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hospitality revenue management - Coggle Diagram
hospitality revenue management
L01 introduction
revenue management
maximising profits through
revenue generation
and cost structure
guest satisfaction, demand creation, demand optimisation =
revenue cycle
using data-driven forecasts, optimise pricing and availability of inventory within each market segment
based on the
predictability of duration/inventory
the product can be
priced differently
(price could be fixed/variable)
for application
common characteristics
market can be segmented
high fixed cost
relatively fixed capacity
perishable products
variable demand
optimising demand
right product
inventory control
right price
pricing strategy
right time
data-driven demand
right consumer at the right place
market segments
L02 key performance indicators
performance measurement framework
important for continuous improvement, value creation and to better assess performance
performance benchmarking
standardised by USALI, published by HFTP
fair market share is measured by an index
form of measurement of how a business utilities its capacity/inventory to generate revenue
L03 the competitive landscape
profiling market position
competition
understanding who the different players are in the market
direct/indirect competitors
market (customer segments)
product (business service)
price (business tier)
proximity (location)
SWOT analysis
understanding the organisation's operating environment
positioning
map consumers' views to the pricing of the products and services
rate value matrix
identifying market segments
understanding who the customers are
through trip advisor, google reviews
segmented into characteristics, preferences and behavioural
L04 revenue management process
revenue cycle
highest amount of "profitable" revenue given its fixed capacity and variable demand
control
control sale of inventory using optimised control through various distribution channels
optimisation
optimal set of controls (allocations, prices, markdowns, discounts, overbooking limits)
data collection
collect and store relevant historical data (prices, demands, casual factors)
forecasting
estimate demand model (forecasting demand and other relevant quantities like no-show, cancellation rates based on transactional data)
historical data, predictive data (current business data/market data)
booking pace
pace comparison metrics
occupancy ranks, subscribed hotel occupancy, competitor set occupancy, subscribed hotel vs competitor set, using in estimation of customer buying behaviour
L05 staying ahead of the curve
forecasting
strategic
support strategic objectives
revenue
realistic picture of probable future of occupied rooms and rates to compare to budget and identify variences
operational
for operational necessities such as scheduling
demand
anticipated demand of the products or services
influencing factors
predictive data
business data
booking pace, demand driving marketing initiatives
market data
competitor activities, supply changes, industry information
impact on revenue strategies
demand forecast increases
increase pricing
restrict discounts
force premium products
shift group/bulk purchase to to other dates
demand forecast decreases
decrease pricing
relax restrictions
add sales deployment
increase marketing spend
impact on stakeholders
business owners
sales volume
customers
pricing
operations
staffing levels, cost of materials
revenue managers
revenue strategies
L06 market segmentation
classified within characteristics, behaviours, preferences
products and services must not be homogeneous as not all consumers are the same
benefits
multiple market segments allow revenue managers to offer rates at differing levels
fencing
controlled availability
transactional characteristics
physical attributes
product line
price sensitivity/profitability between transient and groups
factors influencing buying decisions
environmental
interpersonal
personal
organisational
difference in purchase behaviour (consumer/organisational buying decision)