Tutorial 2 - Harvard Graduate Housing Survey

Market Research

© Imperial College Business School

Tutorial 2: Harvard Survey

1

Strategic Marketing – SUMMER SCHOOL 2014 2

• Lecture Revision• Case Discussion


Overview for today

© Imperial College Business School Strategic Marketing – SUMMER SCHOOL 2014 3

Three key strategic marketing concepts

What did you learn?

Knowledge Persuasion Decision Implementation Confirmation

Adoption

Rejection Rejection

Adoption

(Rogers, 1962)

Problem Recognition

InformationSearch

InformationEvaluation

DecisionPost-purchase

Evaluation


Consumer buying-decision-making process

What did you learn?


Collecting secondary data

Lecture Revision


Three key strategic marketing concepts

What did you learn?


Identifying consumer needs and desires

Market Research

• It’s all about asking people!

• Surveys are great

for validation

purposes


The dangers of asking leading questions…

Survey Design

https://www.youtube.com/watch?v=G0ZZJXw4MTA

An example from government polls on re-introducing national service for young people, aged 18-25




The dangers of selection/response bias…

Survey Execution

London ‘chuggers’ and the Westfield shopping centre…


Sample sizes and margin of error

Survey Design


Beware – what people say is not what they do!

Survey Design


How do we determine the sample size?

Survey Design

Useful formula for calculating required sample size:

Z = Z value (e.g. 1.96 for 95% confidence level) p = percentage picking a choice, expressed as decimal (.5 used for sample size needed)c = confidence interval, expressed as decimal (e.g., .04 = ±4


What is statistical significance?

Survey Analysis

Significance levels show you how likely a result is due to chance. The most common level, used to mean something is good enough to be believed, is .95. This means that the finding has a 95% chance of being true.

A value of .01 means there is a 99% chance of it being true (1-0.1=.99)


• Context: ‘Allston Initiative’ (2005) survey to generate useful information for the expansion of Harvard owned properties in Allston, launched by the Harvard Planning and Real Estate (HPRE) organisation

• Problem: Presence of competing campuses offering more available housing solutions means that HPRE’s graduate housing issue is becoming a recruiting disadvantage for Harvard University, so what do they do?

• Solution: They design a survey to develop their understanding of graduate students needs and desires (when it comes to housing)…

The Graduate Housing Survey

Harvard Case Study


1. Determine the purpose and objectives of the survey

2. Determine the survey population

3. Drafting the questions Themes: Headings for each section of the survey based on objectives

o Current housing situationo First year expectationso Importance of housing features (transport, building condition, security,

furnished)o Demographics and participant informationo Individual preferences (sensitive questions i.e. money)

Format: scales included in questions i.e. ranked or rated? Medium: online/phone/face-to-face?

4. Maximising response rate

Survey Design Process

Harvard Case Study


Go through the survey questionnaire as a respondent…

• What are your feelings, thoughts and emotions as you go along? What makes you want to give up or continue with the survey? What is easy or difficult to answer? What are the merits and shortcomings of this survey?

Let’s explore the following questions

Case Study

Strategic Marketing – SUMMER SCHOOL 2014 17© Imperial College Business School

Case Study

BREAK INTO GROUPS OF THREE

(10 MINUTES)


• Apart from a survey, what other types of research would you recommend to understand the customer in a way which would inform long term planning in Allston?


Case Study


• In your group, write a survey which could be used to check what features and pricing levels customers would most value in a new mobile phone handset. Include scaling, rating, open and closed questions as appropriate.


Group Exercise


Case Study

BREAK INTO GROUPS OF THREE

(20 MINUTES)


Identifying perceived user value


Conjoint Analysis

1. Use in-depth interviews and focus groups to identify value criteria (the reasons why customers buy) for target segment

2. Identify rank position and weightings using focus groups

3. Verify weightings using large sample surveys

4. Undertake market research to identify consumer ratings of value-adding criteria…

5. Calculate PUV for competitor offer


Remember…

Different segments (user groups) define and weigh value differently!


Identify the dimensions of user value...


Identify the dimensions of user value


Stages 1 and 2

Brand image25%

Residual value15%

Economy10%

External design10%

Comfort8%

Performance8%

Safety7%

Cabin ambience7%

Reliability5%

Handling5%

(Estate cars – mid-income private users)


Calculate User Value Criteria, Weightings and Ratings


Stages 3 and 4

Estate Cars: Private User Segment

Criterion Rank Weighting Renault Laguna

Skoda Octavia

VW Passat

Ford Mondeo

Peugeot 406

Audi A4

Brand image 1 25 2 1 4 2 3 5

Residual value 2 15 1 4 5 2 1 5

Economy 3 10 4 4 4 4 3 4

External design 4 10 4 4 4 4 4 5

Comfort 5 8 5 3 4 4 5 3

Performance 6 8 4 4 4 4 3 4

Safety 7 7 5 3 4 5 3 4

Cabin ambience 8 7 4 1 3 4 4 5

Reliability 9 5 1 4 3 4 2 3

Handling 10 5 2 4 2 5 4 4

Total 100

User weighting of criterion importance expressed as

percentage

Mean user ratings from 1 (worst) to 5 (best) based on consumer research


Calculate Perceived User Value


Stage 5

Estate Cars: Private User SegmentCriterion Weighting Renault

LagunaSkoda

OctaviaVW

PassatFord

MondeoPeugeot

406Audi A4

Brand image 0.25 0.5 0.25 1 0.5 0.75 1.25

Residual value 0.15 0.15 0.6 0.75 0.3 0.15 0.75

Economy 0.1 0.4 0.4 0.4 0.4 0.3 0.4

External design 0.1 0.4 0.4 0.4 0.4 0.4 0.5

Comfort 0.08 0.4 0.24 0.32 0.32 0.4 0.24

Performance 0.08 0.32 0.32 0.32 0.32 0.24 0.32

Safety 0.07 0.35 0.21 0.28 0.35 0.21 0.28

Cabin ambience 0.07 0.28 0.07 0.21 0.28 0.28 0.35

Reliability 0.05 0.05 0.2 0.15 0.2 0.1 0.15

Handling 0.05 0.1 0.2 0.1 0.25 0.2 0.2

PUV Score 2.95 2.89 3.93 3.32 3.03 4.44

For example, this figure is calculated by multiplying the user rating from the previous slide (4) by the user weighting (0.08 or 8%)

PUV/Price - Estate Cars (Private User Segment)

Renault Laguna

VW Passat

Peugeot 406

Audi A4

1

1.5

2

2.5

3

3.5

4

4.5

5

1 1.5 2 2.5 3 3.5 4 4.5 5

Price

PU

V

Skoda Octavia

Ford Mondeo

0

5

10

15

20

25

30

35

Stability Speed Sophistication Support Upgrade

Value adding criteria

We

igh

tin

g (

%)

Customers Executives

Value adding criteria: Mobile internet portals

‘Customer versus Executive perceptions’

Danger of ‘over-delivery’

Benchmarking against competitors



Stability Speed sophistication support Upgrade

-3

2025 101530

0

+2

+1

-1

-2

+3

yourfirm

Better than

Worse than

Competitor a

Competitor b

Mobile internet portals

Weighting Competitor a Competitor b

PUV criteria Rating Rating x weight

Rating Rating x weight

Stability 30 3 90 1 30

Speed 25 1 25 2 50

Sophistication 20 -2 -40 0 0

Support 15 0 0 -3 -45

Upgrade 10 -2 -20 -1 -10

Total 100 55 25

Price $1.5m $1.2m

PUV-Competitor matrixMobile internet

Client price Low High

Low

High

0 Client

+60

-60

A

BPerceived user value

Price

Strategy vector

Competitive dynamicsShifting preferences in mobile internet

Tutorial 2 - Harvard Graduate Housing Survey

Education

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