Longitudinality Het begrijpen van online consumentengedrag

Content marketing Experience, 2 oktober 2014

marnix bugel phd

2 2

3

Drs. Wiskunde & Informatica

en Phd Economie (RUG)

Voorheen Customer Analyst

ABN AMRO en partner VODW

Marketing

Managing en founding partner

MIcompany (since 2006)

Serving the board of leading

companies such as Achmea,

KPN, Bol.com and Postcode lottery

(Co) author of scientific articles

including article currently at 12th

position most cited list

Included on list best professionals

(Quote) and best marketers (Dutch

Marketing Magazine, 2nd place)

Short personal- an dcompnay introduction

*A skill that differentiates a company from its competitors

Marnix Bügel

Leading European agency on BIG DATA and

Commercial Analytics

YoY growth since start in 2006:

CAGR of 25%

Unique proposition focused on:

- sustainable growth through analytical

capability* building

- partner relationships with our clients

50 people on pay-roll:

- 85% of them studied Econometrics or

Mathematics

- Exceptional results in high school and

university (average high school score on

mathematics 9.4 (scale of 1 to 10); more

than half of employees graduated cum laude

once or twice)

4

(R)etail

Telecom

Insurance

Travel & Energy

Non-profit

Banking

1 2

Lotteries

3

Micompany serves leading companies across industries

1 2 3 100% online players (corporate) startups international assignments

5

Global media consumption per week Average hours per week

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

Cinema

1940 1920 1900

Print

Analogue radio

Analogue TV

Outdoor

Digital TV

Digital radio

Internet

Wireless

Games

2020 2000 1980 1960

Source: Carat, World association of newspapers 2007-2008.

Two-way media

One-way media

Digital media take over the role of push media

6

0

5

10

15

20

25

30

35

Storage

capacity

Creation

2020 2018 2016 2014 2012 2010 2008 2006

Source: IDC publication – digital universe, are you ready 2010.

• Every two years the amount of

data doubles in the world.

• The Berkeley School of

Management forecasts that more

data will be created in the next

three years than in the previous

40,000 years.

Global data creation and storage capacity Zeta bytes

Data creation explodes in the world

7

type # bytes

1 bit = .125

1 byte = 1

1 kilobyte = 1,024

1 megabyte = 1,048,576

1 gigabyte = 1,073,741,824

1 terabyte = 1,099,511,627,776

1 petabyte = 1,125,899,906,842,624

1 exabyte = 1,152,921,504,606,846,976

1 zettabyte = 1,180,591,620,717,411,303,424

1 yottabyte = 1,208,925,819,614,629,174,706,176

1 xonabyte = 1,237,940,039,285,380,274,899,124,224

1 wekabyte = 1,267,650,600,228,229,401,496,703,205,376

1 vundabyte = 1,298,074,214,633,706,907,132,624,082,305,024

Wallmart collects more than 2,5 petabytes of data every hour from its customer transactions.

From bit to vundabyte

8

Large companies start to wonder what to do about this

8

9 9

10 Fact based marketing

10

11 11

+21%

Nieuwe premie

103,19

Oude premie

85,51

Bron: Bügel, 2010

Premieontwikkeling na prijsverhoging

12 Fact based marketing

12

13 13

Tevredenheid

Kwaliteit van alternatieven

Hoogte van investeringen

Relatiebinding Voortzet-/

beëindigingsgedrag

.845

-.500

.840

.528

Bron: Rusbult, 1983

Het investeringsmodel van rusbult

14 14

35

32

30

Totaal 97

Niet binnen 12 maanden

Niet binnen 3 maar wel binnen 12 maanden

Binnen 3 maanden 33% 33%

31% 64%

36% 100%

100% 100%

Snelheid van terugkeer Aantal vrouwen

Grootte %

Grootte cum %

Bron: Rusbult & Martz, 1995.

Het terugkeergedrag van mishandelde vrouwen

15 15

Determinant investeringsmodel

Grootte Ind %

Grootte Totaal %

Bron: Rusbult & Martz, 1995.

0,19

0,28

0,34

Investeringen

Alternatieven 0,45 0,11

Tevredenheid

Indirect

Direct

Het belang van factor

30%

12%

21%

30%

49%

21%

Het belang van factoren uit investeringsmodel op voortzet- beëindigingsgedrag

16 16

Totaal 1.386

Automotive 276

Mobiele Telcom 272

Supermarkten 277

Zorgverzekeraars 275

Bancair 286

Branche Steekproef grootte (N)

Bron: Bügel, 2010.

0,62

0,60

0,62

0,59

0,64

0,74

Verklarings- kracht (R2)

Investeringen 0,27**

Alternatieven 0,31**

Tevredenheid 0,42**

Determinant investerings- model Gewicht (beta)

** p < .01

investeringsmodel is in verschillende branches toepasbaar

17 17

Het verhogen van de tevredenheid

18 18

Het reduceren van de kwaliteit van alternatieven

19 19

Het verhogen van de investeringen in de relatie

20 20

Het effect van de hisociety

21 21

22 22

Er is meer dan ratio

23 23

Passion Commitment

Intimacy

Source: Sternberg, 1986.

Kamaraad-schappelijke liefde

Romantische liefde

Dwaze liefde

Liefde bestaat uit drie componenten

24 24

Le

vel

of

inti

macy

Duration of relationship

Successful relationship

Failed relationship

Level

of Intimacy

Le

vel

of

pa

ssio

n

Experienced

Level

Positive drive

Negative drive

Opponent processes

Duration of relationship

Source: Sternberg, 1986.

Liefde ontwikkelt zich gedurende de relatielevenscyclus

25 25

Tevredenheid

Kwaliteit van alternatieven

Hoogte van investeringen

Klantbinding (+)

(-)

(+)

Voortzet-/ beëindigingsgedrag

(+)

Klant- Intimiteit

(+)

Klantfase Bron: Bügel, 2010.

Het klantenbindingsmodel volgens bügel

26 26

0,37

0,210,19

0,28

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,40

Several

years

marriage

Living

together

Courtship

0,09

In love

0,13

Get

acquinted

Ø 0,21

Divorce Marital

Grid

0,17

β reg De β voor intimiteit in het regressie model afs functie van de levensfase

2 Nummer van variabele affectie in regressiemodel

4 4 4 3 4 1

Intimiteit cruciaal aan begin en einde klantrelatie

27

de cohort analyse laat zien dat nieuwe gebruikers kwetsbaar zijn

27

148

July 159

June 186

May 247

December 129

November 134

October 136

September 142

August

Starters in May(424k)

Users with sessions

(*1000)

6,3 47

Month Sessions

Per day

Session

Index

10,6

9,3

10,1

10,0

8,1

9,3

9,3

77

90

92

93

96

99

105 58

61

62

66

71

85

119

Starters in June(233k)

Users with sessions

(*1000)

Sessions

Per day

Session

Index*

4,0

7,7

9,1

9,5

7,8

9,3

8,7

30

75

83

88

92

98

98 59

62

64

70

81

117

Starters in July(228k)

Users with sessions

(*1000)

Sessions

Per day

Session

Index*

3,8

8,9

9,5

8,2

9,1

9,0

37

81

88

97

97

103

28 28

29 29

30 30

31

The needs of customers differ between lifecycle phases

31

Custo

mer

phase

Org

anis

ational action

Orientation Selection Confirmation Standardi-

sation Extension Dispersion Seperation Payment

Seduce Offer

Introduce

Serve Extend Keep Save Collect

Customer life time

Dating

Redeem

Becoming customer

Becoming ex customer

32

Value is being built during the customer lifecycle

32

Custo

mer

phase

Org

anis

ational action

Orientation Selection Confirmation Standardi-

sation Extension Dispersion Seperation Payment

Seduce Offer

Introduce

Serve Extend Keep Save Collect

1

2

3

4

5

6

8

9

Customer life time

Customer life time value

Considertion

Acquisition

Welcome

Recurring costs & revenues

Cross- and upsell

Volume

mutation Win

back Debt

collection

Dating

Redeem

Churn

7

Becoming customer

Becoming ex customer

33

Longitudinality is key to capture value from data & analytics

33

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Longitudinality is key to capture value from data & analytics

34

35 35

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