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Snowplow @ de Bijenkorf
05-04-2017
2De Bijenkorf
▪ 145 year old high-end department store
▪ Focus on fashion
▪ Physical stores and a webshop
3
To create the ultimate personalized
omnichannel shopping experience
for our customers
Our goal..
4One user view
Radio
Abri / tv
Display
Social
Sea Seo
Affiliate
Retargeting
Nieuwsbrief
App push Triggers
5
ApplicationsData
User identification
Models /
Selections
DMP
Storage
Email
SiteEmail
Etc.
OMS/ERP
Contents
6
ApplicationsData
User identification
Models /
Selections
DMP
Storage
Email
SiteEmail
Etc.
OMS/ERP
Contents – Snowplow architecture
7
ApplicationsData
User identification
Models /
Selections
DMP
Storage
Email
SiteEmail
Etc.
OMS/ERP
Contents – User identification
8
ApplicationsData
User identification
Models /
Selections
DMP
Storage
Email
SiteEmail
Etc.
OMS/ERP
Contents – Models and applications
9
ApplicationsData
User identification
Models /
Selections
DMP
Storage
Email
SiteEmail
Etc.
OMS/ERP
Snowplow architecture
10Infrastructure
11Infrastructure
12Cloudformation
13Cloudformation
Benefits
• Define stack once, set up in minutes
• Central stack definition
• Easy updates/deployments
• Rollback in case of failure
• Version control your infrastructure
14Try it yourself
github.com/debijenkorf/snowplow-cloudformation
Snowplow streaming in minutes!
15
ApplicationsData
User identification
Models /
Selections
DMP
Storage
Email
SiteEmail
Etc.
OMS/ERP
User identification
16
Recognize the user
17
Connect to store information
research online and buy
offline?
38% of the revenue attributed
to a customer Id
18
Connect to store information
cd87785b18645cbc
81% of the revenue attributed
to a customer Id
19
ApplicationsData
User identification
Models /
Selections
DMP
Storage
Email
SiteEmail
Etc.
OMS/ERP
Contents – Models and applications
20
ApplicationsData
User identification
Models /
Selections
DMP
Storage
Email
SiteEmail
Etc.
OMS/ERP
Emails
Email
21Trigger mails
22Trigger mails
23Triggers in email
Open rate Click to open rate Conversion rate
Newsletter 35.00% 19.00% 2.10%
Trigger 62.00% 40.30% 3.60%
0.00%
25.00%
50.00%
75.00%
Newsletter vs trigger mails
Newsletter
Trigger
24Newsletter
▪ Newsletters are send out
every week
▪ Often focused on specific
brands and/or discounts
Hugo Boss
Not price sensitive
25
Determining segments
User
Acne
Studios Barbour Barts Chantelle
Cheap
Monday Diesel Esprit Essenza
French
Connection
XYZ123 0 1 0 1 0 1 0 0 0
KADS546 0 0 1 0 1 0 0 1 1
ESD112 1 1 0 1 0 0 0 0 0
Segment 1 Segment 2
Barbour Barts
Chantelle Cheap Monday
Diesel Essenza
Acne Studios French Connection
26Users are given a style
Give “points” for each event on a brand
1 point 20 points1 point
Brand Style Points
McGregor Classic Preppy 1
Ladress Business 1
Maison Scotch Denim 20
27First analyses style and discount
Stylematches:
Discount effects:
28
Fashionstyle
Discount
NBA model
Fashionstyle
Discount sensitivity
Browsing behavior
Average mail open rate
Average mail CTR
A
+ = no
B
+ = no
C
+ = yes
29Only model results
▪ 100% means prefectly predicted
▪ 50% means just as good as randomly sending mails
▪ 70% is good and 80% is very good
30
ApplicationsData
User identification
Models /
Selections
DMP
Storage
Email
SiteEmail
Etc.
OMS/ERP
DMP
DMP
31DMP
Classic
Hugo Boss
Not price sensitive
32DMP – trigger
Browsed
ugo Boss shirt without
buying
33Results????
34
ApplicationsData
User identification
Models /
Selections
DMP
Storage
Email
SiteEmail
Etc.
OMS/ERP
Questions?

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de bijenkorf presentation for Snowplow Amsterdam Meetup #3