Forecast Forensics + Digital Profiles: Creation Via Factor Analysis

Here's the variables that I elected to enter into creation of sixteen Digital Profiles (contact me for your own customized project):

• Data for the past twelve months ... using the scoring algorithm from the past twelve months to score prior years as well.
• Frequency:  Orders in past year.
• Items per Order:  Total annual items (20) divided by total annual orders (4) = 5.00.
• Price per Item:  Total annual demand ($800) divided by total annual items (20) = $40.00.
• 1/0 Indicator:  Did customer buy using telephone channel in past year?  1 = yes, 0 = no.
• 1/0 Indicator:  Did customer buy using all other online channels in past year?
• 1/0 Indicator:  Did customer buy using last-click attribution to e-mail in past year?
• 1/0 Indicator:  Did customer buy using last-click attribution to search in past year?
• 1/0 Indicator:  Did customer buy using last-click attribution to social media in past year?
• 1/0 Indicator:  Did customer buy using last-click attribution to mobile in past year?

So, we create a dataset that has one year of data, with these attributes.

WARNING:  The rest of this post gets really "geeky" ... so if you don't like math, move along, there's nothing to see here!


Here are descriptive statistics for our variables:

The means and standard deviations are used later, when I want to create each of four factors.


Next, we run a factor analysis / principal components analysis, extracting four factors.  Here is the rotated component matrix:

In this analysis, we're looking for metrics with an absolute value greater than 0.20 ... this helps us identify the variables that contribute to each factor.

• Factor #1 = Frequency, Mobile, and Social.  This factor likes loyal customers who have migrated to mobile and social channels.
• Factor #2 = Telephone, Not Online.  In other words, this factor favors old-school shoppers who call the contact center to place an order.
• Factor #3 = Many Items per Order, Low Price per Item:  These customers like cheap items, and they buy lots of cheap items!
• Factor #4 = E-Mail + Search:  Customers who buy via e-mail and search, not necessarily other online channels, fall into this factor.  Kinda makes one wonder if e-mail causes search to happen, doesn't it?

Up Next:  We'll create sixteen Digital Profiles from the four factors extracted from this analysis.