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