2 Factors that Impact the Economics of Occupancy in Self Storage
Has your self storage facility encountered the situation where most of your units are occupied (80% occupancy or higher), but there’s still ample square footage that hasn’t been rented?
If that scenario sounds familiar, there’s an imbalance with your Economic Occupancy.
But what is Economic Occupancy?
In the latest installment of “Data Science with Dawson”, we address self storage occupancy and how data science can be applied to reduce occupancy imbalances. Continue reading to learn:
- A definition of data science for your self storage marketing team and owner/operator
- A definition of economic occupancy for self storage marketing teams and owners/operators
- Two Considerations your self storage facility can make to maximize profits and occupancy potential
What is Data Science for the Self Storage Industry?
Data science involves the extraction of large sets of data to predict outcomes and produce insights that provide solutions and business intelligence.
What is Economic Occupancy?
Economic occupancy is the amount of money a facility could be taking in versus how much money a facility is actually taking in.
For example, if 90% of your units are leased, it would be referred to as your physical occupancy. However; if your facility’s economic occupancy is at 60%, there are steps your self storage marketing team and ownership can take to correct this occupancy imbalance.
There are numerous factors that impact economic occupancy. Let’s address two factors commonly found in the storage industry.
Factor #1: Large Units Versus Small Units: What’s Selling?
When analyzing your facility’s data, you may discover that one type of unit may lease more frequently than another in your geographic area. Whether your facility tends to lease out smaller units historically or larger units, the data gleaned will help your owner/operator make strategic decisions that will benefit your economic occupancy.
In the case that smaller units tend to sell better, you could divide larger units into smaller units to accommodate these customers. Conversely, if larger units tend to lease more frequently, your facility could combine smaller units together.
With a data science model in place, your owner/operator will have data historically appended and will confidently be able to identify anomalies (certain units didn’t sell for a period of time but historically perform well for a facility) and overarching trends.
Factor #2: Are Discounts Helping or Hurting Profitability?
There’s a delicate balance between providing incentives for customers who rent your units and generating continuous revenue for profitability. In the instance that discounts are applied for more than one month, look at your facility’s data to determine the length of stay.
If your customers receiving a discount, such as “10% off rent every month” tend to stay for years, it could cause an occupancy imbalance. To correct this imbalance, your owner operator could raise the rates on these customers. They will either continue renting from your facility at the new raised rate, or will move out, allowing for another renter to move in at the new, raised rate. Either way, your facility will increase its profitability.
Contact Our Team to Solve Your Occupancy Imbalances in Self Storage
Occupancy itself is a science. Luckily, it is a science that data science can be leveraged to help. In order to prevent an occupancy imbalance, your facility will need to identify the conditions in place that are the root cause of the imbalance.
For help with data analysis, reporting, awareness of operational and marketing problems, contact us. Our team will help your facility maximize its profits while maintaining a healthy threshold for its occupancy.