e’ve all heard the hype about how the latest and greatest revenue management (RM) system can accelerate self-
storage revenue growth. Industry analysts extol the virtues of “advanced technology” as publicly traded REITs emphasize the ways they can improve the bottom line by using their advanced RM systems. But what are these systems, and are they good for the long-term health of our industry?

Essentially, RM systems attempt to predict how customers will respond to price changes on an item being sold. In many industries, there is meaningful “elasticity of demand,” meaning that as prices decrease, demand will increase. But there is very little elasticity of demand in self-storage because we sell a “needs-based” product. The item we “sell” is a month of use in a storage unit. The RM system tries to predict how an existing or prospective customer will respond to an increase or decrease in the price of a rental unit.

There are two problems with using RM systems in self-storage. The first is that algorithms always use historical data to predict customer response. That works fine when history continues to repeat itself, which has been true over the past 15 years while demand has continuously grown. Today, that historical trend has stopped because one entire segment of historical demand has disappeared. Almost no one today is selling their existing home with a 3 to 4 percent mortgage to move into a nicer home with a 7 to 8 percent mortgage! That segment of demand has disappeared, making the basis for many of today’s RM algorithms invalid.

The second problem with using RM systems in our industry is that we have almost no upside elasticity of demand, so we aren’t creating any more demand by reducing our prices. All we are doing is fighting over the limited number of customers already out there. Today, the RM-driven price reductions just create competitive responses that drive increased rivalry and a “race to the bottom” on prices. And RM systems are terrible at predicting competitive responses with no historically comparable data.

Historically, self-storage has been a very strong industry for long-term profitability because the intensity of rivalry has been relatively low. Property owners only competed within their 3- to 5-mile trade radius for very fragmented, low-ticket customers paying month to month—unlike office, warehouse, and retail properties with big-ticket customers on long-term leases. It made no sense to jeopardize profitability by cutting prices to get one small customer. But automated RM systems that don’t have the historical data or intelligence to accurately predict competitive responses are now driving advertised prices in the majority of our markets. In today’s world of reduced demand, these RM systems are seriously detrimental for the industry.