Develop a marketing look-alike profile for prospective customers I work for a business-to-business company that has a large database of existing clients (small businesses) with various columns of data (e.g., industry, credit-worthiness, financial data, etc) describing each client. There are several marketing data vendors I know of that maintain small-business databases with columns of data similar to what my company has. 

Question: Using the data my company already has, how I can I identify which customers in the vendors' databases have the highest potential of becoming a customer if marketed to? Should I build a predictive model? Should I do some sort of clustering?
The problem is that you only have positive instances (businesses who have become a customer) but no negative instances (businesses who haven't become a customer).  This prevents use of supervised learning.  You could try unsupervised learning -- e.g., a one-class classifier -- but I don't expect it to be particularly effective.

If you had data on businesses who you tried approaching, but ultimately did not become a customer of yours, then you could try applying supervised learning.