INMA_A01.QXD

Recency:

1 – Over 12 months

2 – Within last 12 months

3 – Within last 6 months

4 – Within last 3 months

5 – Within last 1 month

Frequency:

1 – More than once every 6 months

2 – Every 6 months

3 – Every 3 months

4 – Every 2 months

5 – Monthly

Monetary value:

1 – Less than £10

2 – £10–£50

3 – £50–£100

4 – £100–£200

5 – More than £200

Simplified versions of this analysis can be created to make it more manageable, for

example a theatre group uses these nine categories for its direct marketing:

Oncers (attended theatre once)


Recent oncer attended <12 months


Rusty oncer attended >12 <36 months


Very rusty oncer attended in 36+ months

Twicers:


Recent twicer attended < 12 months


Rusty twicer attended >12, < 36 months


Very rusty twicer attended in 36+ months

2+ subscribers:


Current subscribers booked 2+ events in current season


Recent booked 2+ last season


Very rusty booked 2+ more than a season ago

Another example, with real-world data is shown in Figure 6.13. You can see that plot-

ting customer numbers against recency and frequency in this way for an online

company gives a great visual indication of the health of the business and groups that

can be targeted to encourage greater repeat purchases.

Product recommendations and propensity modelling

‘Propensity modelling’ is one name given to the approach of evaluating customer charac-

teristics and behaviour, in particular previous products or services purchased, and then

making recommendations for the next suitable product. However, it is best known as

recommending the ‘Next Best Product’ to existing customers.

A related acquisition approach is to target potential customers with similar character-

istics through renting direct mail or e-mail lists or advertising online in similar locations.

The following recommendations are based on those in van Duyne et al. (2003).

APPROACHES TO IMPLEMENTING E-CRM

Propensity
modelling
A name given to the
approach of evaluating
customer
characteristics and
behaviour and then
making
recommendations for
future products.