1. Chapter 6: Slides Selected by Prof. Clapp
Forecasting Ownership Benefits and Value: Market Research

2. Multiple Factors Affect Real Estate Demand
Needs for access (“linkages”)
“location, location, and location”
Non-locational factors
Housing (style, design, size; financing available)
Commercial (tenant mix and character; parking facilities)
Offices (style, design, floor plate size; amenities and services; electrical and communications service)

3. Market Segmentation
Market segmentation: Differences in preferences or needs among market subgroups
Implication of market segmentation: Market research must focus on relevant market segments
Corollary 1: Most real estate data irrelevant in studying any particular property
Corollary 2: Most important data for a particular market segment may not be readily available

4. Challenges Posed by Market Segmentation
Market segmentation is an empirical notion:
Cannot be described without investigating first
Important facts of segmentation may vary with location and property type
Research process must recognize this challenge
No simple, universal procedure

5. Real Estate Market Research as a Cycle
Create
Market Defining
Story
Competition?
Product?
Refine
Research
Collect
Initial
Data
Customer
Sensitivities?
Customer?
No?
Where is
Customer?
End
Research
Sufficient?
Evaluate
Results
Yes?

6. Writing a Market Story
All market research is someone’s particular story (Best to write down the assumptions of the story)
Clues about market segments can come from industry literature (Urban Land Institute)
Initial collection of data should depend on the assumptions about segmentation
Object: Estimate critical market parameters (rental rates, sales projections, etc.)

7. Three Examples of Property Market Research
Elysian Forest – planned unit development
Palm Grove – Prof. Clapp Deleted these Slides
Plane Vista – proposed apartment expansion
Why look only at development projects?
No difference in market analysis questions between existing and proposed properties
Much more market information for existing properties
Therefore, critical parameters should be clearer for existing properties
Development projects demonstrate more of the challenging data issues

8. Elysian Forest: Proposed Planned Unit Development (PUD)
PUD characteristics
Mixed density (single family to townhouses)
Smaller individual lots for single family
Common areas and recreation facilities
Elysian Forest was bold and big (for University City)
First PUD
900 units (several times the size of typical development

9. Elysian Forest: Projected Sales and Market
Projected Sales of Elysian Forest
Year 1 2 3 4 5
All unit types* 88
212
236
260
104
* Condos, townhouses, patio homes, small-lot single family
Estimated Sales in the University City Housing Market
Year 1 2 3 4 5
All sales
1,500
1,550
1,600
1,700
New units
500
600
850
900
1,100

10. Typical Elysian Forest Patio Home Pair

11. “Competitive Norm” from Local Parade of Homes

12. Typical Elysian Forest Patio Home Cluster

13. Market Defining Story for Elysian Forest
What is the product? (upper income, high-density ownership residences)
Who are the customers? (top 30% of household income, but not top 8%; not traditional family with children at home)
Where are the customers? (retirement buyers; “empty nesters”; single parents, other adults (mixed sources))
What do customers care about in Elysian Forest? (good access to work; good recreation and social facilities; distinctive, contemporary design)
What is the competition? (no other comparable projects; Parade of Homes)

14. Core Market Segments for Elysian Forest
All Households in University City
Owner Occupant Households
Rental Households 99 92
Core Market Segments 70
House Price Percentile
“Traditional” Families
Unrelated Individuals
Empty Nesters
Single Parents
Other family
In terms of %

15. Initial Market Analysis
Determine income range that best approximates the target 22%
Determine owner household “market share” within each income interval for traditional families
Using result from step 2, determine percentage of owner households in our core market segments

16. Initial Data Collection
Basic source: U.S. Census Detailed Tables
Table HCT11: Tenure by Household Income in 1999 (income intervals for the 22% of households targeted for Elysian Forest)
PCT38: Family Type by Presence of Own Children Under 18 Years of Age by Family Income in 1999 (portion of each type of household that is income eligible; portion of traditional households with children at home)

17. Core Market Segments for Elysian Forest
Owner Occupant Households: 48,084
10,121 99 92
Core Market Share
6,642 ÷ 48,084
= .1381
or 13.81%
Core Market Segments
3,479
10,121 – 3,479 = 6,642 70
House Price Percentile
“Traditional” Families
Unrelated Individuals
Empty Nesters
Single Parents
Other family

18. Implications of Analysis for Elysian Forest Sales
Year 1 2 3 4 5
Total target sales 88
212
236
260
104
Total market sales
1,500
1,550
1,600
1,700
Total market segment potential
(all sales x 13.81%)
207
214
221
235
Projected sales at capture rate of 20% 41 43 44 47

19. Actual Outcome for Elysian Forest
Built 20 speculative units
Staffed a sophisticated and expensive sales center
Never sold one unit
Project went to foreclosure
Firm went into bankruptcy

20. Case 3: Plane Vista Apartments
Proposed project: Add 400 units to present 500 units.
Existing project:
Four years old
High quality, wide variety of floor plans
Indoor gymnasium with large weight room
Diverse mix of tenants
Location: Immediately north of Orlando airport
Weakness: Perimeter of city; no special amenities

21. Location of Plane Vista in Orlando
Disney World
CBD
Orlando International Airport
Plane Vista Apartments
Univ. of Central Florida

22. Market Defining Story for Plane Vista
What is the product?
Standard design, broad appeal; high-quality apartments
Who are the customers?
Assume a broad spectrum of working rental households; upper third of rental household income distribution
Where are the customers?
Initial assumption: Persons employed throughout east, south and central Orlando
Influenced by commuting distance to work
What do customers like about Plane Vista?
Should be well known from existing project

23. Initial Data Collection
Concerned with commuter access of Plane Vista relative to competing apartment projects
Must see: locations of new, high-quality apartments and where jobs are concentrated
Obtained apartment locations from dominant apartment market research firm in Orlando
No solid information on job locations

24. Constructing Estimates of Job Locations
Available job related data:
Property appraiser’s database on 43,000 business and government properties
Square footage of structures
Location by geographic coordinates
Classified by over 200 land use categories
U.S. Bureau of Labor Statistics website:
County employment by NAICS category
For 20 major categories of land use compute:
Total county
employment per category
Total county building space ÷ =
Ratio of space per worker:NAICS cat
For each property compute:
Space ÷
Ratio of space per worker =
Est. no. of workers at property

25. Where People Work in Orlando
Univ. of Central Florida
CBD
Source:
Allocate CY empl. using parcel sf
Plane Vista Apartments
Orlando International Airport
Disney World

26. Initial Market Analysis
Distribution of new apartments shows a discrepancy between initial story and map:
Most new apartments are very distant from Plane Vista
Suggests that Plane Vista is isolation from larger Orlando market
Jobs map shows a similar clustering:
Jobs concentrated at airport and on the arterial leading north
Jobs scarce to south, west, and east

27. Revised Market Defining Story: “Airport Island”
Assumption: 75% of Plane Vista occupants work on “airport island.”
Future of Plane Vista market depends on “airport island”
“Airport
Island”
CBD

28. Data Collection: Round Two
Total of jobs on airport island is 25,000
Airport is 60% of total
New firms will add 550 jobs to airport island
Conclusion: Total job growth on airport island is about 5.2% per year for next two years; Metro Orlando job growth at 2.5%
Other apartments on airport island
Construction permits for other apartments are zero
Competitive apartments number about 3,500 units with 90% occupancy

29. Final Market Analysis: Key Assumptions
All else equal, apartment rental rates grow at the rate of inflation
Job growth drives apartment demand on airport island
No other new apartments for two years

30. Projections of Critical Parameters for Plane Vista
2004
2005
Years
2006
2007
2008
Total units
500
900
Occupancy rate
90%
91%-93%
90%-93%
91%-95%
92%-95%
Rental rate growth 0%
1%-2%
2%-3%
2%-4%

31. Questions about the Plane Vista Analysis
Which of the key assumptions seems most vulnerable to error?
What could be done to reduce it’s riskiness?
Does the projection of job growth on “Airport Island” seem safe?
Risk analysis. In depth analysis of employment by NAICs sector enables the researcher to produce informative pessimistic and optimistic scenarios on employment growth.

32. Some Final Observations on the Plane Vista Analysis
A market analysis is always a story
No market analysis is purely numbers
Goal: Put together as much objective evidence as possible before making final judgments
Articulate the key assumptions as clearly as possible (Example: Airport growth was crucial to the Plane Vista story)
Next step: How to translate these into an estimate of value

33. A Perspective on Real Estate Value
James Graaskamp: “When you buy real estate, you are buying a set of assumptions about the future”
We have set out our assumptions about Plane Vista

34. Some Points about Real Estate Market Cycles
Real estate markets differ in cyclicality
Office demand follow business cycles, and is very cyclical
Apartments are less so since households must live somewhere
Longer construction lead time means more cyclicality
Poorer market information means more cyclicality

35. High-Tech Tools for Real Estate Market Research
Geographic information systems (GIS)
Made analysis of Plane Vista possible
Widely used in store location research
Psychographics
Market segmentation research seeks to relate product preferences to “attitudes, interests, opinions, and values, and to demographics
Used to date in retail real estate, but may also apply to housing

36. GIS in Store Location Research: Columbia, SC

37. Survey Research Potentially powerful tool if used carefully
Example applications
Coastal Condo design: How many bedrooms do prospective buyers want?
Plane Vista: Where do current residents really work?
Risk: Ending up with meaningless questions or a meaningless sample
Key preventative tools:
Obtain review and advice from experienced survey researchers
Pretest

38. End of Chapter 6