Post on 07-Jan-2017
Jacques Warren, CEO
MDA MASTER CLASS – Madrid 2015-11-19
DIGITAL ANALYTICS FUNDAMENTALSCONCEPTS, METHODLOGIES, KPI
AGENDA- Positioning Digital Analytics (well, all
Analytics)- Some concepts- Practical cases and exercises- Some more concepts- Test- Many more concepts- Making the case for optimization- Then I let you go
DIGITAL DATA AND ANALYTICS
Business Without Analytics
Business With
AnalyticsAnalytics Added Value
THE PURPOSE OF ANALYTICS
Noise Signal Decision
Data Insight Action
THE PURPOSE OF ANALYTICS
Source: Éric Nguyen, Banque Nationale
“The world in our heads is not a precise replica of reality (…)”
Daniel Khaneman
DATA AND REALITY
“The world in [our data] is not a precise replica of reality (…)”
Paraphrased by me
What is Analysis?
DATA ARE FOOTPRINTS…
HISTORICAL DATA AND TRENDS
HUH!?
Outliers are not the enemy
Visit Attributes
Visitor Attributes
Customer Attributes
DIGITAL ANALYTICS PLANES
A TOOL PERSISTENT MODEL
DIGITAL ANALYTICS FUNDAMENTALS
A SIMPLE MODEL
INPUT OUTPUTOFFER
2X 2X1.2X1X ANALYTICS
A SIMPLE MODEL
Digital ContentTRAFFIC
PPC
Search
Banners
Referrals
Persu
asion
Usability
Emails
Testing
Perform
ance
RESULTS
A SIMPLE MODEL – DIGITAL VERSUS WHAT?
REALM OF CRO REALM OF CRM
DIGITAL ANALYTICS
DATABASE ANALYTICS
DIGITAL CONTENT
% New Customers
% of Subscription
Pageviews/SessionUnits/Orders
% Satisfied Clients
% Sales to New Visitors % Downloads
Subscribers RSS
% Email Sales
Conversion Rate
SEM Ratio
AOV/Campaign
AOV
% Web Sales/Total Sales
Sales/Session
LOOKING FOR THE RIGHT METRICS
DEFUSING SOME MYTHS
- TRAFFIC – Not THAT important
- CONVERSION RATE – Beware of blind optimization
- CONTENT IS KING – Nope, processes are
- WHAT ARE YOURS?
A LITTLE BREAK FROM CONCEPTS
Look at products
Shopping Cart Page
Order Form
ORDERS
CASE #1
CASE #2
IMAGE
Bla bla bla bla bla bla bla bla bla bla bla bla bla bla bla bla
I WANT IT
FORM – Sept 1
Age
Destination
Trip Worth
Continue
10%
10% of 10% = 1,2M$
CASE #3
1 m
ai, 2
013
2 m
ai, 2
013
3 m
ai, 2
013
4 m
ai, 2
013
5 m
ai, 2
013
6 m
ai, 2
013
7 m
ai, 2
013
8 m
ai, 2
013
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ai, 2
013
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ai, 2
013
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ai, 2
013
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ai, 2
013
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ai, 2
013
14 m
ai, 2
013
15 m
ai, 2
013
16 m
ai, 2
013
17 m
ai, 2
013
18 m
ai, 2
013
19 m
ai, 2
013
20 m
ai, 2
013
21 m
ai, 2
013
22 m
ai, 2
013
23 m
ai, 2
013
24 m
ai, 2
013
25 m
ai, 2
013
26 m
ai, 2
013
27 m
ai, 2
013
28 m
ai, 2
013
29 m
ai, 2
013
30 m
ai, 2
013
31 m
ai, 2
013
0
500
1,000
1,500
2,000
2,500
3,000
3,500
OPENING HOUR PAGE VISITS AND MUSEUM ENTRNCES
OPENING HOUR PAGE VISITS MUSEUM ENTRANCES
KEY PERFORMANCE INDICATORS
SOME DEFINITIONS
Measures the evaluate the quality of an organization’s performance in its execution of strategic activities for its present and future success.
Applied to Digital, KPIs tell us if the digital strategic vision is executed well.
KPI CHARACTERISTICS- Align with the online strategy, itself aligned with the
business one;
- Motivate action;
- Allow for prediction;- Be standardized;- Be displayed in context (targets, tolerance
threshold, etc.).
MORE THAN METRICS
KPIs are a some kind of language; how we talk about the business.KPIs must be the results of a consensus.
A PROPOSED METHODLOGY
- Reaffirm the digital strategy;- Define and list the expected outputs;- Document and reconfirm consensus;- Validate data quality and availability;
KPI WORKSHOP & PROCESS
- Decide how results will be communicated.
KPI & DRIVERS
KPI & DRIVERS
EXAMPLES OF THAT TYPE OF WORKDOCUMENT
EXAMPLES OF THAT TYPE OF WORKDOCUMENT
EXAMPLES OF THAT TYPE OF WORK
WHERE YOU WORK
AN ANOTHER LITTLE BREAK FROM CONCEPTS
January February March April May June July August September October November December0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
Transactions
0
100
200
300
400
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
2100
2200
2300
Visites
325
10290
84
75 74 706560
4542
158
2,200
1,050
1,2451,250
1,010986
975
1,850
934
875
650725
ÉVOLUTION DES TRANSACTIONSMeasure Names
TransactionsVisites
TEST KWANTYX
TEST KWANTYX
Janu
ary/
15
Febr
uary
/15
Marc
h/15
April
/15
May/
15
June
/15
July/
15
Augu
st/1
5
Sept
embe
r/15
Octo
ber/1
5
Nove
mbe
r/15
Dece
mbe
r/15
0%2%4%6%8%
10%12%14%16%18%20%
TAUX DE CONVERSION
TEST KWANTYXDate
January February March April May June July August September October November December0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
170
180
190
200
210
220
230
240
250
260
Nouveaux Clients
0
100
200
300
400
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
2100
2200
Total Clients
ÉVOLUTION BASE DE CLIENTSMeasure Names
Nouveaux ClientsTotal Clients
TEST KWANTYX
SEGMENTATION
ATTEMPTING A DEFINITION
- Subdividing a dataset to identify smaller populations with meaningful behavior.
- Segmentation is at the heart of the analysis process. It tells us about possible causes of behavior, and where/how to influence them.
- Segmentation is to the analyst what dissection is to the physician
SEGMENTING WHAT?
- Segmenting by behavior types or attributes.
- Segmentation Levels: traffic, visitors/users, customer file
LOOKING THROUGH DIEFFERENT ANGLES
Basic Digital Analytics Segmentation - Sources
WHO IS THERE TO DO WHAT?
The Importance of Use-Case (Gary Angel’s great contribution)
Three principles are the foundations of the two-tiered segmentation approach:
Its about understanding the buyer/visitor, not measuring the activity on the website;
Intention drives visitor behaviour, so we can reconstruct intention from sequences of actions;
Once we have established the visitor’s intention, we can then determine whether they were successful or not in accomplishing their task
WHO IS THERE TO DO WHAT?
We aim to determine WHO the visitor is and WHAT they are trying to do.
With these elements, we build use cases. With use cases, it then makes sense to segment KPIs.
TOWARD THE TWO-TIERED SEGMENTATION
Web Site Usage Segments (KWANTYX’s Client)- Information Seeking Prospects- Advanced Prospects – Ready to Convert- Clients Managing Their Account- Clients Adding Services- Job Seekers- Others
DIGITAL ANALYTICS CONTEXT
Measuring Marketing is measuring people who do marketing.
METRICS ARE POLITICS
I’M RIGHT!!
METRICS ARE POLITICS
TRUTH
CAN YOU HANDLE THE TRUTH?
THE ILLUSION OF TRUTH
ANALYTICS GOVERNANCE
Source: Gary Angel, EY
WELL, TALK ABOUT A PROGRAM!
Source: Gary Angel, EY
WELL, TALK ABOUT A PROGRAM!
Source: Gary Angel, EY
WELL, TALK ABOUT A PROGRAM!
Source: Gary Angel, EY
WELL, TALK ABOUT A PROGRAM!
Source: Gary Angel, EY
WELL, TALK ABOUT A PROGRAM!
Source: Gary Angel, EY
WELL, TALK ABOUT A PROGRAM!
OPTIMIZATION
DOES DIGITAL ANALYTICS WORK?
Isn’t optimization the whole purpose of Digital Analytics?
WHAT IS OPTIMIZATIONhttps://www.youtube.com/watch?v=BzLSTpaZkrI
Go watch that video. Watch it up to the end, and see what 63 years of optimization could do. Show it to your team next time they say you can’t squeeze any more value. Remember: the 1950 people were at the top of their game…
Measure everything you do,
THE OUTTER LIMITS
Measure everything you do, but don’t do only what you measure.
THE OUTTER LIMITS
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