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

Date post: 13-Apr-2017
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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

RehabilitationDisability 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 AdvertisingAudience Collection

Content Marketing, SEO

& Native Advertising

Receptive, Undecided Path to Conversion & Retention

Building Brand Awareness Interest & Consideration

Actively Seeking

ConversionRetention &

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

AnalyticTarget

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)

preventsdrop-off

existing

retainlose

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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