A Key Metric: Predicting Storage Demand With Median Home Values
What would you say is the most important key metric in predicting self-storage demand and potential rent growth? Answers might include:
- Population growth,
- Population density,
- Median household income,
- Average household income,
- Supply per capita,
- Incoming residential construction,
- Incoming self-storage construction, and
- Percent of area that is renter-occupied.
These are all important metrics to consider when evaluating storage investment opportunities. Median household income is commonly used to evaluate the potential of a market. It’s intuitive to think that an area with a greater household income can support higher rents, right? Let’s look at the data.
Although there is some correlation between these variables, it does make sense that median household income shouldn’t be relied on in predicting street rates. The beauty of self-storage is that it attracts customers from all walks of life and all income levels. Moving, downsizing, renovating, decluttering, and of course things like death and divorce, are all reasons people rent self-storage. These major life events impact customers at every income level.
What if there was a better key metric for predicting street rates than median household income? Median home value is often overlooked and not discussed within the industry, but it is a much better predictor of street rates within a market.
Although it’s helpful to understand street rates and how median home value correlates, the real prize investors are after is achieved rates. Uncovering what the actual achieved rate facilities are producing within a market is one of the great challenges investors face. Most of this information is private and extremely hard to get. The publicly traded self-storage REITs do publish some of their achieved rate data, but it is generalized into large MSAs. We’ve compiled achieved rate data from the REITs and compared it to street rates.
To summarize, we’ve determined that median home value is a better predictor of street rates and achieved rates than median household income. But how well correlated is median home value to occupancy? Let’s explore.
It makes sense that median home value is not a driver of occupancy in self-storage. Occupancy is more likely tied to factors such as:
- Incoming self-storage supply,
- Competition (different pricing, promotion, and discounting strategies), and
- Accessibility and visibility from a major road with high daily traffic counts.
What does occupancy tell us about rates (achieved and street) in a given market?

- There are very few instances where rates are above $2.00 per SF in a market with sub-90 percent occupancy.
- Ninety-one percent to 95 percent occupancy appears to be optimal for pricing as there are many instances where rates reach above $2.00 per SF.
- In markets that are 95-plus percent occupied, there are zero instances where rates crest the $2.00 per SF mark. If a facility is approaching 100 percent occupancy, there is likely money left on the table. When a facility is highly occupied, operators can afford to sacrifice a little occupancy and more than make up for the revenue lost by raising rates on existing tenants or achieving higher move-in rates.
In conclusion, data can be a powerful tool in determining what key metrics to focus on when evaluating self-storage investments. The biggest takeaways from this article are summarized below.
- Median home value is a much better (almost two times) predictor than median household income of the rates (street and achieved) a market can sustain.
- Despite the various pricing strategies among operators, street rates are an excellent predictor of achieved rates. If a market has lower street rates, it’s likely the achieved rates aren’t much better.
- Median home value and rates are not very correlated to occupancy. To predict occupancy, consider looking at key metrics like incoming storage supply, competition, accessibility, and visibility.
This article is not meant to conclude that median home value trumps all other key metrics. It’s important to look at data for every key metric to uncover the full potential of a prospective investment. Better data leads to better decisions.
–
Noah Starr is the CEO of Tract IQ
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