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To Yield or Not to Yield – that is the Question


Yielding, as we define it here, is simply segregating demand based on implied profitability. In this blog, we build on the table games analytics strategy post and intend to make the qualitative case that profit maximization is an outcome – rather than a goal of yielding – because yielding allows us to prioritize the right type of demand and aligns strategy with operations.

Usually, when yielding we segregate demand based on price because the higher the price, the higher the implied profitability. When applying this concept to table games, the following is a useful segmentation model:

  • Time-constrained patrons
  • Wallet-constrained patrons


Time-constrained patrons
: Patrons in this segment usually run out of time before they run out of budget or their wallet. They are usually high-value players, less sensitive to price and a long cycle time. With the right gaming experience, they are likely to remain loyal to the property.

Wallet-constrained patrons: This segment consists of patrons who have a limited spend and are more sensitive to the price or table minimums.

All casinos will have patrons who fall in each of these segments in different proportions. Player ratings data can be used to study the player segments. Of course, there are many other factors that need to be incorporated such as table utilization, game type and game pace.

 

Levers to Manage Demand

 

As an operator, the goal should be to ensure that we’re not sacrificing the experience of time-constrained patrons at the expense of wallet-constrained patrons. The only approach that will allow us to attain that goal is to influence the levers that can be controlled: table capacity, open hours and table pricing.  As the demand fluctuates between these two segments, prioritizing the seats for the time-constrained players will ensure that we are maximizing the experience for these gamers, in short, yielding the floor.

Marketing spends enormous efforts trying to get high-value patrons, who are predominantly time-constrained, into the casino. Hence, it is imperative to think about what happens when these patrons show up and they do not get a seat at the table, or it’s too crowded for their liking.

How hard does it progressively become for marketing to bring these high-value patrons back after they’ve had a bad experience? What happens to the acquisition cost of patrons when there is a gap between what is promised by marketing and what is delivered by operations? Without yielding, we risk alienating high-value patrons at the expense of the budget patrons.

It may be helpful to draw an analogy with the hotel industry from the customers’ perspective. Do we as customers expect rooms to be more or less expensive on weekends vs. weekdays? Do we expect to pay more for better service – either in form of a better room (suites vs basic rooms) or better services (e.g. lounge access or butler service). As customers, we intuitively understand that we need to pay more to get more and I believe that extends to our table games patrons as well.

It is a fine strategy to target high volumes of low-value customers; Walmart has built a phenomenal business by competing on low price. However, should we choose to do that, we must align our marketing to that strategy by cutting back on reinvestment as well as the type of experience – no high end spaces – and focus on simply advertising our low prices.

Outside of that, a better and a more realistic approach is to prioritize serving high profitability segments. We already do this by offering the same game at different price points. However, if the open hours and pricing strategy does not change as demand fluctuates throughout the week, then we are again at risk of alienating a segment of the business, whether it’s the time-constrained player who can’t find a seat during peak periods, or a wallet constrained player who can’t find a seat during off-peak periods. This approach will also result in repeat visits from the patrons as operators offer a consistent gaming experience.

In our view, to yield or not yield is not the question to focus on at all – of course, we should yield. Instead, the right question to ask is: are we yielding in way that is consistent with our patrons’ expectations? The answer is what decides whether marketing is driving the right customers, if customers are having the desired experience, if the experience is engendering loyalty and whether this virtuous cycle is driving profits – both in the short and long run.

Key Takeaways

The key takeaways from the article can be summarized as follows:

  • As an operator, it is imperative to understand your patrons by analyzing ratings and operational data and study their gaming preferences.
  • There are three levers available to manage demand – capacity, open hours and price. Prudent use of these levers allows servicing the demand in a way that is consistent with the patron’s gaming preference while maximizing profitability concurrently.
  • Finally, it is important to have an alignment between marketing and operations so that marketing is driving the right types of patrons and operations is set up to create the right experiences for them based on expectations set by marketing.

Authors:

Varun Nayak
As Tangam’s Senior Vice President of Gaming Strategy, Varun has over 15 years of experience in technology, finance, and casino analytics. Previously, he oversaw gaming optimization and established analytical processes to measure and improve profitability at Sands China in Macau and Caesars Entertainment in Las Vegas. Varun is a computer scientist by training and received his MBA from UCLA Anderson in Finance and Strategy.

 

Maulin Gandhi
As one of the founding executives, Maulin currently serves as the President of Tangam Systems. With over thirteen years of experience helping operators improve business performance with data science, Maulin has overseen Tangam’s growth to the global leader in Table Games analytics. He received his Computer Engineering Bachelor’s and Master’s from the renowned McGill University in Montreal, specializing in Artificial Intelligence.