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@hyunjeehale
The study of the distribution and
determinants of health-related states
and events in specified populations
John Snow
One of the Fathers of Modern Epidemiology
1854
Broad Street
Cholera Outbreak
London
Where Do Epidemiologists Work?
Digital Campaigns
vs.
Disease
The Epidemiologic Triangle
Environment
Host
Agent
The Digital Triangle
Digital
Presence
Target
Audience
CTAs
Natural Hx of Disease
Primary Prevention Secondary Prevention
Interrelations of Agent, Host,
and Environmental Factors
Rxn of the Host to the Stimulus
Levels of Preventive Measures
Tertiary Prevention
Rehabilitation
Disability
Limitation
Early Dx &
Prompt Tx
Specific
Protection
Health
Promotion
Prepathogenesis Period Period of Pathogenesis
Production of Stimulus
Early
Pathogenesis
Discernible
Early
Lesions
Advanced
Disease
Convalescence
Natural Hx of Digital
Primary Promotion Secondary Promotion
Interrelations of Target Audience,
Digital Content & Environment
Rxn of the Target Audience to the Digital Campaign
Levels of Promotion
Tertiary Promotion
Maintenance
Paid Advertising
Audience
Collection
Content
Marketing, SEO
& Native
Advertising
Receptive, Undecided Path to Conversion & Retention
Building Brand Awareness
Interest &
Consideration
Actively
Seeking
Conversion
Retention &
Referrals
Web of Causation
Web of Digital
Epidemiologic Study Design
Observational
Cross-Sectional
AnalyticDescriptive
Case-Control
Cohort
Digital Study Design
Observational
Analyze all visitors to a
website and determine
exposure to the
campaign and
conversion rates
Analytic
Target
Audience
Separate
visitors into
convertors and
non-convertors
and determine
exposure
Follow visitors who
were exposed to a
campaign vs.
visitors who were
not and determine
rate of conversion
Epidemiologic Study Design
Experimental
Community
Trials
Clinical Trials
Quasi-
Experimental
Digital Study Design
Experimental
Change specific
features of the digital
campaign
Random A/B testing
of landing pages
Focus Groups
Statistical Decision-Making
Question of
Interest
Sample/Population
Study Design
Data
Collection
Description of the Data
Formulate Hypothesis
Inferential Statistics
Interpretation of Results
Additional Studies/Implement Program
Initiatives
Digital Decision-Making
Business
Objective
Target Audience
Marketing Plan
Data
Collection
Description of the Data
Visitors are more likely
to convert when X
Test if your theory is
correct using statistical
models
Reporting to internal
teams and clients
Develop modified digital strategy based on
results
Incidence and Prevalence
incidence
prevalence
New and Existing Customers
new
existing
bathtub
(digital landscape)
prevents
drop-off
existing
retain
lose
1,000
Mortality
Rate
100
Conversion
Rate
1,000 Mortality
Rate
100
Conversion
Rate
Years of Potential Life Lost (YPLL)
Life
Expectancy
Age at
Death
Years of Customer Lifetime Lost
Avg.
Customer
Lifespan
Number of Years a
Customer at time
of Loss
Measure for Assessment of Risk
Absent
TOTAL
b
Exposure
Present
Absent
Disease
Present
a
dc
TOTAL
a+c b+d
a+b
c+d
a+b+c+d
Measure for Assessment of Conversion
Absent
TOTAL
b
Exposure
Present
Absent
Conversion
Present
a
dc
TOTAL
a+c b+d
a+b
c+d
a+b+c+d
What’s Next?
Who Do You Need?
Coming in 2017
Data Detectives & Digital Space
Finding the Signals within the Noise

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Hazmat suits and content zero: How I learned to study digital marketing like a disease