Marketing Communications

MEASURING DIRECT MARKETING EFFECTIVENESS 445

In the customer’s mind, five elements determine the value of a loyalty programme: cash

value, the number of options, aspiring value, relevance and convenience. The value should be

calculated as a percentage discount on the amount a consumer has to spend to be able to get

the reward. A free trip to a Caribbean island or a new car has a higher aspiring value than

a discount on a phone bill. Customers should also be able to choose from different benefits.

A programme is only relevant if the aspired benefit is within reach; if it takes years to collect the

necessary air miles to make a free trip it will not be of any relevance to a customer. If it takes

a lot of administration, whether for the customer or the retailer, a loyalty programme has a

small chance of success. This is what is meant by ‘convenience’.

Measuring direct marketing effectiveness

Direct marketing and interactive marketing are behaviour-oriented in nature, and therefore

research into the effectiveness of direct and interactive marketing campaigns will invariably

be tests of ‘counting’ behavioural response, e.g. the number of people responding to a free

phone number in a DRTV commercial.

Evidently, all communications effectiveness tests are aimed at subsequently improving the

communications effort. In direct marketing, which is essentially database-driven, the optimi-

sation of a direct mailing campaign can be based on response scoring models, i.e. a procedure

in which a number of indicators of behavioural response in the past are combined. A well-

known response scoring model is the RFM-model. For all customers in a database, three

behavioural response parameters are measured:

   Recency: the time elapsed since the last purchase.

   Frequency: the frequency with which a customer places an order.

   Monetary value: the average amount of money a customer spends per purchase.

Obviously, the shorter the time elapsed since a customer placed an order, the more frequently he

or she buys something; and the higher the average amount of money spent, the more positive the

expected response is following the next mailing campaign.^70 For each of the three variables,

a number of categories can be defined, and each category can be given a ‘value’ or score rep-

resenting the importance of each category for future response. This is illustrated in Table 13.3.

Evidently, the values attached to each category are, to a certain extent, arbitrary, but they

can also be derived from the analysis of past response behaviour. The RFM values can now

be used selectively to mail those members of the target group that have the highest score on

one or two of the three factors, or on a combination of all three. It can, for instance, be

decided to mail only those customers that have a score of at least 80 on the recency value,

as well as a score of 30 on the frequency factor. Response scoring models can improve the

effectiveness of mailing or e-mailing campaigns. It is advisable, however, to pre-test a campaign

before sending it out to a sample of target group members.

Table 13.3 The RFM-model

Recency Score Frequency Score Monetary value Score

Last 6 months 100 Once a year 0 Less than €100 0

7–12 months 80 Between 2 and 4 times a year 30 More than €100 20

13–24 months 60 More than 4 times a year 70

25–36 months 30

37 months or more 0

M13_PELS3221_05_SE_C13.indd 445 6/5/13 2:56 PM