U.S. BOWLING ALLEY PRICING STRATEGY
Michael FriedmanMarty GriffithSarah LackritzPierce Reeves
STRT 624- Strategic PricingDecember 15, 2010
Management Summary
Bowling in the U.S.
Venue Classifications
Cost and Pricing Structure
Study of Nationwide Pricing
Conclusions
Bowling is a popular source of recreation throughout U.S.
Source: IBIS world- Bowling Alleys in the US Industry Report
Market Share Analysis AMF – 13.2% Brunswick – 13.1% No other company controls >1%
Recent Trends Revenues have shrunk an
average of 2.2% annually since 2005 Industry profits are correlated with
disposal income Decreased tournament play
Facilities have begun focusing on other segments by increasing the variety of offerings
Recent trend towards consolidation (typical in declining industries)
Venue Type Determines Target Market
As of 2010:There are over 4,200 bowling locations nationwide and it is the 7th most popular “recreational pursuit”
The bowling industry generates $3.4B in revenue, with $374M in profits
Traditional• Focused solely
on bowling• Adult leagues
with league-only play
Lounge• Full bar with
music; generally darker than traditional alleys
• Aimed at young adults
Family Entertainment Center (FEC)• Arcade games,
go-carting, billiards etc.
• Aimed at attracting the whole family
Best method to evaluate pricing structure is to consider average revenue per bowler outing
Key revenue drivers that make up ARPBO: Lane Rentals (Open play, league play, parties) Shoe Rentals Food and Beverage Games
Billiards Pinball Video Games
Pro Shop Vending ATM fees Sublets FEC’s include variety of other sources
Bowling industry is made up of high fixed costs and low variable costs
The bowling service is almost entirely based on fixed costs Facility Lane equipment and maintenance Bowling equipment Utilities
Labor costs can be slightly variable based on historical trends of demand for services
The food and beverage service is made up of both fixed and variable costs
Pricing is segmented by time of day/week and promotional pricing is use to achieve higher utilization rates
Segmentation and price discrimination Day vs. Evening- 3rd degree Weekday vs. Weekend- 3rd degree League vs. Open Play-2nd degree College nights or Senior Rates- 3rd degree
Achieving high utilization rates Daily specials Happy hours
How Can We Predict the Price of a Game?
Regression Analysis
Surveyed 58 bowling alleys nationwide Data from 31 states plus DC
Data collection: Alley Websites Phone Calls Google Maps’ “Search Nearby” feature
Goal: Use data to determine relationship between price of games and
independent variables determined by the team to possibly be significant
Regression analysis relied on data from multiple independent and dependent variables
Cost of an open play game at different times
All-in cost: 2 games, shoes, and a beer
Independent Variables Dependent Variables
Type of Venue
Geographic Location
Metro Area (Y/N)
Number of Lanes
Price of Shoes
Price of Domestic Beer
Area Population
Area Median Income
Distance to Nearest Movie
Theater
Distance to Closest Bowling
Alley
Number of Alleys within 15mi.
There are 4 significant variables affecting weekday open play
Independent Variables:
Type of Venue
Geographic Location- increased price in NE
Metro Area (Y/N)
Number of Lanes
Price of Shoes- Increases Price
Price of Domestic Beer-increases price
Area Population- increases price
Area Median Income
Distance to Nearest Movie Theater
Distance to Closest Bowling Alley
Number of Alleys within 15mi.
Model explains 57% of variability in
price
Independent Variables:
Type of Venue
Lounge type more expensive
Geographic Location
Metro Area (Y/N)
Number of Lanes- decreases price
Price of Shoes- increases price
Price of Domestic Beer- increases price
Area Population- increases price
Area Median Income- increases price
Distance to Nearest Movie Theater
Distance to Closest Bowling Alley
Weekend Open Play: 6 Significant Variables
Additional variables
are significant and
greater predictive power
Model explains 73% of variability
in price
All-in Cost: Fewer Significant Variables
Independent Variables:
Type of Venue
Lounge type $4 more expensive per outing on Weekend nights
Geographic Location
NE $2 more expensive per outing, SE $1.6 & MW $4.8 less expensive
Metro Area (Y/N)
Number of Lanes
Area Population- increases price
Area Median Income- increases price
Distance to Nearest Movie Theater
Distance to Closest Bowling Alley
Number of Alleys within 15mi.
price of a beer and shoes are themselves dependant
variables and were removed
Model explains 55% of variability
in price
So… what does this mean?
The models were significant, but not 100% predictive 25-50% of the price of a game cannot be explained by our model Other factors were not captured by our model High fixed cost industries can lead to more variable, and subjective
pricing structure More of the elements we tried to capture had an effect on
weekend pricing Type of venue matters more; customers willing to pay more for up-
scale entertainment Number of lanes also matters; as lanes are added the price of a game
goes down, because there is less threat of capacity constraints Beer and shoes will be more expensive at alleys where games
are more expensive All scenarios showed positive correlations Possible Future Analysis: Examination of happy hour drink specials
Areas with higher populations pay higher prices
Potential Errors in Research Methodology
Room for subjectivity in the following data inputs: type of alley, metro area
Census data are accurate, but may not reflect appropriate measure of “area population” or “median income”
Sampling errors: biased towards bowling alleys with websites, and towards cities and towns of interest to the researchers
Some alleys only rent entire lanes by time period, and making these lanes comparable relies on key assumptions
Small sample size: additional data points would make the models more robust