Presentación en inglés de Aurélie Pols en el Web Analytics Congress celebrado en Utrecht el 13-14 de marzo de 2013.

1. Analytics cultures in Europe
March 2013 – Web Analytics Congres – Aurélie Pols

2. Who am I?
@aureliepols

8. Women’s
day
Because women always analyze everything,
we know how to optimize (our time & work!)

9. ¿Mind Your Group?
Empresas de nicho volcadas en ayudar
a sacar el máximo partido
al canal
online

10. Sponsored
by

11. Data-informed vs. data-driven

12. STAGES
OF
ANALYTICAL
COMPETITION
Use
Internal
+
StaGsGcal
Analysis
&
External
Data
Analy4c
PredicGve
Modeling
Compe4tors
High
Quality
Data
/
Company
Wide
Culture
Analy4c
Companies
Not
CompeGng
Have
BI
Tools
Isolated
No
Easy
Access
Analy4c
Aspira4ons
FuncGons
Mostly
ReporGng
Business
Localized
Analy4cs
as
Usual
Poor
Quality
/
Missing
Data
Analy4cally
Impaired
Lack
Skill

13. Modelo de madurez en Analítica Digital
Basado
en
el
modelo
de
madurez
de
analí/ca
web
de
Stéphane
Hamel

14. Un plan estratégico
Diseño
de
Scorecards
Analí4ca
Prescrip4va
12
Elaboración
Plan
Estratégico
meses
Integración
datos
offline
Iden4ficación
de
Oportunidades
Analí4ca
Predic4va
9
Análisis
Ciclo
de
Vida
del
Cliente
meses
6
Desarrollo
Dashboards
Automa4zados
Personalización
Contenido
Generación
Modelos
Estadís4cos
Perfiles
y
Modelos
de
Personas
meses
3
E4quetado
de
Campañas
Creación
Embudos
Conversión
infraestructura
Análisis
UX
Análisis
Arquitectura
Información
Preparación
Test
A/B
Estudio
de
la
competencia
Análisis
Cualita4vo
meses
Implementación
Básica
Herramienta
Personalización
Herramienta
Ges4ón
de
Calidad
de
los
Datos
tác4ca
Análisis
del
Tráfico
Análisis
Conversión
1
Establecimiento
de
Obje4vos
Generación
KPIs
Definición
Segmentos
de
Negocio
mes
estrategia

15. The key to success, not new
Technology
People
Process

16. 7 steps for beautiful DDDM
# 7
Go
for
the
boOom-­‐line
(outcomes)
# 6
ReporGng
is
not
analysis
# 5
Depersonalize
decision
making
# 4
ProacGve,
not
reacGve
insights
# 3
Empower
your
analysts
# 2
Solve
for
the
Trinity
# 1
Got
Process?
Avinash Kaushik

17. # 7 Bottom-line
Product
innovaGon
PRICE
STRATEGIES
Product
Quality
DifferenGated
MarkeGng
MARGIN
Process
InnovaGon
COST
STRATEGIES
FuncGonal
Efficiencies
DiscreGonary
spending
NET
INCOME
IntegraGon
MARKET
SHARE
STRTEGIES
MarkeGng
SegmentaGon
Customer
Value
Chain
RelaGve
Spending/Effort
VOLUME
MARKET
SIZE
STRATEGIES
“Related”
New
Products
“Related”
New
Markets
More
usage
occasions

18. # 6 Analysis, not Reporting
Comparing Roles
Analytics Analytics
Consultant Practitioner
June Dershewitz
1.
A
pracGGoner
has
an
open-­‐ended
statement
of
work
2.
What’s
the
hold-­‐up?
3.
MeeGngs
upon
meeGngs
upon
meeGngs
4.
Longer
projects,
lasGng
impact
5.
Fear
of
losing
touch
6.
From
center
of
the
universe
to
subject
maOer
7.
The
role
of
the
consultant
is
to
make
the
client
look
good

19. Outsource the boring stuff!
20%
How
does
your
day
look
like?
Source:
The
Next-­‐Genera4on
Privacy
Professional
-­‐
IAPP

20. WEB
ANALYTICS
2.0
Tráfico
y
1.
Qué
Conversión
Datos
Offline
2.
Cuánto
TesGng
3.
Por
Qué
Voz
Cliente
CompeGdores
4.
Qué
más
Insights

21. PEOPLE
RATIONAL
BEHAVIOR
&
YOU

23. Statement
#1:
Companies
&
sectors
are
not
equal

24. 2005: Google Analytics = free
“Staffing for a free
product is an issue
in Germany”
Oliver Schiffers
Matt Cutler Jason Burby

25. Google Analytics market share
Source:
http://www.targetonlinemarketing.com/
en/blog/203-infographic-ireland-who-is-
using-google-analytics.html

26. Europe’s economic fiber: SMEs

27. Europe’s economic fiber: SMEs
http://blogs.ec.europa.eu/neelie-
kroes/coalition-digital-jobs/

28. In 2007…
and still today
Action vs. findings
“What is the most difficult aspect of analytics for your company?”
Pulling together the data 24%
Forming the hypothesis 9%
Developing the analytical models 12%
Interpreting the results 3%
Acting on the findings 53%
Source: Forrester Research

29. Cruise ship vs. speed boat

31. Statement
#2:
Job
descrip4ons
are
not
always
what
they
seem

32. Analytics rockstar
What are you
willing to sacrifice?
to outsource?

33. Long term vision
Dylan Lewis
Wonder about data, analytics & Hadoop? Read
this:
http://hortonworks.com/blog/future-of-hadoop/
Bob Page

34. Life stages

35. Journey companion

36. Consultancy or company?
http://scottberkun.com/2013/pick-your-own-boss/
Outsourcing or
near sourcing?

37. The Spanish Connection
Be demanding: evolve or change!

38. Statement
#3:
There
is
no
truth,
only
points
of
views

39. Is attribution dead?
Distribución
de fuentes
De tráfico

40. From web analytics to digital
Source:
hOp://www.slideshare.net/marketo/how-­‐to-­‐build-­‐a-­‐beOer-­‐inbound-­‐markeGng-­‐machine

41. How can you…
Reach
more
people,
more
efficiently,
at
lower
costs?

42. Specializations
#CRO
#UX, #LEANUX
#SEM, #SEO
#MEASURE
#ANALITICAWEB
#MOBILE
#RWD
…
#AUDIT
#PRIVACY
http://www.weboptimeez.com/wp-content/
uploads/2013/01/weboptimeez-analytics-
roadmap-2013.jpg

43. Los datos son el nuevo oro negro
Page

43

48. Our Blood Type is Data +

49. What did we learn today?
# Best
prac4ces
exist
about
data
driven/informed
cultures
# Despite
differences,
pockets
of
excellence
also
exist
# Create
win-­‐win
situaGon
for
you
and
your
company
# If
not,
move
on:
in
the
Netherlands,
in
Europe
or
in
the
world

50. Don’t Crash & Burn!
Informed
Uninformed 2
Pessimism
Optimism 1
5
Informed
Optimism
Crisis of
3
Meaning
4 Crash & Burn
Transition Curve

51. Ask yourself this
Where
do
YOU
want
to
be
In which
country/region?
in
10
years?
Loner or part
of a team?
Life balance: Doing what? Expert or
Professional Responsible generalist?
vs. Private for what?

52. El futuro pertenecerá a los que
realmente hagan buenas preguntas
Gracias
Aurélie Pols
@aureliepols
aurelie@MindYourGroup.com