A full facility can still face weaker pricing. A useful self-storage investment screen connects occupancy, realized rent and relevant competing supply. Read these measures together before deciding that a market is either undersupplied or saturated.
Start with a real example of the measures moving apart
Public Storage’s second-quarter 2026 results show occupancy rising while rental revenue per square foot fell. The comparison covers 2,755 same-store facilities. These portfolio figures illustrate the relationship; they do not establish conditions in your target market.
| Reported same-store measure | Q2 2025 | Q2 2026 |
|---|---|---|
| Average occupancy | 92.3% | 92.5% |
| Annual rental income / occupied sq ft | $22.06 | $21.89 |
| Annual rental income / available sq ft | $20.36 | $20.24 |
Source: Public Storage, 29 July 2026: Q2 2026 results, operating table and metric definitions
Use the denominator that matches the decision
Occupied-foot rent describes rented space; available-foot rent spreads income across all rentable space. Public Storage’s figures include promotional discounts, exclude late and administrative fees, and omit unstabilized fill-up properties from the same-store comparison.
Using the rounded inputs, $22.06 × 92.3% = $20.36 in 2025; $21.89 × 92.5% = $20.25 in 2026. The reported 2026 result is $20.24 because displayed inputs are rounded.
Before comparing local operators, align definitions. Web asking rates are not collected rents. Public availability does not reveal facility occupancy. Label a study built from asking rates as a price survey.
Source: Public Storage, 29 July 2026: Q2 2026 results, operating table and metric definitions
Count the product that would actually compete
A supply-per-person ratio can help organize a market screen, but it collapses unit sizes, storage types, location and price into one number. Build the competitor set around the proposed product: for example, climate-controlled units of specified sizes within a defined catchment. Preserve other supply as context.
Fictional example: the study area contains 240,000 square feet of known rentable storage and 40,000 residents. The broad ratio is six square feet per person. Only 64,000 square feet is confirmed as the target product. A verified future project would add another 10,000 square feet of that product, increasing known relevant capacity by 15.625%.
The useful question is whether demand and achievable pricing can support that specific increase. Six square feet per person has not answered it. Keep unknown capacity and uncertain unit mix outside the confirmed total, with a visible list of unresolved properties. Match geography and observation periods when comparing ratios.
Build scenarios without pretending to know delivery probabilities
For the fictional market, the table below shows relevant supply under three delivery scenarios. “Half delivered” is an assumption to test, not a claim that the project has a 50% chance of completion. Record construction status, source and latest confirmation separately from your scenario.
| Scenario | Known relevant existing supply | New relevant supply | Total | Increase |
|---|---|---|---|---|
| No project delivery | 64,000 sq ft | 0 | 64,000 sq ft | 0% |
| Half delivered | 64,000 sq ft | 5,000 sq ft | 69,000 sq ft | 7.8125% |
| Full delivery | 64,000 sq ft | 10,000 sq ft | 74,000 sq ft | 15.625% |
Test how much occupancy can compensate for a price cut
A separate fictional operating case makes the trade-off visible. Suppose a comparable facility earns $24 annually per occupied square foot at 90% occupancy. That produces $21.60 per rentable square foot. If occupied-foot revenue falls 5% to $22.80 while occupancy rises to 93%, the result is $21.204, down about 1.8%.
To hold the original $21.60 with a $22.80 occupied-foot rate, occupancy must reach about 94.74%: $21.60 ÷ $22.80. This is a break-even revenue calculation, not a market forecast. It excludes other income, operating costs and timing. It tells the team exactly which occupancy assumption needs support when the rate assumption weakens.
Test the case against consistent local observations: comparable unit rates and incentives over time, verified operating information where available, and the stage of competing projects. A higher advertised rate is not evidence of collection, and a waitlist is not equivalent to a signed, paying customer.
Build a useful screen in five steps
Use three linked tabs: competing units, future projects and operating scenarios. Each observation should retain its source and date. Keep a separate list of gaps that could change the conclusion.
- Define the proposed product and catchment. Record what qualifies as relevant competition before collecting rates.
- Inventory operating capacity by product, preserving confirmed, conflicting and missing information. Record asking rates and terms without inferring occupancy.
- List future projects by stage, expected product and dated evidence. Calculate explicit delivery scenarios with a consistent capacity measure.
- Where operating evidence is available, connect occupancy with realized rent and revenue per rentable foot. Calculate the occupancy or rent needed to preserve your baseline.
- Write a one-page decision note: what the evidence supports, which assumption carries the case and the next fact needed before further site or financial diligence.
Make the next update easier than the first
The first screen defines the comparison. The ongoing work is keeping the same properties, unit definitions and dates aligned as offers change and projects advance. A repeatable process should show what changed and whether that change affects the investment question. Adding more unclassified map pins does not resolve a pricing or supply gap.
Sources and further reading
Sources checked 12 October 2026. Examples and workflow suggestions are Dart editorial guidance.
Turn your storage screen into a maintained analysis
Bring one market, your proposed unit mix and the model your team uses. Dart can help scope a repeatable review of relevant competitors, future supply and the assumptions that need fresh evidence.
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