For any company with a transaction file, organization of those transactions is key to customer and prospect analysis. This means to "roll-up" key transaction information to be stored in a framework, with one record per customer, to tell of their transaction history. For example, create a field called AttendedAnnual2012. Wherever someone attended the annual meeting in 2012, we will have a value of 1, and if they did not attend the annual meeting, we will fill it with 0. By querying the transaction table with the proper criteria for attendance in the annual meeting, we can derive who attended, using this to update our new framework field.
With this shorthand notation for transaction, list generation becomes more straightforward. For example, mail a brochure for this year's annual meeting to whoever attended last year. And these selections may become more complex as the need dictates. For example, select anyone who attended the annual meeting in the last three years, bought a product from us in the last three years, or has joined our mailing list.
Predictive analysis also becomes more practical when transactions are organized. There are several tools available to look at a group of contacts, say, those contacts who renewed their contract or membership, and compare to another group of contacts, say, those contacts who canceled their contract or membership. With a variety of transactional knowledge at hand, these tools can help give precise predictions of the future transactions, based on the data of present contacts when compared to past.
A combination of transactional and demographic information (gender, location, profession) will lead to a useful and practical framework of customer and prospect information, full of opportunities and insight.
For details, please contact BDS: