W1 T1

Question 1

Google Analytics is used

Answer 1

d to review/analyse click-stream online (behavioral) data on WEBSITE TRAFFIC.

Question 2

resuls of google analytics are

Answer 2

aggregated (total) numbers based on a subset (sample) of visitors

Question 3

Google Analytics (Basic Version)

Answer 3

Aggregate Data total number of visitor and clicks

Question 4

Google Big Query (360 Suite / Corporate Version):

Answer 4

: individual level data, so you can see each visitors’ individual journey and visiting behavior

Question 5

On Google Analytics main-dashboard you can track

Answer 5

You can track the general traffic to your website from different devices, locations, occasions and time-slots.

Question 6

GA Easy to use / Self Explanatory: Because

Answer 6

GA is designed-developed for everyday use for managers at small to medium sized companies.

Question 7

Using Google Analytics you can check customer journeys: 2

Answer 7

: attribution & paths-to-purchase for your website.

Question 8

Which Analysis/Regression Type to Use ? what do we need to know=

Answer 8

We have to know the SCALE type of our Y variable.

Question 9

nominal

Answer 9

eye color

Question 10

ordinal:

Answer 10

level of angry: natural order

Question 11

interval

Answer 11

temperature: natural order, equal interval

Question 12

ratio

Answer 12

height: natural orde, equal interval, true zero value

Question 13

To choose the correct regression type we look at 2

Answer 13

OUTCOME (Y) variable and its scale type.

Question 14

(Y) IS METRIC/CONTINUOUS VARIABLE

Answer 14

MULTIPLE LINEAR REGRESSION

Question 15

(Y) IS DISCRETE/NOMINAL VARIABLE

Answer 15

MODEL-ANALYSIS: LOGISTIC REGRESSION

Question 16

When use multiple linear regression?
OV (what is the outcome?):
PV (what are the potential drivers/predictors?):

Answer 16

OV (what is the outcome?): Quantitative/Metric Scale
PV (what are the potential drivers/predictors?): One or more PVs, quantitative or categorical scale

Question 17

Why use linear regression? 3

Answer 17

> So multiple predictor variables can be tested simultaneously
-> Identify the relative importance (effect) of each predictor variable (X) on outcome (Y)
-> Predict the values of the outcome variable (in our case: sales) from values of multiple predictor variable

Question 18

example predictor variables

Answer 18

facebook, banner ads, emails

Question 19

example outcome variables

Answer 19

total sales euro

Question 20

Total Sales in Euro (€) is a quantity-metric variable here > SO we use

Answer 20

LINEAR REGRESSION

Question 21

All ad exposure variables are also measured in numeric/metric scale: i.e total number of times # each type clicked.
This means they can directly be used in

Answer 21

regression

Question 22

linear regression: Unstandardized Beta coefficients help us to interpret + example

Answer 22

absolute impact of each touchpoint on saleswe interpret them like:
Facebook: One more (increase) click on our Facebook ads is likely to increase our sales per person 17,683 € per year.

Question 23

lineair regression: (standardized beta coefficients)

Answer 23

Comparing the effects; which X variable has a stronger impact on Y

Question 24

linear regression: The Concept of INTERACTION

Answer 24

What is the combined effect of two different (X) variables?

Question 25

logistic regression most usely used tp ana;yze

Answer 25

touch[oints

Question 26

Logistic Regression: what shows significance

Answer 26

sig values

Question 27

logistic regression: what shows most influencal touchpoint

Answer 27

Odds Ratio shows us what is the most influential touchpoint

Question 28

logistic regression: Organic Search with Exp(B) Odds Ratio 365,392 means:

Answer 28

Customers who clicked Organic Search results are X 365 times more likely to convert (buy) in comparison to those who did not click Organic Search ResultsI know it is overly high & exaggatered (maybe not realistic) but I keep the effect HIGH for demonstration purposes – since this is an example :0)

Question 29

Probabilistic Attribution:

Answer 29

Value of Each Touchpoint in Journey