours per Week Based on some sample information from the two biggest web sites, it was possible to estimate an amount of players playing per hour of the week (see tables 1, 2 and 3). A rough number says that on a pick hour all sites sum up together to 324. 000 players. This information can be found right on the top of the site interface. (Postmasters is the market leader, and on a Sunday night had more then 110,000 players) Sources of Revenue Basically there are two main types of games, Tournaments and Cash Money. Tournament: Each player that decides to enroll on a tournament pays a fixed amount, for example IIS$11 ($1+$10). That meaner that one dollar goes to the site and $10 to a pot that will be split among the final players. A tournament has a certain time to start, everyone starts with the same amount of chips, and the blinds (mandatory bets for everyone in every round) increase continually, in order to spell players with low stakes. * Cash Games: On the cash games, people Just “walk by’ with different amounts of money and play until they are willing to. On this type, the sites charge what they call Rakes (see exhibit 1 for more details).

Basically the rakes are a 5% commission of the total pot, but it always has a ceiling. For example “$0. 05 for each $1. 00 in the Pot to a maximum of $3. 00). That’s mean, if the pot goes to $200, the site will charge $3 instead of $10. For this paper I will not get into the detail of different types of Cash Games, such as Limited, Pot Limited or Unlimited. The types don’t affect the final calculation in a significant matter. Sampling For all financial numbers you will find further, I calculated a sample of one hour of all games in rather to have the best distributions among low stake and high stake games.

Also in order to split the market between Tournament and Cash Games. Based on an hour sample from a tournament at Postmasters we found out 1 5637 players on a Friday 4 PM. With the data from Tables 1, 2 and 3 we could derive the percentage among both game types (see also Table 4) Size of the Market From table 3 and percentage among game types we have the amount of playing hours per week for each game. On a normal poker game, people used to play 30 hands (30 rounds) per hour. On-line game is much faster, sometimes averaging 90 hands per hour.

In order to be conservative with our model, let’s use 60 hands per hour. Rakes were calculated on a base of $1. 17 per table per hand (or $0. 6 per player per hand). Our sample (see samples) shows an average of 7 players per table. For tournaments we used the information on Table 4 (build based on the information from sample 2), and the total revenue for tournaments is approximately IIS$89 million. The total revenue from the on-line poker websites all around the world is 1 It is 6 times bigger than the information that Wisped has for the year of 2005.

Many facts can lead to this huge difference, but as mentioned before we can attribute from the fact that abroad companies would hardly be official measure by any authority. As many of all different kind of services used to offer now a days, poker sites has a retention program. The main sites you can accumulate points to play for big prizes in the future. Also knowing their customer, they send e-mails offers of products (such as cards, chips and other kind of poker merchandise) or even communicating about big events, such as the World Series of Poker.

Marketing The model as any other has its flaws. Many of the numbers are estimations and this can lead to a different number than the real one. But that doesn’t mean is reliable. Having the amount of clients per hour per site is a strong information for the model ND this is an easy data to get, and in this model can be easily improved by having a membership on every single site and log-in on every single hour. A problem with that a wrong estimative might cause is for a new entrant that needs to build a business case before investing the capital.

If he consider a market size of 1 billion and believes with his product he will be able to capture 5% of the market, De go decision would be based on a expected revenue of 60 million. The worst case scenario would be the 200 million dollars data from Wisped; in this case the investor is looking for a business of 10 million in revenue. Considering that the infrastructure investment for an online poker site is not that big, a good strategy would be to start small and then as the investor see potential, increase the investments on ads and other marketing initiatives.

Models Having the advertisement spending for the main players of this market would be good information to factor in. With it I could compare revenue versus spending and found out an estimate profit from the operation. Yikes The two biggest challenges were to build the two revenue samples for tournament and cash game. It was an exercise of looking into many different data and variables ND figure out what would be a good way to sample all the information. If I could import all the information from the screen to an excel sheet, would be heaven.

Appendix (Blue meaner observed data, and orange projected data) (In blue the correspondent percentage of “utilization” based on observed data. All the others was projected based on the observed data) (Amount of players per hour based on the number in table 1 and proportions in table 2) Exhibit 1 Sample 1 (From 10 page downs on the website I sample the top 3 games running and bottom three from each page down in order to calculate average players and average pots. Rakes = 5% of the average pot.

The final number is the rake with the ceiling that meaner force to be equal or lower than $3) Sample 2 (In a random hour at Postmasters I sample the number of players and the entry fee, then I factor it to the market and different times. Based on this sample I build the table 4) Print Screens to build the Samples Screen from the tournaments running on a specific hour. Details, such as entry fee, of each could be found by double clicking on each one. Screen from the online game. It had more than 10 page downs of it. For the sample I picked the info from top three and bottom three of each page down.

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