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Developing Forecasting Criteria for Snow School Lesson Volumes
CWSAA Snow Sports Schools Division
May 7, 2013
Left Coast Insights
Tourism Development Consulting
Today
 Project Goals and Research Questions
 Concepts from the Literature
 Project Methods and Lessons Learned
 Results
 Conceptual Model
 Recommendations
 Discussion
Project Goals and Research
Questions
 How many lessons are we going to
sell?
 How many people to we need to
hire/schedule?
 What should we charge?
 What factors could be used to
forecast?
Project Methods
 Sequential Exploratory
 Structured Interviews
 Similar Experience – Similar Responses
 Customer Database Analysis
 Linear Regression & ANOVA
 Data exported from RTPOne:
December 1, 2011 to February 25, 2012
Looking at Adult and Kids daily group lessons & Private lessons
Intrapersonal
• Anticipation of
expense
• Afraid of Injury
• Will get cold and wet
• Hard to learn
• Scared of lifts
• Too stressful
• Self-conscious
• Physical Challenge
Gilbert & Hudson, 2000, p. 919
Literature: Constraints to Participation
Structural (or Interpersonal)
• Clothing & Equipment
expense
• Lack of low cost, all-inclusive
holidays
• Prefer to holiday elsewhere
• Lack of money
• Slopes too crowded
• Lack of snow
• Hassle with equipment
• Too much planning
• Others don’t have the money
• Others too elitist
Gilbert & Hudson, 2000, p. 919
Literature: Constraints to Participation
Gilbert & Hudson (2000, p. 910) based on Jackson, Crawford, & Godbey (1993)
Thaler (1985)
Mental accounting and
consumer choice
McFadden (2001)
Economic Choices
Pine & Gilmore (1999)
Experience economy
Model of leisure constraints
Structured interviews:
Factors that influence demand for lessons
• Price – often a constraint
• Geographic Origin – Destination vs. Local
• Ability level – Beginners more likely than advanced
• Gender – Females more likely than males
• Family – families and kids especially
• Familiarity with the resort – less familiar, more likely
• Previous lesson experience – more likely if taken before.
• Socio-economic status – higher incomes more likely
Which of these factors can be measured?
What data do we have that could be used to explain the relationships?
Factors that influence demand for lessons &
possible data sources
• Price – Holiday vs regular vs DWD pricing
• Geographic Origin – Transaction data contains address (60-70% of the time)
• Ability level – Survey data
• Gender – Survey data – but suspect non-response bias
• Family – Yes – Kids penetration rate is much higher than adults
• Familiarity with the resort – Pass type – edge – ticket – season
• Previous lesson experience – Survey data
• Socio-economic status – survey data – economic indicators do not match daily
data.
Familiarity with the Resort
Pass Type Adult Group Kids Daily Private Grand Total
Edge Card 5.87% 7.34% 4.75% 6.17%
Daily Lift 84.36% 83.31% 94.36% 86.05%
Season Pass 9.77% 9.35% 0.88% 7.78%
Total: 100.00% 100.00% 100.00% 100.00%
R² = 0.3542
0
100
200
300
400
500
600
0 1000 2000 3000 4000 5000 6000 7000
ADULT GROUP LESSONS TO ADULT SEASON PASS VISITS
R² = 0.1067
0
50
100
150
200
250
0 1000 2000 3000 4000 5000 6000 7000
ADULT PRIVATE LESSONS TO ADULT SEASON PASS VISITS
Sum of Private Linear (Sum of Private)
R² = 0.475
0
100
200
300
400
500
600
0 1000 2000 3000 4000 5000 6000 7000
ADULT GROUP LESSONS TO ADULT EDGE CARD VISITS
R² = 0.3369
0
50
100
150
200
250
0 1000 2000 3000 4000 5000 6000 7000
ADULT PRIVATE LESSONS TO ADULT EDGE CARD VISITS
Sum of Private Linear (Sum of Private)
R² = 0.4892
0
100
200
300
400
500
600
0 1000 2000 3000 4000 5000 6000 7000 8000 9000
ADULT GROUP LESSONS TO ADULT LIFT TICKET VISITS
R² = 0.405
-50
0
50
100
150
200
250
0 1000 2000 3000 4000 5000 6000 7000 8000 9000
ADULT PRIVATE LESSONS TO ADULT LIFT TICKET VISITS
Sum of Private Linear (Sum of Private)
Lesson Program Top 3 origins that influence
participation rate
Top 3 origins for participation
Adult Daily Group Lessons Australia
Asia
USA
British Columbia (23.7%)
USA (23.7%)
Australia (17.2%)
Kids Daily Group Lessons British Columbia
USA
Whistler
British Columbia (33.4%)
USA (31.5%)
Whistler (11.4%)
Privates Kids
Asia
Latin America
Whistler
Adults
Whistler
Asia
USA (25.0%)
Whistler (22.8%)
Asia (12.0 %)
Geographic Origin
R² = 0.2536
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
0 10 20 30 40 50 60
ADULT PRIVATE RATE TO LATIN AMERICAN ORIGIN
R² = 0.3954
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
0 20 40 60 80 100 120 140 160
ADULT PRIVATE RATE TO ASIAN ORIGIN
R² = 0.567
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
0 20 40 60 80 100 120 140 160 180 200
ADULT PRIVATE RATE TO WHISTLER ORIGIN
Does Price Impact Demand?
R² = 0.1933
0
0.02
0.04
0.06
0.08
0.1
0.12
120 130 140 150 160 170 180 190 200
Adult
Group
Lessons/
Adult
Lift
Tickets
Adult Group Lesson Price
ADULT GROUP LESSONS TO ADULT LESSON PRICE
Group Rate Linear (Group Rate)
Price Sensitivity
AdultGroup = 149.11 + (0.05)LiftTickets + (-1.04)AGPrice
KidsGroup = -153.39 + (0.26)LiftTickets + (1.05)KGPrice
AdultPrivate= -365.39 + (0.01)LiftTickets + (0.60)PrivatePrice
KidsPrivate = -138.76 + (0.04)LiftTickets + (0.23)PrivatePrice
Comments from
Sales and Marketing
• Product is generally
well respected
• Too many products for
customers to make a
decision – Max4 is
better
• Need to Offer Early
Booking Incentive
Conceptual Model
Intrapersonal
Factors
Interpersonal Factors Structural Factors
Preferences
Interpersonal
and product
compatibility
Lesson
Participation
Online Marketing
Word of Mouth
Product timing
and availability Pricing
Market Segments
Recommendations
Management component Important considerations
Factors to use for forecasting
Pre-booked lift tickets
Price – only adult group lessons
Holidays – for kids lessons
Market segments including guest origin
People Need effective sales and booking agents
Product
Create simplicity in product offerings
Re-brand niche products separately
Price
Adult group lessons are price sensitive
Private lessons not price sensitive
Kids lessons more likely driven by other factors
eg. Holidays
Use effective rate fences
Promotion
Improve preference for snow-school prior to
arrival – online word & of mouth
Use price promotions for certain market
segments
Thank You!
Ryan Staley
ryan@leftcoastinsights.com
604-849-1229
leftcoastinsights.com
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Cwsaa wbss - forecasting lesson volume

  • 1. Developing Forecasting Criteria for Snow School Lesson Volumes CWSAA Snow Sports Schools Division May 7, 2013 Left Coast Insights Tourism Development Consulting
  • 2.
  • 3. Today  Project Goals and Research Questions  Concepts from the Literature  Project Methods and Lessons Learned  Results  Conceptual Model  Recommendations  Discussion
  • 4. Project Goals and Research Questions  How many lessons are we going to sell?  How many people to we need to hire/schedule?  What should we charge?  What factors could be used to forecast?
  • 5. Project Methods  Sequential Exploratory  Structured Interviews  Similar Experience – Similar Responses  Customer Database Analysis  Linear Regression & ANOVA  Data exported from RTPOne: December 1, 2011 to February 25, 2012 Looking at Adult and Kids daily group lessons & Private lessons
  • 6. Intrapersonal • Anticipation of expense • Afraid of Injury • Will get cold and wet • Hard to learn • Scared of lifts • Too stressful • Self-conscious • Physical Challenge Gilbert & Hudson, 2000, p. 919 Literature: Constraints to Participation
  • 7. Structural (or Interpersonal) • Clothing & Equipment expense • Lack of low cost, all-inclusive holidays • Prefer to holiday elsewhere • Lack of money • Slopes too crowded • Lack of snow • Hassle with equipment • Too much planning • Others don’t have the money • Others too elitist Gilbert & Hudson, 2000, p. 919 Literature: Constraints to Participation
  • 8. Gilbert & Hudson (2000, p. 910) based on Jackson, Crawford, & Godbey (1993) Thaler (1985) Mental accounting and consumer choice McFadden (2001) Economic Choices Pine & Gilmore (1999) Experience economy Model of leisure constraints
  • 9. Structured interviews: Factors that influence demand for lessons • Price – often a constraint • Geographic Origin – Destination vs. Local • Ability level – Beginners more likely than advanced • Gender – Females more likely than males • Family – families and kids especially • Familiarity with the resort – less familiar, more likely • Previous lesson experience – more likely if taken before. • Socio-economic status – higher incomes more likely
  • 10. Which of these factors can be measured? What data do we have that could be used to explain the relationships?
  • 11. Factors that influence demand for lessons & possible data sources • Price – Holiday vs regular vs DWD pricing • Geographic Origin – Transaction data contains address (60-70% of the time) • Ability level – Survey data • Gender – Survey data – but suspect non-response bias • Family – Yes – Kids penetration rate is much higher than adults • Familiarity with the resort – Pass type – edge – ticket – season • Previous lesson experience – Survey data • Socio-economic status – survey data – economic indicators do not match daily data.
  • 12. Familiarity with the Resort Pass Type Adult Group Kids Daily Private Grand Total Edge Card 5.87% 7.34% 4.75% 6.17% Daily Lift 84.36% 83.31% 94.36% 86.05% Season Pass 9.77% 9.35% 0.88% 7.78% Total: 100.00% 100.00% 100.00% 100.00%
  • 13. R² = 0.3542 0 100 200 300 400 500 600 0 1000 2000 3000 4000 5000 6000 7000 ADULT GROUP LESSONS TO ADULT SEASON PASS VISITS
  • 14. R² = 0.1067 0 50 100 150 200 250 0 1000 2000 3000 4000 5000 6000 7000 ADULT PRIVATE LESSONS TO ADULT SEASON PASS VISITS Sum of Private Linear (Sum of Private)
  • 15. R² = 0.475 0 100 200 300 400 500 600 0 1000 2000 3000 4000 5000 6000 7000 ADULT GROUP LESSONS TO ADULT EDGE CARD VISITS
  • 16. R² = 0.3369 0 50 100 150 200 250 0 1000 2000 3000 4000 5000 6000 7000 ADULT PRIVATE LESSONS TO ADULT EDGE CARD VISITS Sum of Private Linear (Sum of Private)
  • 17. R² = 0.4892 0 100 200 300 400 500 600 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 ADULT GROUP LESSONS TO ADULT LIFT TICKET VISITS
  • 18. R² = 0.405 -50 0 50 100 150 200 250 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 ADULT PRIVATE LESSONS TO ADULT LIFT TICKET VISITS Sum of Private Linear (Sum of Private)
  • 19. Lesson Program Top 3 origins that influence participation rate Top 3 origins for participation Adult Daily Group Lessons Australia Asia USA British Columbia (23.7%) USA (23.7%) Australia (17.2%) Kids Daily Group Lessons British Columbia USA Whistler British Columbia (33.4%) USA (31.5%) Whistler (11.4%) Privates Kids Asia Latin America Whistler Adults Whistler Asia USA (25.0%) Whistler (22.8%) Asia (12.0 %) Geographic Origin
  • 20. R² = 0.2536 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0 10 20 30 40 50 60 ADULT PRIVATE RATE TO LATIN AMERICAN ORIGIN
  • 21. R² = 0.3954 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0 20 40 60 80 100 120 140 160 ADULT PRIVATE RATE TO ASIAN ORIGIN
  • 22. R² = 0.567 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0 20 40 60 80 100 120 140 160 180 200 ADULT PRIVATE RATE TO WHISTLER ORIGIN
  • 23. Does Price Impact Demand? R² = 0.1933 0 0.02 0.04 0.06 0.08 0.1 0.12 120 130 140 150 160 170 180 190 200 Adult Group Lessons/ Adult Lift Tickets Adult Group Lesson Price ADULT GROUP LESSONS TO ADULT LESSON PRICE Group Rate Linear (Group Rate)
  • 24. Price Sensitivity AdultGroup = 149.11 + (0.05)LiftTickets + (-1.04)AGPrice KidsGroup = -153.39 + (0.26)LiftTickets + (1.05)KGPrice AdultPrivate= -365.39 + (0.01)LiftTickets + (0.60)PrivatePrice KidsPrivate = -138.76 + (0.04)LiftTickets + (0.23)PrivatePrice
  • 25. Comments from Sales and Marketing • Product is generally well respected • Too many products for customers to make a decision – Max4 is better • Need to Offer Early Booking Incentive
  • 26. Conceptual Model Intrapersonal Factors Interpersonal Factors Structural Factors Preferences Interpersonal and product compatibility Lesson Participation Online Marketing Word of Mouth Product timing and availability Pricing Market Segments
  • 27. Recommendations Management component Important considerations Factors to use for forecasting Pre-booked lift tickets Price – only adult group lessons Holidays – for kids lessons Market segments including guest origin People Need effective sales and booking agents Product Create simplicity in product offerings Re-brand niche products separately Price Adult group lessons are price sensitive Private lessons not price sensitive Kids lessons more likely driven by other factors eg. Holidays Use effective rate fences Promotion Improve preference for snow-school prior to arrival – online word & of mouth Use price promotions for certain market segments
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