blackberry market research project

Bridging the gap of innovationDion McKenzieRobert Shumbusho 12’

Background information

Research problem & research strategy

Research method and results

Data Analysis

Recommendations & Limitations

• Founded in 1989• First phone launched 1999• 2011 Revenue: $19.9 billion• 2011 Net Income: £3.4

billion

BUSINESS INFORMATION

19.6%

TARGET MARKET

COMPETITORS

46.0% 27.8%

• First iPhone launched 2007• 2011 Revenue: $108 billion• 2011 Net Income: $25.9• billion

• Nexus One launched 2010• Sold 190m • 2011 Net Income:

$2.5billion

Advantages:• Brand awareness, On going

innovation, Prestige

Disadvantages: • Price point and lack of choice

Advantages: • Cheap, multi platform, variety of

smartphones

Disadvantages: • Still behind IOS in terms of apps, Too

many handsets

COMPETITORS

46.0% 27.8%

COMPETITORS CONT.

Background information

Research problem & research strategy

Research method and results

Data Analysis & Findings

Recommendations & Limitations

• Convergence of business users > prosumer users

• Innovation

• Bad publicity

RESEARCH PROBLEM

RESEARCH STRATEGY

OBJECTIVES• Customers existing mobile phone characteristics

• Customer preferences of mobile phone choice

• Which consumers Blackberry should focus their marketing efforts on

PRIMARY RESEARCH• Questionnaire: “How clever is your mobile”

STRATIFIED RANDOM SAMPLING

• Age 18 and over

• Location Highcross Shopping Centre

(Leicester)

Background information

Research problem & research strategy

Research method and results

Data Analysis

Recommendations & Limitations

86%

5%

9%

Collected Survey Data

CompletedDidn't qualify Incomplete

RESEARCH METHOD

DATA COLLECTED: SURVEY STRUCTURE

SAMPLE DEMOGRAPHIC PROFILE

GENDER

Male 51%

Female 49%

AGE

15-20 25%

21-25 26%

26-30 20%

31-35 8%

36-40 6%

41-45 6%

46+ 8%

OCCUPATION

FT Student 40%

Financial services 6%

Sales/Marketing 5%

Engineering 4%

IT 1%

Government/Legal 2%

Medical/ Health Service 3%

Education 8%

Retail 17%

Self-employed 3%

Media Journalism 2%

Performing Arts/Designer 1%

Non-profit/Charity 2%

Retired 2%

Unemployed 3%

EDUCATION

Less than secondary school

4%

GCSE 9%

A-Level 47%

BA/BSc 26%

MBA 6%

PhD 6%

Other 2%

CHILDREN

Yes 40%

No 60%

INCOME PER ANNUM

0-12 38%

13-25 20%

26-38 9%

39-51 3%

52+ 2%

Prefer not to say

27%

MARITAL STATUS

Single 57%

Co-hab 20%

Married 28%

Divorced 5%

Background information

Research problem & research strategy

Research method and results

Data Analysis

Recommendations & Limitations

• Multiple regression Identify factors that significantly

affect smartphone choice

• Cluster analysis Identify meaningful customer

segments (unknown variables)

• Discriminant analysis Profile each segment

demographically

ANALYSIS METHODS

REGRESSION ANALYSIS

Features BETA Tolerance Price .113 .670Voice clarity .059 .519QWERTY .185 .731Apps .218 .345

Features BETA Tolerance SMS -.236 .611

MMS .208 .504Web browsing .247 .132Video .104 .340Music .204 .688

Features BETA Tolerance Social networking .119 .144Video .113 .202

Features BETA Tolerance Magazine- Lifestyle .150 .689In Store Reps .206 .702Television .053 .661

Summary of the important values

Model R Square1 .080

2 .169

3 .240

4 .250

R-Square- tells us how much of the variance in the dependent variable (like hood of purchase BB) is explained by the model (which includes all the features and characteristics)

In our case the total of values are 25%. Which means that the features and characteristics determine 25% of likelihood of purchasing a Blackberry

It is highly unlikely to get 100% prediction from the variables, therefore the other 75% could be influenced by many other things such as demographic and psychographic behaviours etc.

1 2 3 4 5

0

5

10

15

20

25

30

Clusters

Wei

ght (

%)

CLUSTER ANALYSIS

Cluster Summary

Cluster Frequency Proximity(how close each person in that cluster Is to each other)

Nearest cluster

1 25 1.51 4

2 31 1.89 3

3 17 1.88 2

4 43 1.7 1

5 28 2.04 2

CLUSTER ANALYSIS

Series10

5

10

15

20

25

30

Cluster 1 Cluster 2Cluster 4

Clusters

Wei

ght (

%)

CLUSTER ANALYSIS: NARROWING FOCUS

CLUSTER MEAN

1 4.76

4 4.58

5 4.70

CLUSTER MEAN

1 3.57

4 3.75

5 3.60

How likely are you to choose a ‘smartphone the next time you buy a mobile phone (continuous scale 1-5)

How likely are you to make your next phone a Blackberry (continuous scale 1-5) DV

Features Cluster1 2 4

Price* M M H

Voice Clarity H H H

Email H H H

Ease of use H H H

Battery Life H H H

Touch screen* H M M

QWERTY Keyboard* M M M

Internet H H H

GPRS H M H

Style/Attractiveness H H H

Brand Reputation H H H

Camera H H H

Apps H M H

Gaming M L H

CLUSTER ANALYSIS - PREFERENCES

Rate the following features in order of importance in your initial choice of mobile phone

(Continuous scale 1-7)

1-3 (Low), 3-5 (Moderate, 5-7 (High)

Features Cluster

1 2 4

SMS H H H

MMS H L M

Email H H H

Web Browsing H H H

Social Networking H L H

Purchased Apps* M M H

FRRE Apps H M H

Video H M H

Music H M H

#Q16 Please choose how often you currently use the following feature on your CURRENT MOBILE PHONE(Continuous scale 1-7)

1-3 (Low), 3-5 (Moderate, 5-7 (High)

Features Cluster

1 2 4

SMS H H H

MMS* H M M

Email H H H

Web Browsing H H H

Social Networking H H H

Purchased Apps M L H

FRRE Apps H M H

Video H M H

Music H H H

How frequently do you intend to use the following features on your NEXT MOBILE PHONE (Continuous scale 1-7)

1-3 (Low), 3-5 (Moderate, 5-7 (High)

#Q18 Generally, where do you look for information when purchasing technology products? (Binary variable)

Features Cluster

1 2 4

In store Sales Rep H H M

Magazines – High Tech L L L

Magazines – Lifestyle L L M

Internet – retailers website L M H

Internet – review websites L L L

Newspapers M H M

TV L M H

Word of mouth L L L

Trade Fairs L L L

1-3 (Low), 3-5 (Moderate, 5-7 (High)

DISCRIMINANT ANALYSIS

Demo/psychographics Cluster

1 2 4

Age: 1(15-20) 7(46+) 3.16 2.32 1.66

Male? 0.52 0.39 0.6

Education: 1(HS) – 6(PhD) 3.48 3.35 3.3

Married? 0.16 0.19 0.21

Children? 0.24 0.39 0.4

Annual income: 1(0-12k) – 5(52k+) 2.23 3.16 2.89

Price sensitivity 0.24 0.55 0.47

Mac 0.4 0.35 0.15

PC 0.6 0.61 0.58

CLUSTER #1• More likely older (late 20s)• Less likely married, children• More likely a PC owner

CLUSTER #2• More likely female• Higher income• More price sensitive

CLUSTER #4• Male• Youngest – students

Occupation: 0(N) - 1(Y) Cluster

1 2 4

Full-time student 0 0.68 0.77

Financial services 0 0.1 0.02

Sales/Marketing 0 0.1 0.07

Engineering/ Construction

0 0.06 0.05

Information Technology 0.04 0 0.02

Government/Legal 0.08 0 0

Medical/Health Services 0.04 0 0

Education 0.12 0.06 0

Retail 0.36 0 0

Self Employed 0.04 0 0

Media/Journalism 0.08 0 0

Performing Arts/ Designer

0.04 0 0

Non-profit/Charity 0 0 0

Retired 0.08 0 0

Unemployed 0.12 0 0

CLUSTER #1• Most diverse• Somewhat Retail and

Education

CLUSTER #2• Engineering/ Construction

and Education

CLUSTER #4• Mostly Student• Somewhat Sales/Marketing

Background information

Research problem & research strategy

Research method and results

Data Analysis & Findings

Recommendations & Limitations

TARGET MARKET SUMMARY

KEY DEMOGRAPHICS

Age Late 20’s

Gender 50/50, M/F (mixed)

Education A Levels or Bachelors Degree

Annual income £25-£40K

Married/Children No

Occupation Sales/Marketing, IT, Education, Retail,

Computer PC

Current Phone Blackberry or iPhone

Price Sensitivity Balanced

High Importance Low ImportanceMobile phone use/preferences

Voice clarity Purchased Apps

Ease of use Gaming

Battery MMS

Style/Attractive

Camera

Intend to use Email Purchased Apps

Web browsing

Social networking

Music

Marketing Channels In-store sales reps Magazines – High Tech

Newspapers (advertising) Internet – review websites

TARGET MARKET SUMMARY

MARKETING CHANNEL

• With smartphone technology becoming more advance, consumers need more explanation on key features and how to use phone to full capabilities. In store sales reps will play a big part in phone choice

• Newspaper ads also very significant with target market

• Ineffective: Word of mouth, internet – review sites, magazines

PRODUCT

Improved OS (i.e. ease of use and speed) Improve voice clarity Improve web browsing experience Longer battery life

Minor focus: Social networking (integrate better)

Twitter is a trademark of Twitter, Inc.

• Time constraints– Our respondents could have been more representative– Sample size could have been larger

• Questionnaire– Would of liked to gather more information, however with the

survey being 5 pages and 21 questions this could of affected participation

– Specialist terminology (isolated non-smartphone users)

LIMITATIONS