RFM Output

This feature is available in the Direct Marketing option.

Binned Data

Charts and tables for binned data are based on the calculated recency, frequency, and monetary scores.

Heat map of mean monetary value by recency and frequency. The heat map of mean monetary distribution shows the average monetary value for categories defined by recency and frequency scores. Darker areas indicate a higher average monetary value.

Chart of bin counts. The chart of bin counts displays the bin distribution for the selected binning method. Each bar represents the number of cases that will be assigned each combined RFM score.

• Although you typically want a fairly even distribution, with all (or most) bars of roughly the same height, a certain amount of variance should be expected when using the default binning method that assigns tied values to the same bin.

• Extreme fluctuations in bin distribution and/or many empty bins may indicate that you should try another binning method (fewer bins and/or random assignment of ties) or reconsider the suitability of RFM analysis.

Table of bin counts. The same information that is in the chart of bin counts, except expressed in the form of a table, with bin counts in each cell.

Unbinned Data

Chart and tables for unbinned data are based on the original variables used to create recency, frequency, and monetary scores.

Histograms. The histograms show the relative distribution of values for the three variables used to calculate recency, frequency, and monetary scores. It is not unusual for these histograms to indicate somewhat skewed distributions rather than a normal or symmetrical distribution.

The horizontal axis of each histogram is always ordered from low values on the left to high values on the right. With recency, however, the interpretation of the chart depends on the type of recency measure: date or time interval. For dates, the bars on the left represent values further in the past (a less recent date has a lower value than a more recent date). For time intervals, the bars on the left represent more recent values (the smaller the time interval, the more recent the transaction).

Scatterplots of pairs of variables. These scatterplots show the relationships between the three variables used to calculate recency, frequency, and monetary scores.

It's common to see noticeable linear groupings of points on the frequency scale, since frequency often represents a relatively small range of discrete values. For example, if the total number of transactions doesn't exceed 15, then there are only 15 possible frequency values (unless you count fractional transactions), whereas there could by hundreds of possible recency values and thousands of monetary values.

The interpretation of the recency axis depends on the type of recency measure: date or time interval. For dates, points closer to the origin represent dates further in the past. For time intervals, points closer to the origin represent more recent values.