The document discusses the importance of longitudinal data analysis in understanding online consumer behavior and enhancing content marketing strategies. It highlights the rapid growth of data creation and storage, illustrating the challenges and opportunities presented by big data in various industries. Additionally, the document emphasizes the significance of customer intimacy and relationship management throughout different phases of the customer lifecycle.

1. Longitudinality Het begrijpen van online consumentengedrag
Content marketing Experience, 2 oktober 2014
marnix bugel phd

2. 2

3. 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 Bü g el
 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. 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. 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
1900 1920 1940
Print
Analogue radio
Analogue TV
Outdoor
Digital TV
Digital radio
Internet
Wireless
Games
1960 1980 2000 2020
Source: Carat, World association of newspapers 2007-2008.
Two-way media
One-way media
Digital media take over the role of push media

6. 6
0
5
10
15
20
25
30
35
Storage
capacity
Creation
2006 2008 2010 2012 2014 2016 2018 2020
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. 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. 8
Large companies start to wonder what to do about this
8

9. 9

10. 10
Fact based marketing
10

11. 1111
+21%
Nieuwe premie
103,19
Oude premie
85,51
Bron: Bügel, 2010
Premieontwikkeling na prijsverhoging

12. 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. 1144
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. 1155
Determinant
investeringsmodel
Grootte
Ind %
Grootte
Totaal %
Bron: Rusbult & Martz, 1995.
0,19
0,28
0,34
Investeringen
Alternatieven 0,11 0,45
Tevredenheid
Indirect
Direct
Het belang van factor
30%
12%
21%
30%
49%
21%
Het belang van factoren uit investeringsmodel op
voortzet- beëindigingsgedrag

16. 1166
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. 1177
Het verhogen van de tevredenheid

18. 1188
Het reduceren van de kwaliteit van alternatieven

19. 19
Het verhogen van de investeringen in de relatie

20. 2200
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
Level of intimacy
Duration of relationship
Successful relationship
Failed relationship
Level
of Intimacy
Level of passion
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. 2266
0,37
0,21
0,19
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
Marital Divorce
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. 31
The needs of customers differ between lifecycle phases
31
Customer phase
Organisational 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. 32
Value is being built during the customer lifecycle
Customer phase
Organisational 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

34. Longitudinality is key to capture value from data & analytics
34

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36. 36
cadeautje