Asset Optimization Strategies

Selecting an Asset Optimization Strategy determines how the system handles capacity and how assets are assigned to purchases made through the system. It's important to note that Asset Optimization Strategies only applies to products with the following characteristics:

• Scheduled product type
• Utilizes asset management
• Limited capacity products
• Products utilizing the "Allow Single Use During Set Time (Up To Time Slot Capacity)" asset management strategy

While the above list are the requirements for any optimization strategy it's also important to note that these optimizations don't take effect (meaning either option works the same) if only 1 asset is used. The differences become apparent when a product uses multiple assets at the same time.

This article covers the following topics:

• Optimized for Sales
• Optimized for Assets

Related articles:

• Assets
• Asset Optimization Strategies

Optimized for Sales

This is the default optimization strategy. In this scenario purchases made will be split across multiple assets (if multiple assets are used.)  Using this strategy can results in higher revenues because the seats on the assets are maximized but can oftentimes result in decreased customer satisfaction due to parties being split between assets and/or higher manual time and effort to optimize placements of parties within assets after purchase.

Here's an example of how a sales optimized product would work:

Because the system can split parties across multiple assets the capacity shown to a customer able to purchase is 18 seats.

John Smith makes a purchase for a party of 4. The system assigns this purchase to Boat A and the availabilities now looks like this:

The system will show a customer availability of 14 seats available for purchase. Pepper Potts now makes a purchase for a party of 3. The system identifies there are still seats available on Boat A and assigns 2 of the 3 to Boat A. There are still outstanding seats needed for Pepper Potts' reservation so the system then assigns 1 to Boat B. The availabilities now looks like this:

Using this strategy there are now 11 seats available to other customers to purchase. You, as the operator, didn't have a single seat remaining on Boat A that could be challenging to sell resulting (potentially) in higher revenue, but the Pepper Potts' party is upset because they were unaware they wouldn't be on the same boat.

Optimized for Assets

In this strategy the system intelligently determines at time of purchase which asset is best suited for the size of the party. This often results in higher overall customer satisfaction because parties sit together but can also result in a reduction in revenue because you could end up with single seats remaining on assets which can be hard to sell. Because the system handles the assignments it often results in reduced workflows and manual efforts on the operators' part to manually assign parties to assets. 

Let's look at how an asset optimized product would work:

Because the system can't split up parties using this method it treats capacities differently than other ways. The maximum seats available for purchase in this scenario would be 6. However this strategy also supports the ability for assets to contain different amounts of capacity. In this case the system will always show the highest amount of seats available for an asset. 

John Smith makes a purchase for a party of 4. The system assigns this purchase to Boat A and the availabilities now looks like this:

There are still a maximum of 6 seats available for purchase to a customer because Boat B and Boat C are still fully available.

Pepper Potts now makes a purchase for a party of 3. The system has identified that Boat A is not an option because only 2 seats remains on it so it assigns the entire party to Boat B. The availabilities now looks like this:

There are still a maximum of 6 seats available for purchase to a customer because Boat C is still fully available.

Let's continue to expand on this example with another purchase. Benjamin Jones purchases for a party of 5. The system identifies that both Boat A and Boat B do not have enough capacity completely (even though combined they do contain 5 seats available) to hold the Jones party without splitting them up so it assigns the entire party to Boat C. The availabilities now looks like this:

To the customer, now that all assets have at least one assigned party to them, will show the maximum still available. In this case, there are 2 seats available on Boat A, 3 seats available on Boat B, and 1 seat available on Boat C. The system will display 3 seats available even though 6 total seats remains because parties cannot be split between assets with this optimization enabled.

Expanding this further, Bart Simpson makes a purchase for a party of 2. The system identifies that Boat A and Boat B both have enough capacity for handle this party of 2 but the system always will assign to the asset with the lowest number of seats available that can handle the full party. In this case that is Boat A, so Boat A is now completely sold out. Here's what those availabilities look like:

To the customer there are 3 seats available even though a total of 4 seats remains. 

To round out this example January Jones makes a purchase for a party of 3. Because Boat B has 3 seats remaining this party is added to Boat B. This is what those availabilities looks like:

This product has now successfully sold Boat A and Boat B completely. A single seat remains on Boat C. A customer would see 1 seat remaining going forward.