Not All Data Is Created Equal: Data Analysis for Marketers

@KennethLim

NOT

ALL

DATA

IS

CREATED

EQUAL

If Big Data was useful,

we would have called it

Useful Data

Donald Rumsfeld:

“ There are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns -- the ones we don't know we don't know.

” 7

Finding Data

known knowns

known unknowns

unknown unknowns

8

Data Application

Analysis & Testing

Discovery

We analyze data…

not because

we want to report it

not because

we can

and certainly not because

#YOLO

but because we want to

improve the outcomes

We must learn

how our goals are impacted

by understanding the

relationships within the data

Not all data

is created equal

Goal

Performance

Process

Behavior Circumstances

Data Hierarchy

16

Circumstances: variables that can influence Behavior, e.g. Seasonality

Performance: what you need to reach your goal, e.g. € 2M Profit

Process: a key figure that impacts Performance, e.g. Profit Margin per Product

Behavior: individual actions within the Process, e.g. Products Bought and Price Paid

Goal

Data Hierarchy

17

: what you ultimate want to achieve, e.g. 10% Financial Growth

Online Shop Example

Known Knowns Known Unknowns

Goal Profit

Performance Revenue Costs

Process Revenue per Customer Revenue per Order Revenue per Email Campaign

Behavior Website Visits Products Bought Orders Made Amount Paid Discounts Applied Abandons Emails Opened Email Links Clicked

Customer Online Times

Circumstances Holidays Gifts Email Campaigns

Birthdays Anniversaries

18

Circumstances

Understanding Relationships within Data

19

Goal

Performance

Process

Behavior

Profit

Revenue

Emails Opened

Email Links Clicked

Email Campaign

Amount Paid

Revenue per Email Campaign

Discounts Applied

Abandons Customer

Online Times

Email Campaign Process

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1. Email Received

9. Email Order

Revenue (in €)

4. Order

Placed?

5. Abandoned?

7. Discount Applied?

8. Email Order

Discount (in €)

6. Email Order

Abandon (in €)

2. Email Opened

3. Email Link Clicked

Yes Yes

Yes

No No

Measuring Revenue per Email Campaign

21

Total Email Order Revenue

Total Number of Emails Sent

Total Unique Email Opens

Total Number of Emails Sent

Total Email Order Revenue

Total Email Order Revenue + Total Email Order Discounts + Total Email Order Abandons

*

Revenue per Email Campaign =

Adjusted Revenue per Email Campaign =

But wait…

there’s more!

Circumstances

Improving Revenue per Email Campaign

23

Goal

Performance

Process

Behavior

Profit

Revenue

Emails Opened

Email Links Clicked

Email Campaign

Amount Paid

Revenue per Email Campaign

Discounts Applied

Abandons Customer

Online Times

We can obtain data

by asking

We can obtain data

by taking

We can obtain data

by testing

We should obtain

data by asking,

taking & testing

Improving Revenue per Email Campaign

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Total Unique Email Opens

Total Number of Emails Sent

Total Email Order Revenue

Total Email Order Revenue + Total Email Order Discounts + Total Email Order Abandons

*

Adjusted Revenue per Email Campaign =

An Evolving Approach to Data

1. Understand the impact of and the relationships within the data

2. Collect the data that is important

3. Analyze the outcomes

4. Optimize the approach

29

The story is never

about the data itself

Final Thoughts

• Always look to improve the outcome

• Establish a firm understanding of the relationships within your data

• Challenge the unknown

• The story is never about the data itself

31

Kenneth Lim

designxdata.com

[email protected]

@kennethlim