how we made +300% and how others made -50% out of it

1. PREDICTIVE
BY GÜNTHER HASLBECK
OVENGA MEDIA
ECOMMERCE

2. ECOMMERCE
WITH DATA

3. CREATETHEMODEL
✓ WHAT PRODUCTS DID THEY LOOK AT BEFORE THEY MADE A
PURCHASE?
✓ WHAT PAGES DID THEY VIEW BEFORE MAKING THAT
PURCHASE?
✓ DID THEY LOOK AT THE PRODUCTS’ DESCRIPTIONS?
✓ DID THEY READ USERS’ REVIEWS?
✓ HOW MANY REVIEWS DID THEY READ?
✓ DID THEY READ BOTH POSITIVE AND NEGATIVE REVIEWS?
✓ DID THEY PURCHASE SOMETHING ELSE IN ADDITION TO THE
PRODUCT THEY CAME LOOKING FOR?

4. THINKBUSINESS
✓ THOROUGHLY UNDERSTAND THE BUSINESS PROBLEM WE’RE
TRYING TO SOLVE.
✓ OBTAIN AND PREPARE THE DATA WE WANT OUR MODEL TO
WORK WITH.
✓ RUN STATISTICAL ANALYSIS, DATA-MINING, AND MACHINE-
LEARNING ALGORITHMS ON THE DATA.

5. STEPBYSTEP
✓ EXTRACT THE FACTS THAT ARE CURRENTLY HAPPENING.
✓ DISTINGUISH PRESENT FACTS FROM THOSE THAT JUST
HAPPENED.
✓ DERIVE POSSIBLE SCENARIOS THAT COULD HAPPEN.
✓ RANK THE SCENARIOS ACCORDING TO HOW LIKELY THEY
ARE TO HAPPEN.
✓ USE EXISTING DATA FROM YOUR CATALOG, CRM …
✓ USE BUSINESS KNOWLEDGE

6. LETS
START

7. CATEGORIES
IP CLICKS IN > HEILPRAKTIKER >
HOMÖOPATHIE INTO 1 BOOK
IP
HEILPRA
KTIKER

8. CATEGORIES
IP CLICKS IN > HEILPRAKTIKER >
NATURHEILVERFAHREN INTO 2
DIFFERENT BOOKS
IP
HEILPRA
KTIKER
HOMÖO
PATHIE
NATUR
HEIL
1
BOOK
2
BOOKS

9. BASKETTOCRM
IP PLACES BOOK FROM
> HEILPRAKTIKER >
HOMÖOPATHIE INTO BASKET AND
BUYS
USER
HEILPRA
KTIKER
NATUR
HEIL
CRM

10. WE KNOW CUSTOMER
NOW
HOWABOUT OFFLINE
CUSTOMER

11. EANIDENTIFIESUNIQPRODUCT
CUSTOMER REGISTERS AT
WEBPORTAL FOR BONUS
MATERIAL
USER
HEILPRA
KTIKER
EAN
in
Product
catalog

12. ADDUSERTOCRM
DATA IS ENOUGH TO IDENTIFY
INTEREST OF CUSTOMER.. WHY
SHOULD HE BUY STUFF AND
REGISTER WHICH IS NOT FROM
INTEREST?
USER
HEILPRA
KTIKER
CRM

13. ADDMOREDATA
USER
HEILPRA
KTIKER
Sell
Score:
2
Order
Amount:
2
Akupun
ktur
Sell
Score:
1,8
Order
Amount:
2
Most
soled
Books
are
for
Group:
Private
Use
|
Students
|
Professionals
Score:
1
|
2
|
3

14. CUSTOMERSUSEOFPRODUCT ISIMPORTANT

15. SEGMENTBYCUSTOMERS
USER
USER
USER
USER
USER
USER
USER
USER
USER
USER
SIMPLE SQL OR SEGMENT BY
BAYES ALGORITHM OR OTHER
HELPFULL TOOLS

16. MAILBYGROUPS
USER
USER
USER
USER
- SEND MAIL BY GROUPS TO A/B
TEST YOUR MAILINGS
- DONT SEND TO ALL AT ONCE, OR
YOU HAVE ONLY ONE SHOT!
Mail
Vers
A
ClickRate
1
Mail
Vers
B
ClickRate
2
Mail
Vers
B
ClickRate
2

17. WEACHIEVED

18. SALESINCREASED
BY 300 % !
(XMIO€/YEAR)

19. U COULD DO MORE
-
WE STOPED HERE

20. UKNOWITFROMEVERYWHERE

21. 2,5YEARSAFTERTEAM
LEAVE‘S COMPANY
PROOF....

22. SALESDECREASED
BY -50% !
COMPAREDTOLASTYEAR
2011
2013
2012
2014
2015
2010
NEWTEAM TEAMLEFT NEWSHOP

23. WHATHAPPENED
NEWTECLEAD:#
-OTHERCOUNTRY1:NODIRECT
COMPETITOR
NEWDEPARTMENTLEAD
-OTHERCOUNTRY2:NOAMAZON
UNKNOWNMARKET

24. NOKNOWLEDGE
OTHERCOUNTRY1:
- WEBSHOP
- MARKETINGBY
LETTER

25. NOKNOWLEDGE
OTHERCOUNTRY2:
- WEBSITE,ORDERBY
LETTER
- MARKETINGBY
LETTER

26. NEWEUROPEWEBSHOP
„MODERNECOMMERCE
PLATFORM“REPLACES
LOCALATGINSTANCE
WHICHREMOVESALL
„PLUGINS/EXTENSIONS“..

27. BUT
THEYDONOT
UNDERSTAND*THE
FOLLOWING...
* NOT BADWORDS,THEYAREVERY GOOD INWHATTHEYARE
DOING,ITS JUST NOT HELPFULL FOR GERMANY

28. IT‘S NOTTHE (BASIC)
WEBSHOP,
STUPID

29. ITISNOTTHESHELFORTHE
COLOROFTHESHELFINYOUR
STORE...
YOUDONOTNEEDANEWSHELF

30. CUSTOMERKNOWLEDGE,
PRODUCTKNOWLEDGE
AND
HOWTOSPEAKWITHTHE
CUSTOMER
ITSALLABOUTTHE

31. THINK SIMPLE

32. DOYOUREMEBERHER?

33. YOU NEED HELP

34. CHECK OUR
WEBSITE
OVENGA MEDIA#
CAN HELP
WWW.OVENGA-MEDIA.DE