Overcoming Base Rate Bias

When it comes to understanding or anticipating customer needs, we often assume we know more than we do. We often experience biases, such as base rate bias, that may cloud our judgement. Common misperceptions in the self-storage industry include:

• My customers will move out if rents are raised above the street rate, or above a certain percentage.
• All my competitors are lowering their prices, so I need to lower mine.
• My prices are higher than my competitors. Therefore, I cannot charge more for a more conveniently located unit in a unit group.

Base Rate Bias.

There is certainly some truth to all of the above. However, the tendencies noted above are not as “all encompassing” as we often anticipate. For example, when carrying out a detailed analysis of rentals and rent increases, many operators discover that far fewer customers move out than they anticipate when rents are raised to levels above the current street rate.

What we remember, however, are the instances where customers complain. Especially, when they complain about rent increases being too much. In fact, the tendency to ignore more important, general information over a specific case has a name: base rate bias. In our case, the general information is that many customers continue to rent despite receiving a rent increase. The specific case is the customer complaint of a rent increase.

Base rate bias often operates in conjunction with other aspects of reasoning errors. Confirmation bias is another example. Confirmation bias occurs when we look for and interpret information that confirms our preconceptions. We tend to avoid revising beliefs even when presented with new evidence. There are many other biases which, together, often result in the perpetuation of various pricing myths. For those who are willing to invest the time and energy in data analysis and adopt data-driven decision making, many opportunities to increase revenues and profits emerge.

How can decision-making biases affect you?

Let’s put this to the test. What percent of your customers do you think would pay 10 percent more to rent a unit that is slightly more convenient? For example, suppose you have two available units of the same size on the second floor of your self-storage facility. One unit is only one hallway turn from the elevator and the other is two hallway turns away. (Assume all the units closer to the elevator are occupied). Take a moment to think about this before reading the next paragraph. What percent of your customers do you think would pay 10 percent more for the unit closer to the elevator?

Was your answer 10 percent? Perhaps 20 percent or even 25 percent?

In fact, our experience in the United States, Canada, South Africa and Australia shows that 25 to 45 percent of new customers will generally be willing to pay more for a more convenient available unit. Even at single-story, all drive-up facilities, 15 to 20 percent of customers, and frequently more than that, are prepared to pay more for a unit they consider to be better located. Many operators underestimate the willingness of customers to pay more for a better located unit.

Focus on the base rate.

With regards to rent increases, the types of biases noted above often result in operators being more cautious than they need to be. That does not operators should increase everyone’s rent by a greater amount. Rather, in a data-driven world, we refocus the question into:

1. Whose rents should be increased by a greater amount?
2. Whose rents should be increased by a lesser amount (or not at all)?

By refocusing the rent increase process and decisions, operators can increase the overall amount of rent increases while simultaneously reducing the number of rentals that terminate due to receiving a rent increase. While that may seem counter-intuitive, it is possible because data-driven techniques are better able to identify the leases that are more likely to move out due to a rent increase, as well as those leases, where if they do move out, would lead to greater revenues from new move-ins paying a higher rate.

It’s often good to be reminded that sometimes what we think we know, isn’t an accurate depiction of how our customers behave. Capitalizing on that knowledge can lead to higher revenues and profits.