Step 1: Take a calendar year (2007), or any twelve month period of time. Create an indicator (1 = yes, 0 = no) whether the customer purchased from a micro-channel during that timeframe.
Step 2: Take the next calendar year (2008), or any subsequent twelve month period of time. Create the same set of indicators (1 = yes, 0 = no).
Step 3: Take any one indicator in Step 1 (say the customer purchased because of Google Paid Search), and store those customers in a file.
Step 4: For all customers in Step 3, calculate the percentage of customers who.
- Purchased in the dataset in Step 2.
- Purchased from any of the indicators in the dataset in Step 2.
Step 6: Classify each index on the basis of the following criteria.
- Isolation Mode = An index between 0.00 and 0.20.
- Equilibrium Mode = An index between 0.20 and 0.50.
- Transfer Mode = An index greater than 0.50.
Equilibrium Mode is where all of the subtleties of a business happen. In social media, we've seen the slow leak from blogging to micro-blogging, as users migrate away from blogs to their own Twitter page. For catalogers, there has been a decade-long leak from customers ordering over the telephone to customers ordering via websites. For online channels within retailers, you'll see that customers rarely stay loyal to the online channel ... often, the customer slowly leaks back to the retail channel.
Transfer Mode happens when there is a mass exodus from a product, brand, or channel to another product, brand or channel.
Work with the good folks at Coremetrics or Omniture to have these metrics generated for you, there's no reason they cannot calculate these metrics, at a micro-channel level, to assist you in understanding how customers are interacting with micro-channels. For you catalogers who partner with Unica, they certainly have the skills necessary to do this, just ask them! And for those of you lucky enough to have a SQL/SAS/SPSS programmer, this is brutally easy to do!
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