Online slots are one of the most sought after sort games, and developers work to make more convenient slots. However, the slots industry relies more on data-based decision making to add to their data analytics team. Data analytics could be difficult to explain; however, Alexandra Vasilkova (view profile), makes the complex world simple by explaining all issues regarding data analytics.
With knowledge in numbers, spreadsheets and contagious enthusiasm, readers get much from him. Our expert is competent in data analytics technology and artificial intelligence. He is willing to take us through the evolution of slot management and what we are missing in our metrics.
Slots machine management is based on a primary metric commonly used throughout the industry- Win Per unit (WPU). Win Per Unit is defined as the amount of win, theoretical or actual, that a machine averages over a given time, such as Win Per Unit Per Day (WPUPD). It is usually combined with another metric known as house average or the average WPU of the floor.
Time and again, the metric is used as a base for decisions regarding slot machine purchases, theme change, configuration and movements. All signs seem to display that the metric is working incredibly, judging by the success of casino slot machines.
The most cumbersome issue is that WPU appears to be outside the fundamental laws of supply and demand. Some people tend to pose the question of whether WPU is a pure reflection of the market and slot machine management.
To clear the air, WPU is not a reflection of demand. Most of the time, the highest WPU are found on high Limit slot machines, and people are not likely to play them. On the contrary, some devices are ever occupied, although their WPU is below house average. What does WPU indicate?
There is no clear definition for demand metrics when playing in fast withdrawal casinos. Gambling platforms are known to sell games, and they sell games at a time. In blackjack games, they are known as hands, but they are known as pulls on slots. What is the value of a pull? The price of a pull to a player is $0.25- $25 a spin.
Casinos are a little craftier in the price as the bet times the house edge of the game. However, it is easier to have a picture in mind as the bet per spin. The demand is the number of customers pulling for any specific game. On the other hand, the supply is the number of pulls available, while the price is the distributed price per pull.
Using total pulls available results in having lots of pulls. Let us break it down. When a machine plays at ten pulls per minute, it means that ten pulls *60 minutes *24 hours a day, totalling 14,400 pulls in a single day.
The best explanation for such a scenario is that few games will come close to 14,400 pulls a day; the busy ones included with such a method its possible to see utilization percentages of 30% or 40% even on active games. Each game has a different pull rate. There are machines with eight pulls per minute and others with 15 pulls per minute. The trick to increasing demand is to drop the pull speed.
However, there should be another number to understand occupancy and its occupied positions truly. When a gamer sits on a slot machine, the machine is sold and no longer available for purchase regardless of their play speed. Have you ever been to the floor of a traditional casino? Slots machines capture the eyes of gamblers on sight, and the slots are occupied positions.
On achieving demand through customer segments, operators can optimize the slot floor’s supply and pricing, such as slot movements, slot purchases, minimum bet, and an optimized house edge for customers. The evolution of slot management to supply optimization has a huge potential to increase slots revenue.
The online slots market is already flourishing. A world of slot optimization arises when a new set of metrics revolving around supply and demand is defined.
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