Data-driven Marketing Done Right: Strategies to Focus on Prospects of Value, not Volume

Direct mail or print

advertising close rate

The average click-through rate

for paid search (worldwide)

Clicks and the results from

6 to 10 on a Google

search account for only

Average webinar

registrant-to-attendee

rate

Living in a World of Diminishing Returns

2% 42%

1.7%

3.73%

Focusing on the Wrong End of the Funnel

Path or Poof

Path or Poof

Path or Poof

Path or Poof

Path or Poof

Why Now?

• What does data-driven mean in 2015?

• Is it a complete overhaul?

Technological Determinism

Social ConstructionOf Technology

New Technology

Market Need

Market Need

New Technology

The Market Need has Changed

Produce as much

as possible

Production Era

Convince customers

to buy what you

have

Sales Era

Give customers what they

want

Customer

Era

Buyer’s MarketSeller’s Market

Volume

(clicks, visits, registrations)

Velocity

(Conversion Rate)

What is the Missing Piece?

Volume

(clicks, visits, registrations)

Data-Driven = Value Driven

Velocity

(Conversion Rate)

The Missing Piece is VALUE• Asking the right questions is how we get there

The Domains of the Customer Journey

The

Customer

Journey

Digital

Presence

Live

Events

Marketing

Outreach

Sales

Outside of

Influence

Questions for Value-driven Approaches

Value

• Where do you find customers of value?

• What success metrics to use

• How to approach customer experience?

• Where to find ideas?

The 80/2 Rule

• Less than 2% of your customers will bring in more than 80% of the value

Success Metrics

• Long Term Value = Long Term Success

Success Metrics Examples

• Conversion Rate, Attribution

Conversions

Impressions

Success Metrics Examples

• ROI

Value

Cost

Segmentation

Prioritization

PersonalizationApply

Automate

Learn

Customer Experience

Science

ArtPutting In the science

Into the ArtAnd

Mark

etin

g M

atu

rity

Hypothesis Creation

Accurate Predictions

Understanding the Customer Journey

Accountability for Business Goals

High Level Business Goals

Cross Channel Data

Automation

Hypothesis Validation

Customer Journey Database

High Level Conversion Tracking

Segmentation

Marketing Attribution

Predictive Analytics

Insights

Experiments, A/B Testing

Personalization

Problem Technology

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