Final Exam

Question 1

Defining the Data Driven Marketing Strategy

Answer 1

Know yourself > know your customers > Segment your customers > Data driven marketing > build trust > keep score

Question 2

Firms that “keep score”

Answer 2

Research shows that firms that ‘‘keep score’’ for marketing have significantly better financial and market performance compared with those that do not.

Question 3

Road map for implementing data driven marketing

Answer 3

Design > Diagnosis > Opportunities > Tools > Process

Question 4

80/20 Rule

Answer 4

Start by collecting the right data to get the quick win—ask what is the 20 percent of data that will give 80 percent of the value?

Question 5

Metric #1 the essential awareness metric

Answer 5

Brand awareness = ability to recall a product or service
measured by asking for (product or service) what is the first (company or product) you think of? what other companies or products have you heard of?

Question 6

Metric #2 the essential evaluative metric

Answer 6

Test drive = customer pretest of a product or service prior to purchase

Question 7

Metric #3 the essential loyalty metric

Answer 7

Churn = percentage of existing customers who stop purchasing your products or services, often measured in a year, 90 days, or 30 days

Question 8

Metric #4 The golden marketing metric

Answer 8

CSAT = Customer satisfaction measured by asking “would you recommend this product or service to a friend or colleague?”

Question 9

Metric #5 the essential operational effectiveness metric

Answer 9

Take rate = percentage of customers accepting a marketing offer

= # of accepted offers/ # of contracts

Question 10

The four essential financial metrics

Answer 10

6 Profit = revenue - cost

#7 NPV = Net present value
#8 IRR = Internal rate of return
#9 Payback = the time for a marketing investment to payback the cost of initiative

Question 11

Metric #10 the essential customer value metric

Answer 11

CLTV= future value of a customer

Question 12

Acquisition cost

Answer 12

AC = Cost per contact * number of contacts / number of accepted offers

AC = cost per contact / Take rate

Question 13

NPV

Answer 13

NPV = PV-cost
So we are just calculating the benefit minus cost in each time period, which is just the profit metric #6, and discounting by the factors for the time value of money. This is the idea that the profit is worth less in the future.

Question 14

IRR

Answer 14

IRR is technically calculated by setting the NPV equation to zero and solving for r = IRR

If IRR is greater than r, in principle, one should invest, and if IRR is less than r, then one should not.

Question 15

Decision making from NPV, IRR, and payback

Answer 15

For management decisions, think NPV > 0 IRR > r, good; and NPV < 0 IRR < r, bad. Similarly, also think short payback, good; long payback, bad.

Question 16

Sensitivity analysis

Answer 16

Sensitivity analysis is essential to define the range of possible outcomes given the market risks and is surprisingly easy in Microsoft Excel.

Question 17

CLTV Matrix

Answer 17

High CLTV high Profitability: grow and retain
High CLTV low Profitability: grow, reduce costs, manage risks
Low CLTV High profitability: maintain relationships, transition to high CLTV
Low CLTV low profitability: manage costs, identify transition opportunities

Question 18

Metric 11: the essential search engine marketing metric

Answer 18

CPC = cost per click on a sponsored search link or banner advertisement

Question 19

Metric 12: the essential metric connecting internet clicks to dollars

Answer 19

TCR= transaction conversion rate; the percentage of customers who purchase after clicking through to your website

Question 20

Metric 13: the essential return on internet search marketing metric

Answer 20

ROA= return on ad dollars spent = net revenue / cost

Question 21

Take rate matrix

Answer 21

High CPC low take rate: high cost publishers not driving purchases; consider cutting
High CPC high take rate: high cost publishers driving purchases. Identify high ROA activities and duplicate within these publishers
Low CPC low take rate: publishers have a low probability of producing a purchase but CPC is low; use CTR vs TCR matrix to optimize campaigns
Low CPC high take rate: low cost publishers with highest probability of producing a purchase. Consider increasing funding for these publishers

Question 22

Metric 14: the essential website performance metric

Answer 22

Bounce rate = percentage of customers who leave your website after spending less than 5 seconds on your site

Question 23

Metric 15: the essential metric for word of mouth on the internet

Answer 23

WOM = word of mouth = (# of direct clicks + # of clicks from recommendations) / # of direct clicks

Question 24

What is the purpose of pivot tables?

Answer 24

A Pivot Table is used to summarise, sort, reorganise, group, count, total or average data stored in a table. It allows us to transform columns into rows and rows into columns. It allows grouping by any field (column), and using advanced calculations on them.

Question 25

Descriptive vs Predictive vs Prescriptive Statistics

Answer 25

descriptive analytics, which tell us what has already happened; predictive analytics, which show us what could happen, and finally, prescriptive analytics, which inform us what should happen in the future.

Question 26

ROMI

Answer 26

ROMI = [𝑅𝑒𝑣𝑒𝑛𝑢𝑒 𝐴𝑡𝑡𝑟𝑖𝑏𝑢𝑡𝑎𝑏𝑙𝑒 𝑡𝑜 𝑀𝑎𝑟𝑘𝑒𝑡𝑖𝑛𝑔 × 𝐶𝑜𝑛𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛 %− 𝑀𝑎𝑟𝑘𝑒𝑡𝑖𝑛𝑔 𝐶𝑜𝑠𝑡 ($)]/
𝑀𝑎𝑟𝑘𝑒𝑡𝑖𝑛𝑔 𝐶𝑜𝑠𝑡 ($)

Question 27

Why is the standard definition of ROI not one of the essential marketing metrics is?

Answer 27

First, the ROI defined above does not include the time value of money. We have discussed that money in the future is worth less than money today, but this ROI definition assumes all time periods are equal. The other major challenge is the length of time. For example, one can have an ROI of 100 percent for a campaign that is nine months or three years. The ROI number is the same but the campaigns are clearly completely different. This is why ROI defined above is not one of the essential marketing metrics in this book.

Question 28

CLTV Calculation

Answer 28

CLTV = 𝐶𝑜𝑛𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛 𝑀𝑎𝑟𝑔𝑖𝑛 ×
𝑅𝑒𝑡𝑒𝑛𝑡𝑖𝑜𝑛 𝑅𝑎𝑡𝑒 %/ 1+𝐷𝑖𝑠𝑐𝑜𝑢𝑛𝑡 𝑅𝑎𝑡𝑒 (%)−𝑅𝑒𝑡𝑒𝑛𝑡𝑖𝑜𝑛 𝑅𝑎𝑡𝑒 (%)

Question 29

What is the flaw in the CLTV metric?

Answer 29

Keep customers who show a positive NPV for the marketing investment, the rules say, and drop the ones who don’t. Those are rational choices at the time of the calculation—but only then. The conventional calculation is thus rather static and actually flawed, because you are not able to factor in a company’s flexibility to cut a given customer loose at any time.

More important, some negative CLVs actually turned positive when the value of the real options was considered. In other words, we found that neglecting a customer with a negative NPV—as traditionally calculated—may be exactly the wrong choice: He could turn out to be highly profitable.

Question 30

Web analytics vs marketing analytics

Answer 30

Web analytics measure things a webmaster cares about, like page load times, page views per visit, and time on site. Marketing analytics, on the other hand, measure business metrics like traffic, leads, and sales, and which events (both on and off your website) influence whether leads become customers.

Marketing analytics mostly focus on ‘people’ and is thus, customer-centric, giving more emphasis to the prospect, lead or customer while web analytics usually consider the page view as the factor of focus.

Question 31

Elastic vs Inelastic demand and pricing

Answer 31

An elastic demand is one in which the change
in quantity demanded due to a change in price is large. An inelastic demand is one in which the
change in quantity demanded due to a change in price is small.

Given a demand curve, the price elasticity for demand is the percentage of decrease
in demand resulting from a 1 percent increase in price. When elasticity is larger
than 1, demand is price elastic. When demand is price elastic, a price cut will
increase revenue. When elasticity is less than 1, demand is price inelastic. When
demand is price inelastic, a price cut will decrease revenue.

Question 32

What is the purpose of linear regression?

Answer 32

Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable’s value is called the independent variable.