value and optimisation in multichannel retailing quantitative research report august 2010

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Value and Optimisation in Multichannel Retailing Quantitative Research Report

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Page 1: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

Value and Optimisation in Multichannel RetailingQuantitative Research Report

August 2010

Page 2: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

2

Some Background... ACRS strategic realignment away from ‘public’ education to focus on:

1. Customised ‘in-house’ education

2. Customised (proprietary) research

3. Thought leadership research (funded by industry)

a. Single partner research

b. Collaborative industry research The Retail Thought Leadership (RTL) project

o 2009 ‘Retail 2020’: The Future of Retail (Australia, NZ, Asia-Pacific)

CEO Forum with 10 industry leaders from Australia & NZ Multichannel retailing

1. Consumer value perceptions, and

2. Optimisation of the retail channel mix

Page 3: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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RTL 2010 Research Objectives

The questions addressed are:

1. How do consumers value different channels, in terms of their pre-purchase, purchase and after-sales behaviour?

2. How does the configuration of different multichannel offers impact on consumer perceptions of shopping value and satisfaction levels?

3. How can consumers be segmented to reflect their multichannel retail preferences and behaviour?

4. How do generational differences impact value perceptions and satisfaction?

Page 4: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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Does the online channel pay? A comparison of online versus offline information search on physical store spendInternational Journal of Retail & Distribution Management

Page 5: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

Research Overview

Page 6: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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Our Research Partners

Page 7: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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Research Approach

Workshop with CEOs & industry

• Agreement on objectives & outputs

• Agreement on design & sample

Research approach

• Method approach

• Design of questionnaire

Pre-testing & fieldwork

• One-on-one testing

• Pre-test online (n=100)

• Online survey of 1,000 consumers

• Validation test with NZ sample

Reporting & presenting

• Analysis of the data

• Presentation series

• Development of report

• Customised ‘in-house’ series

Page 8: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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Retail Categories

Consumer electronics Holiday travel

Clothing & footwear

Page 9: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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Consumer Behaviour Stages

Pre-purchase research

Purchase After-sales

Page 10: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

What Consumers Want

Page 11: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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Multichannel Expectations

5.6 5.4 5.4 5.3 5.3 5.05.6 5.4 5.4 5.3 5.3 5.0

5.5 5.3 5.3 5.2 5.2 5.05.6

5.2 5.2 5.1 4.9 5.1

1

2

3

4

5

6

7

The ability to return a product/make warranty claims across channels

Consistent customer service across channels

Consistent product pricing and promotional offers across channels

Means to access after-sales service or information

Sufficient information online to make a purchase decision

In-store returns of online purchases

Mea

n ra

ting

Multichannel Features Sample Base: Total Sample = 1,027

Total sample Clothing & footwear Consumer electronics Holiday travel

5.04.7 4.4 4.3 4.3

5.04.7 4.4 4.3 4.3

5.0 4.84.3 4.4 4.4

4.84.4 4.3 4.2 4.0

1

2

3

4

5

6

7

The same products available across different channels

The ability to order online and pick up from a store

Receiving feedback about my purchase experience

The ability to earn and take up loyalty offers in any channel

My purchase history can be used to make tailored offers

Me

an

ra

tin

g

Multichannel Features Sample Base: Total Sample = 1,027

Total sample Clothing & footwear Consumer electronics Holiday travel

Page 12: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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Relative Channel Importance: Pre-Purchase

5.1 5.14.8 4.7 4.6

4.3 4.34.0 4.0

3.83.5 3.4 3.4

3.02.8 2.8 2.7 2.7 2.6

2.3 2.2 2.1

5.3 5.24.7 4.8 4.5 4.5 4.3 4.2 4.1 3.9

3.6 3.4 3.43.1

2.7 2.8 2.7 2.7 2.6 2.3 2.2 2.24.8 4.8 4.9 4.4 4.6 4.1 4.2 3.8 3.9 3.7 3.5 3.4 3.4 3.0 2.9 2.7 2.6 2.8 2.6 2.3 2.2 2.2

4.8 4.95.0

4.7 4.7

4.04.1

3.43.7 3.6

3.3 3.33.1

2.72.9

2.62.4 2.4 2.3 2.2

2.0 2.0

1

2

3

4

5

6

7

Mea

n ra

ting

Pre-Purchase: Channel Importance Sample Base: Total Sample = 1,027

Total sample Clothing & footwear Consumer electronics Holiday travel

Consumers are online

Page 13: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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Relative Channel Importance: Purchase

5.0 4.8 4.54.1

2.7 2.7 2.6 2.2 2.0 1.92.7

5.0 4.8 4.74.1

2.7 2.6 2.62.2 2.0 1.9

2.8

5.2 4.94.2

3.8

2.7 2.6 2.6 2.4 2.1 2.02.7

5.3 5.04.3 4.1

3.02.4 2.3 1.9 1.9 1.9 2.0

1

2

3

4

5

6

7

Mea

n ra

ting

Purchase: Channel Importance Sample Base: Total Sample = 1,027

Total sample Clothing & footwear Consumer electronics Holiday travel

Page 14: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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Relative Channel Importance: After-Sales

4.6 4.5 4.3 4.13.6 3.5 3.3

2.3 2.0 1.9

4.6 4.5 4.3 4.23.6 3.6 3.4

2.3 2.0 1.9

4.7 4.4 4.23.8 3.6

3.1 3.3

2.4 2.2 2.1

4.6 4.5 4.2 4.4

3.4 3.4 3.1

2.0 1.8 1.8

1

2

3

4

5

6

7

Mea

n ra

ting

Post-Purchase: Channel Importance Sample Base: Total Sample = 1,027

Total sample Clothing & footwear Consumer electronics Holiday travel

Page 15: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

Reactions to Different Multichannel Offers

Page 16: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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The MC OfferStore only Traditional

MultichannelEmerging

Multichannel

Page 17: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

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Convenience

Enjoyment

Risk

Sat

Loyalty

Page 18: Value and Optimisation in Multichannel Retailing Quantitative Research Report August 2010

Consumer Segmentation

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Segmentation variables

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Macro-Segments Four macro-segments A few interesting comparisons to note...

Loyals Adopters Traditionals Functional

Spend (avg. $) $78.00 $84.00 $93.00 $78.00

Smartphone 20% 22% 16% 27%

Connectedness1 3.5 3.9 2.6 2.2

1 number of retailer communications (emails) an individual is signed up to

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49% of are pro cross- channel shoppers

Store Loyals34%

Channel Adopters

28%

Traditional Multichannel

Shoppers21%

Functional Shoppers

17%

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Macro-segment 1: Store Loyals Rate Store as most important channel across search, purchase &

after-sales Represent 34% market share Relatively low in terms of ‘innovativeness’ High proportion of Baby Boomers across macro-segment 3 micro-segments…

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Macro-segment 2: Channel Adopters Place relatively equal (high) importance on all channels (and higher

than most on emerging) Represent 28% market share Relatively high in terms of ‘shopping enjoyment’ High proportion of Gen Y & Gen X across macro-segment 3 micro-segments…

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Macro-segment 3: Traditional MC Shoppers Place highest importance on store and traditional channels

(catalogue, Internet) Little importance on ‘emerging’ channels Represent 21% market share High proportion of Gen Y & Gen X across macro-segment 2 micro-segments…

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Macro-segment 4: Functional Shoppers Low importance scores across channels Represent 17% market share Low in terms of ‘innovativeness’ and ‘enjoyment’ Spread across generations and skew toward females 2 micro-segments…