@WillPate

Will pate VP Digital

Case Study

“Making Sense of Data at Any Size”

m2

Will Pate, VP Digital Strategy, m2

April 8, 2014 @willpate

@m2canada

Making Sense of Data at Any Size

Data Big Data

How Most Companies Use Data

Actionable

insights for informed

decision making

Unstructured

Insights

Visualized

Data

Structured

Data

Unstructured

Data

There is a Hierarchy of Value From Data

Opinions

What Does a Data Driven Culture Look Like?

What Does a Data Driven Culture Look Like?

Not Data Driven

• Executive knows best

• Without art

• Selective about access

• Passion without reason

• Reliant on a small set of people

• Obfuscates purpose so that data is simply

numbers without meaning

• Stuck in decision cycles too slow to act upon

new insights

• Focus on technology over people

X

What Does a Data Driven Culture Look Like?

• Executive led

• Empowers everyone

• Builds everyone’s capacity to make

better decisions

• Passion driven by data

• Makes clear to everyone what we’re

optimizing towards

• Agile, adaptive to learning

• Technology serves the people’s needs

Data Driven

Who is Responsible for Data Science?

Who is Responsible for Data Science?

• Rapid building of organizational

capability for data driven decision

making

• Need time to learn operational

mechanics of business

• Organization is reliant on a small group

and therefore fragile to staff changes

• Spiky distribution of improvement based

on political power of groups requesting

resources

Data Scientists

Who is Responsible for Data Science?

• Capacity for better decision making

across the organization

• Alignment between operational

understanding and insights

• Better aggregate organizational

capacity for data driven

decision making

• Organization is resilient to staff changes

• More even improvement

across organization

Everyone

Create a Hierarchy of KPIs

KPI What question it answers

Lifetime Customer Value by Channel What channels drive the most valuable

customers?

Sales of widget by channel What channels drive the most

customers?

Months to recover Cost of Acquisition

by channel

How long before customers from

a channel become profitable?

Cost per acquisition by channel Where the cheapest customers

come from?

Conversion rate by channel Where the visitors most likely to buy

come from?

Cost of visitor by channel Where the cheapest prospects

come from?

Measure What you Measure

What Does a Data Driven Culture Look Like?

• Usually easy to measure

• Don’t require any specific

understanding of your business

• Are platform-specific

• Don’t matter to your stakeholders

• Don’t help you optimize to the KPI

up the hierarchy

Poor KPIs

What Does a Data Driven Culture Look Like?

• Usually hard to measure

• Require an understanding

of your business

• Are platform agnostic

• Matter to your stakeholders

• Help you optimize to the next

important KPI

Good KPIs

Identify and Fill The Gaps With Infrastructure Investments

KPI Status Requirements

Lifetime Customer Value by Channel 1 year 1 year of sales data in data warehouse

Sales of widget by channel 6 Weeks 90 days of sales data in data warehouse

Months to recover Cost of Acquisition by

channel

3 Months 90 days of sales data in data warehouse

Cost per acquisition by channel 6 Weeks Connect sales system into data warehouse

Conversion rate by channel Done Pulled spend and web analytics into data

warehouse

Cost of visitor by channel Done Pulled spend and web analytics into data

warehouse

Summing It Up

Commit to a repeatable model for actionable insights

Start with culture, and start from the top

Hire data scientists, but make their mandate capability building

Prioritize your KPIs

Measure what you measure

Identify and fill the infrastructure gaps

Happy to continue the conversation on Twitter @willpate

and be sure to tell @m2canada what you think!

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