Date post: | 22-Jan-2018 |
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Data & Analytics |
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Data | Domain | Delivery
Presented to:
Art of Targeting & Personalization
Stephen H. YuAssociate Principle, Analytics and Insights
1Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
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2Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
What we will cover
DATA LANDSCAPE INSIGHTS VIA ANALYTICS WHY MODEL?
ART OF TARGETING "ANALYTICS-READY"
ENVIRONMENT
PROPER PERSONALIZATION
VIA DATA AND ANALYTICS
3Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Where the Data Movement is Going
No guessing game – You MUST know your target
Vast amount of online & offline data collected
But are they being used properly?
Analytics play a huge role in prospecting & CRM
Short paced marketing cycle getting shorter
Marketers must stay relevant to their target to cut through the noise
Huge difference between advanced marketers and those who are falling behind
And it’s all about proper “Personalization”
Winners are the ones who know howto stay relevant with their target bywielding the power of data faster.
4Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
It is NOT about Channels or Technologies
There is no such thing as an “online person”
– It is almost offensive
– Channel-centric view confuses buyers
– New channels and technologies in the future
» What then?
This data business should be about “People”
– No one is one-dimensional
– “Buyer-centric” point of view
» Should NOT be channel-, product-, division- or brand-centric
» But most marketers are
» Buyer-centric data structure leading to proper “Personalization”
Never about the technology, but about the people who are looking
at the new device (or even thin air)
– And they are in control, not marketers!
“The Future ofOnline is Offline”– Stephen H. Yu, 2002
5Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Take the data seriously, not just your
gut feelings
Define the goals first, then control
the flow of data
Don’t blindly trust machine based
solutions
Be logical, as there are no toolsets
that read minds
Set specific goals for small
successes
It is about the Data Users, too
Don’t be a “Data Plumber”, but a
businessman
Don’t be technology oriented, but
solution oriented
Don’t do things just because you
can
For Decision Makers For Data Scientists
6Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Leading with Analytics
“A database is
not just a sum of
all data sources,
and Analytics is
not just an array
of statistical
techniques”
1.Business Goals
2.Answers via Analytics / Modeling
3.Databases Optimized for Analytics
Solution design based on business goals, not around capabilities
7Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
What 1:1 Marketing is about
Marketers must know:
– Whom to contact, and
– What to say, if they decided to contact
someone
» What to offer through what channel and
when
Analytics help marketers with both:
– Targeting, and
– Personalization
Everyone is being
bombarded with
marketing
messages through
multiple channels
8Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Different Types of Analytics
“ANALYTICS” MEANS DIFFERENT THINGS…
BI (Business
Intelligence) Reporting:
Display of success metrics,
dashboard reporting
Descriptive Analytics:
Profiling, segmentation,
clustering
Plus, “Prescriptive Analytics” for All Stages
Predictive Modeling:
Response models, cloning
models, value models,
revenue models, etc
Optimization:Channel optimization,
marketing spending analysis,
econometrics models
9Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Insights through Data Refinement
Insights are derived from data through the refinement process
Data Collection by
Channel
Rapid Data Retrieval
Basic Dashboard
Data Hygiene and
Standardization
Consolidation and
Summarization
Advanced Analytics
including Statistical
Modeling
Comprehensive
Dashboard and BI
Reporting
Ad hoc Reports
Campaign Targeting
and Management
Personalization
DATA PLAYERS MUST EXCEL IN:
Collection Refinement Delivery
10Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Why Model?
Models summarize complex data into simple-to-use “scores", and fill in the gaps by converting “unknowns” to “potentials”
Increase targeting accuracy
Reduce costs by contacting less/smart
Stay relevant with target customers
Achieve consistent results
Reveal hidden patterns in data
Reach marketing automation faster
Expand the target universe
“Supposedly” save time and effort
11Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Why NOT Model?
Universe too small
Predictable data not available
1:1 marketing channels not in
plan
Tight budget
Lack of resources
Really? Remember 1:1 Marketing
is about:
Knowing whom to engage
Knowing what to offer if you
decided to engage someone
Models provide answers for both
12Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
What is a Model?
Target vs. Non-Target, such as
Buyer vs. Non-Buyer
Responder vs. Non-Responder
Loyal vs. Attrition
High Value vs. Low Value
Defining target and non-target is equally critical
“A model is a
mathematical expression
of differences between two
dichotomous groups”
13Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Art of Targeting
Remember T, C, M
1.Target
2.Comparison Universe
3.Methodology
Defining the proper target is most critical even
more than the methodology
Marketers must get involved in Target
Definition
– State the goals and usages clearly
– Don’t be a bad patient demanding specific
prescriptions
“Some targets are not what they seem…”
Start by hanging the target in the right place
14Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Defining the Target (or Targets) (1/4)
How frequent is frequent enough?
How much is high enough value?
How big is the size of the ideal target?
Continuous Target
15Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Defining the Target (or Targets) (2/4)
Multiple distinctive segments in
the target universe
For example,
Infrequent Big Spenders
Frequent Small Spenders
New Customers
Dormant Customers
Geographic targets
Demographic segments
Multiple Targets
16Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Defining the Target (or Targets) (3/4)
Multi-step approach for multi-step
sales/marketing
‒ Sales pipeline (various stages of
lead qualification)
‒ Open-Click-Browse-Convert-Repeat
cycle
Very narrow target in a big universe
Sub-targets within major segments
Target within a Target
17Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Defining the Target (or Targets) (4/4)
Inversely Related Targets
For example,
Frequent shoppers with
low average spending
Responsive prospects
with bad credit
Build multiple models
and find cross-sections
18Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Any Pain Implementing Models?
Modelers are fixing data all the time
Repeatedly rely on a few popular variables
Always need more variables
Takes too long to build models and deploy them
Inconsistencies shown when scored
Disappointing results!
19Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Predictive Modelling is all about “Ranking”
12 3
Relational or unstructured
databases won’t cut it
Must create “Descriptors”
that fit the level that needs to
be ranked
Households
Individuals
Companies
Email Addresses
Products
Ultimately, models must
properly “Rank”
Define the level of
data accordingly
20Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Single View of Customer
Web
CRM
POS
Social
Media
Call
Centre
Mobile App
Mobile App
Call
Centre
CRM
Social
Media
POS
WebEmail
21Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Marketing Database Supporting Analytics
Database Optimized for Analytics
– Analytics supporting efficient Targeting and Personalization
– “Buyer-Centric” Portrait
» Transform Channel-, Product-, Division-, or Brand-Centric data to “Descriptors” of the
Target
The Solution – “Analytical Sandbox”
– Additional table(s) without overhauling existing DB structure
– Ideal environment for:
» Analysts and analytical toolsets
» Model maintenance/scoring
– Finished groundwork for level-playing field
» Data Hygiene/Standardization
» Categorization/Tagging/Binning
» Data Consolidation
» Variable Creation
– End-to-end run – from data collection/refinement to campaign execution/backend
analysis
22Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
“Analytical Sandbox” Conceptual Flow
Analytics is not just about statistical techniquesRealign data to achieve accurate, consistent and speedy results
Hygiene / Edit
Categorization
Consolidation
Summarization
Variable
Creation
Model
Development
Model
Application
Reporting
Knowledge
Sharing
Results Analysis
Attribution
Analytical Sandbox
23Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Customer-Centric Environment
MASTER
CUSTOMER
TABLE
W/ CONSISTENT
ID
TRANSACTION
HISTORY
PRODUCT &
AFFINITIES
OTHER
ACTIVITIES
DIRECT
MARKETING
PROMOTION
HISTORY
PROMOTION
HISTORY
OTHER
MARKETING
PROMOTION
HISTORY
DM
RESP
EM
RESP
Descriptors of Customers by
Product, Time-series, Amount,
Activity, Status, Etc.
Descriptors of Customers by
Promo/Response
(Adequate, Over & Under)
BEHAVIOR CHANNEL
Summarization &
Attribution
Summarization &
Variable Creation
Customer-Centric View
24Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Monetary
Frequency
Recency
Sample Variables after Summarization
Weeks since last online purchase
Years since member sign up
Days since last delinquent date
Months since last response date
Orders by offer type
Orders by product/service type
Payments by pay method
Average days between transactions
Total $ past 24 months
Life-to-date spending
Average dollars by channel
Average dollars by product type
BEFORE AFTER SUMMARIZATION
25Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Addressing your customers by their first
names?
Suggesting more of the same products
that they just purchased through
collaborative filtering?
Collecting explicitly expressed
preferences and reacting to them?
Keeping in touch with your customers
all the time?
Customizing emails and landing pages
based on customer preference?
Knowing when to contact through what
channel?
About Personalization
But, maybe you are
‒ “Personally” annoying your
customers and prospects
‒ Personalizing a fraction of the base
and completely ignoring the others
‒ Personalizing sporadically only
when obvious trigger data become
available
Personalization is the big
buzzword now, but what does it
mean?
They are all better than copying and
pasting the same content to
everyone…
26Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
“Personalization is about the Person”
Look at it from the customer’s point of view…
Transform transaction, event, or product level data to:
‒ Describe people, not product
‒ Create 360-degree Single Customer View
(“Analytical Sandbox”)
Develop “Personas”, then match products to them
‒ Not the other way around
‒ Fill in the gap with modeling
Personalization is about the Person
No one is just an “online” or an “offline” person
“Personalization Engines” are often overrated
(especially product level collaborative filtering is on
auto-drive mode)
Raw SKU level data are utterly inadequate for
personalization
27Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Verified “known” explicit data are
scarce even in this age.
Data are often missing for targets who are:
‒ New to business
‒ Dormant
‒ New to channel
‒ Hiding their tracks
But, most personalization efforts are
done based only on “known” explicit
data!
Need to maximize the value of available
data, even implicit or anonymous data
Even now, real data are hard to come by
DATA COVERAGE
RIC
HN
ES
S O
F D
AT
A
28Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Sample PersonasRaw Data
Demographic / Firmographic
Transaction Data / RFM Data
Products & Services Used
Promotion / Response History
Channel Usage Data
Lifestyle / Survey Responses
Delinquent history
Call / Communication Log
Movement Data
Survey / Social Media / Sentiments
Data to Answers via Modelling
Likely to buy a luxury car
Likely to take a foreign vacation
Likely to be a wine enthusiast
Likely to have a home office
Likely to be a risk averse investor
Likely to respond to free shipping offer
Likely to be a high value customer
Likely to be qualified for credit
Likely to upgrade/leave/come back
Formulate the answers through modeling
29Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
1.Not even considering personalization yet; still spraying the same HTML to everyone
2.Some personalization is considered, but do not know where to start
3. Identified basic toolsets for personalization, but do not have specific data or technology roadmap
4.Created the data roadmap, but did not start thorough data inventory
5. Identified required data sources, but datasets are not cleaned up or consolidated for 360-degree
view of customers
6.Datasets are ready for personalization, but only with “known” explicit data; statistical modeling to
fill in the gaps is not considered yet
7.Tested personalization engines through major marketing channels of choice, employing collected
“known” explicit data
8.Creating model-based “personas” with all available data, filling in the gaps with statistical
techniques
9.Personalizing most messages and offers through every touch point, employing explicit data (“hot”
data) and implicit/inferred data (“personas”)
10.Collecting and utilizing results data to enhance targeting models, personas and personalization
engines continuously, leading to full automation
Data & Analytics Steps towards Proper Personalization
30Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Holistic Approach to Personalization
Data, analytics, content management and delivery working in conjunction
INSTALL
PERSONALIZATION
ENGINE
TEST THE
ENGINE WITH
SIMPLE
SEGMENTS
PERSONALIZE
EVERY
MESSAGE
Deployment of interactive
display capabilities
– Web
Ground work for next steps
Data-driven
personalization - secure
access to deeper data
Employ all available
“known” explicit data
Employ model-based “personas”
Convert “unknown” to
“potentials”
Extend personalization to
customers with little or no history
1 2 3PHASE PHASE PHASE
31Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Multiple Dimensions of a Person
Frequent Traveller
Early Adapter
Family Oriented
Bargain Seeker
Examples of Personas:No one is one-dimensional
32Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
More about messaging than targeting
Pin a target individual into one
segment at a time
Hard to update with reliable
consistency
Group them first, describe them later
‒ End up calling everyone in a
segment the same way
Segments vs. Personas
Built for 1 attribute at a time
Describe an individual with multiple
attributes
Identifies dominant characteristics of
a person via side-by-side comparison
Each persona represents diverse
array of data
Easy to update, 1 persona (i.e., one
model) at a time with consistency
Ready for multi-channel marketing
Clustering/Segmentation/Cohorts Personas
33Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
“Personas” built for specific attributes
Project small “known” attributes to large universes of “unknowns” in form of
model scores
Fill in data gaps leaving no missing value – Scores for every record using all
available data
Enable side-by-side comparison of attributes – Quickly find dominant
characteristics of an individual
Simplify matching process between individuals and best suitable
products/services
Support message “rotation” for an individual customer using multiple personas
Lead to marketing automation – Simple scores are no burden to personalization
engines
Model-based Personas in Action
34Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Examples of Model-based Personas
Frequent Flyer
Foreign Traveler
Luxury Hotel
Gourmet
Wine Enthusiast
Adventure Seeker
Young Family
Budget Conscious
Family Oriented
Romantic
High-end / Luxury
Seasonal
Frequent Small Gifts
Pre-packages
Bargain Seekers
Specialty Items
Corporate Purchase
Home Office
Consumables /
Repeat Purchase
Big Ticket Items
Technology Buyers
Early Adopters
Trend Followers
For Hospitality Industry For Gift Industry For Business Solutions
35Confidential eClerx – An ISO/IEC 27001:2005 Certified Company March 16
Modern 1:1 marketing is about proper targeting and personalization with the buyer-
centric view
Business goals first; it is not about data or technology
Invest in analytics – models can pack large amount data into simple answers to questions
Databases must be optimized for analytics and modeling – maintaining consistency is the
key
Add “Analytical Sandbox” to the existing data environment for end-to-end efficiency
Personalization is about the person, not channel
Expand the horizon: Personalize all the time for everyone through every touch point
Move from simple segments to personas for constant and effective personalization
Key Takeaways