INMA_A01.QXD

Hurdle rate

According to Novo (2003), ‘hurdle rate’ refers to the percentage of customers in a group

(such as in a segment or on a list) who have completed an action. It is a useful concept,

although the terminology doesn’t really describe its application. Its value is that it can

be used to compare the engagement of different groups or to set targets to increase

engagement with online channels as the examples below show:


20% of customers have visited in past 6 months


5% of customers have made 3 or more purchases in year


 60% of registrants have logged on to system in year


 30% have clicked through on e-mail in year.

Grouping customers into different RFM categories

In the examples above, each division for Recency, Frequency and Monetary value is

placed in an arbitrary position to place a roughly equal number of customers in each

group. This approach is also useful since the marketer can set thresholds of value rele-

vant to their understanding of their customers.

RFM analysis involves two techniques for grouping customers

1 Statistical RFM analysis

This involves placing an equal number of customers in each RFM category using quin-

tiles of 20% (10 deciles can also be used for larger databases) as shown in Figure 6.12.

The figure also shows one application of RFM with a view to using communications

channels more effectively. Lower-cost e-communications can be used to correspond with

customers who use only services more frequently since they prefer these channels while

more expensive offline communications can be used for customers who seem to prefer

traditional channels.

2 Arbitrary divisions of customer database

This approach is also useful since the marketer can set thresholds of value relevant to

their understanding of their customers.

For example, RFM analysis can be applied for targeting using e-mail according to how

a customer interacts with an e-commerce site. Values could be assigned to each customer

as follows:

CHAPTER 6· RELATIONSHIP MARKETING USING THE INTERNET

Figure 6.12RFM analysis

Frequency

5

Highest

Each R quintile contains

20 % of all customers

R = 5, F = 5 contains

10 % of customers

Lowest

Note here boundaries are arbitrary in order to place an equal number into each group

4

Direct mail 3

Phone

E-mail/web

only

2

1

Monetary

5

4

3

2

1

Recency

5

4

3

2

1