Many of these KPIs need to be translated into hotel vocabulary to make sense and increase hotel CLV use. The hotel definitions of the KPIs necessary to calculate CLV are essential, but hotels need to consider other hotel-specific business rules when implementing CLV. For example, variation in demand, the high degree of fixed costs, displacement calculations, and high Customer Acquisition Costs for each stay are some hotel-specific variables to consider.
Definitions of KPIs
The original definitions of these KPIs come from selling products and services and use a vocabulary that sounds strange to hotels. First, the original meaning and then a workable hotel definition in hotel vocabulary.
Customer
A customer is an individual or business that purchases a hotel's products and services. Most hotels have two types of customers. One is Business to Consumer (B2C) which means that the guest (consumer) pays for products and services. Another is Business to Business (B2B), which means that a business pays for products and services.
Hotels need to make separate CLV calculations for their major types of customers. For example, it would not make sense to mix B2C (individual guests) with MICE, corporate contracts, or travel agents.
Average Order Value (AOV)
Average Order Value (AOV) = Total Sales Revenue/Total Number of Orders
In a hotel adapted version, AOV becomes ASV
Average Stay Value (ASV) = Total Revenue/Total Number of Stays
Purchase Frequency (F)
Purchase Frequency (F) = Total Number of Orders / Total Number of Unique Customers
In the hotel adapted version, F also means the frequency
Stay Frequency (F) = Total Number of Stays/Total Number of Unique Guests
Gross Margin (GM)
GM = Total Sales Revenue – Cost of Goods Sold (COGS) / Total Sales Revenue (express the result as a percentage).
The Gross Margin formula is the same in hotels. The challenge for hotels is to calculate COGS for different revenue sources. For example, COGS for a hotel room is very different from COGS for food and beverage. Hotels need to split the revenue for every stay into various revenue sources and then apply an estimated COGS % to each revenue source. The total of each revenue source COGS sums up to the total COGS.
GM = Total Revenue-COGS/Total Revenue
Example B2C (individual guests)
Room revenue (2 nights @ €250) = €500. COGS = €30/night.
Food & beverage €200. COGS 40 % = €80
1 hour spa treatment for 2 guests $300. COGS (labor + material) = €120
Total revenue €1000
Total COGS €260
GM = (€1000-€260)/€1000 = 74 %
Churn Rate (CR)
Churn Rate = (# of Customers at the end of the Period – # of Customers at the beginning of the Period) / # of Customers at the beginning of the Period.
Hotels can calculate the churn rate using the same formula. However, the customers in a hotel are not the same every typical year, so the churn in hotels in the B2C segment is very high.
Customer Lifetime Period
Customer Lifetime Period = 1/churn rate
The calculation is the same in hotels.
Calculations
Here are a few examples of calculations for different types of guests
Customer Lifetime Value - B2C (individual guests)
Average Stay Value: €1000
Average Stay Frequency: 2 times per year
Gross Margin: 74 %
Churn rate: 90 % ➝ Customer Lifetime Period: 1,11
€1000 (ASV)*2 (F)*0,74 (GM)*1,11 (CLP) = €1 643
Customer Lifetime Value - B2B (Corporate contract)
Average Stay Value: 1,2 nights @ €125 room only = €150
Average Stay Frequency: 1200 room nights, 1000 stays per year
Gross Margin: (€125 - €30)/125 = 76 %
Churn rate: 25 % ➝ Customer Lifetime Period: 4 (customer stays for 4 years)
€150 (ASV)*1000 (F)*0,76 (GM)*4 (CLP) = €456 000
Customer Lifetime Value - B2B (Tour series)
Average Stay Value: 40 guests in 20 rooms for one night @ €60 per room + breakfast and dinner @ €25/guest = €1700
Average Stay Frequency: 1 group per week for 12 weeks during the summer
Gross Margin: (€60-€30+€25-€15)/(€60+€25) = 47 %
Churn rate 50 % ➝ Customer Lifetime Period: 2 (2-year contract)
€1700 (ASV)*12 (F)*0,47 (GM)*2 (CLP) = €19 176
Analysis of CLV
The calculations above show a different CLV depending on the type of customer. Hotels need to analyze each customer type separately since the average CLV from all customers would not make any sense. The CLV analysis would be possible if the hotel has a hotel B2B Sales CRM where CLV can rank each separate customer. In a hotel dependent on B2B customers, these customers tend to have the highest CLV and therefore need more attention to stay as a customer longer.
Other hotel-specific considerations
There are a few other hotel-specific considerations worth mentioning.
Capacity displacement
Revenue management wants to maximize revenue on the available capacity. There is one room left to sell, and two customers want to buy. One is the B2C with an estimated daily room revenue of €250, and the other is the B2B (corporate) with an estimated daily room revenue of €150. The revenue manager would give the room to the B2C guest.
Suppose the commercial leader focuses on maximizing CLV. In that case, the room will go to the B2B (corporate) customer to avoid losing the corporate contract, especially if the hotel is frequently "fully booked."
Hotels probably need to refine the CLV formula and include a displacement variable. However, unless the negotiated rates in the corporate contracts are substantially lower, these customers only compete about the availability during high-demand days, and the customer only promises a few room nights, the CLV will always be higher for a large corporate contract.
Service displacement
The hotel is 80 % booked with high-spender B2C customers. The hotel gets a request for a group of 30 guests in 20 rooms at a low rate of €100 per room + a low-cost two-course dinner at €40 per person. The group will probably consume beverages in the bar later in the evening. Total estimated revenue 20*€100 + 30*€40 = €3 200. Gross margin €1700.
The group is a stag party, and they take over the bar and turn away many of the other B2C guests. 20 guests spend €100 less on beverages, and 5 rooms check out one day early. Total revenue loss of €3 250. Gross margin loss €2 300. Guests in two of the rooms will never return to the hotel.
The example above shows a service displacement when hotels cannot service the guests when they want to purchase products and services during their stay. Lack of service is often devastating for long-term revenue and profits.
Again CLV is contradictory to revenue management. In this case, the group's extra room revenue was $2000 minus the unexpected early checkouts of €1250. The additional room revenue captured by the revenue manager was €750, RevPAR went up, and probably also RGI since this was an ad-hoc group that the hotel captured instead of competition. All the traditional measurements say that the decision was the right one.
Conclusion
Hotels need to calculate CLV for different types of customers and then rank customers within each type to understand which customers are the most valuable.
If a hotel wants to focus on CLV, the hotel needs to give up or adjust all other metrics. Before CLV, what was the proper behavior would then be wrong when the hotel started to focus on CLV.
For hotels that want to get more insights about CLV, read more about theory and practical advice in the following articles.
