Welcome to my first foray into the world of blogging.  As the title of the blog suggests, I’ll talk a lot about pricing…and more. Along with revenue management and pricing psychology, we’ll discuss all sorts of other demand management issues—marketing, credit scoring, sales process, and more. Some of it will be serious and some just amusing. Many ideas will come from me, but many will come from other experts in the field, from clients (with their permission) and from readers (so send your own observations or questions to me atThis email address is being protected from spambots. You need JavaScript enabled to view it.).

Let’s start with something serious. There’s been so much talk about pricing and revenue management—particularly sophisticated pricing software systems like Lease Rent Options^TM and Yieldstar^TM, that I thought it might be worth starting with an overview of a model of the maturation of pricing:

In future posts, I’ll dive into more detail on each. But for starters, let’s focus on the three key stages of pricing maturation (the green boxes):

1. Price Administration: This first, and most basic, stage is all about exactly what it says—administering prices. A good Price Administration System (PAS) ensures that prices put in the system are in fact quoted to customers. A PAS ensures any rules (e.g. late fees, pet rent, application fees) are in fact followed. And  a PAS either prevents sales from happening at the wrong price or at least alerts executives when it happens.

2. Data Mining: this is sometimes referred to as “business intelligence” (BI). In this stage, data is collected from various sources—your PAS, your PMS (“property management system”), lead generation sources, etc.; and then the data is analyzed to find trends that are useful in setting pricing rules. What's the median time from guest card to lease signing? What's the seasonality? Early termination percentage? How have renewals performed?

3. Price Optimization: In this most sophisticated phase of pricing maturity, data is not only collected and mined, it is also used to create forecasts of supply and demand which are then fed into an optimization algorithm designed to maximize some desirable results (usually in multi-family housing that’s something like “maximizing the next 12 months of operating revenue”). This stage of maturity needs technology solutions developed by experts in this kind of math--PhDs in operations research, behavioral econimics, etc. Optimization is not for amateurs and dilettantes.

So where is your organization in its journey to pricing nirvana? What will it take for you to move further up this value chain? More on each of these coming up.