Causation vs. Correlation

0:00

In marketing, we love to talk about being data-driven, or at least in recent

0:04

times, data

0:05

and farmed.

0:07

But one way or the other, we love to see ourselves as marketers who use data to

0:10

make

0:11

better decisions.

0:13

One thing that's very important to go along with that though, is how much it

0:16

means to

0:17

be data-literate.

0:18

And that can sound like a slightly insulting phrase, but the truth is that data

0:22

can be

0:23

very easy to misinterpret if you don't know where its limitations are.

0:28

And a really big example of that is the difference between correlation and

0:33

causation.

0:34

And if you look at marketing data, this is a much bigger problem than we often

0:38

think.

0:39

Now the simplest example of correlation mixed up with causation is if you were

0:43

to plot a

0:43

graph of all of the people who use ice cream and all of the people who wear

0:47

shorts, you

0:48

would find that there's a very strong correlation between the two.

0:52

Now does that mean that people who wear shorts are more likely to eat ice cream

0:56

No.

0:57

I mean the people who eat ice cream are more likely to wear shorts also though.

1:02

What it means is that the people who are eating ice cream and wearing shorts

1:05

usually

1:05

do so because it's hot out.

1:07

So there is a correlation between the two.

1:10

And this comes up in marketing programs quite a lot.

1:14

A very obvious example that you see commonly is in paid search programs.

1:19

Where if you look at unbranded keywords versus branded keywords, you will find

1:23

that the branded

1:24

keywords get much higher click through rates, much lower cost per leads and a

1:27

much higher

1:28

overall ROI.

1:31

But of course they do because it's simply correlated data.

1:34

The people who click on branded keywords were looking for you.

1:37

The people who clicked on the unbranded keywords were looking for something

1:40

that you might do

1:41

but not necessarily you.

1:43

So of course they were going to perform better.

1:45

It's a co-hearted group that has more likelihood to convert.

1:49

It's not because the branded keywords was the better campaign.

1:52

But it could very easily lead you to say let's put more money into branded and

1:57

less into

1:58

unbranded.

1:59

And what you might miss in all of this is are those people who click on branded

2:04

keywords

2:05

unlikely to buy from you if you didn't put that ad in front of them.

2:09

A lot of the data would say that they were going to buy anyway.

2:12

You simply paid them to come in when they were going to do so anyway.

2:18

Another example of this that doesn't get talked about as often is retargeting.

2:22

When you look at a retargeting list versus a cold audience list, again same

2:26

things, much

2:27

higher clicker rates, much lower cost per lead, much higher ROI.

2:32

And so it leads people to sometimes abandon the cold audiences entirely and

2:36

only focus

2:37

on the retargeting list.

2:39

But again this is correlation.

2:40

The people in a retargeting list happen to be people who are already familiar

2:45

with you

2:46

versus the cold audience list who are not.

2:49

So if you abandon the cold audience list, you may not be bringing in any new

2:53

people who

2:54

are not yet familiar with you.

2:56

You are simply focusing on the audience who is.

2:58

And in the long term, you can end up generating fewer deals by focusing on the

3:03

conversion rate

3:04

of that group.

3:05

Or another version is people try and take that cold audience and as quickly as

3:09

possible,

3:10

put them into a retargeting list assuming that that same conversion rate will

3:15

hold,

3:15

but it generally doesn't.

3:17

And this is the difference between correlation and causation.

3:20

And what really matters is if you accidentally look at correlation and assume

3:24

that it is

3:25

caused, it can lead you to think that you are generating better and better

3:30

outcomes.

3:31

But at the end of the day, if you're betting on things like branded keywords

3:35

only and retargeting

3:36

lists only, then you're not actually bringing new unfamiliar future buyers in

3:41

and down the

3:42

line, you could end up with less revenue even though you went with the highest

3:46

ROI options

3:47

available.

3:48

That's the difference between correlation and causation.

3:52

And that's the importance of data literacy.

3:54

[MUSIC]

4:04

(dramatic music)

4:07

(buzzing)