That comparison shows whether the surge is growing, flat, or shrinking, without requiring any external benchmark.
What do you need before you start measuring?
Before you pull a single report, lock down two things: the exact date range you call your student window, and the total unit count you will use as your denominator. If you change either one between years, the numbers are not comparable.
You also need access to your management summary report. According to Inside Self Storage, the management summary report in self-storage property management software shows physical, square-foot, and economic occupancy alongside move-ins and move-outs for each month, making it the standard collection instrument for all three measures.
Self-storage management software platforms including Storable/SiteLink, Self Storage Manager, and Yardi Storage Manager record move-in and move-out events at the transaction level, so you can filter those events by date range to isolate your defined student-season window, as noted by Inside Self Storage.
What are the three measures, their denominators, and how do you collect them?
Physical occupancy rate is the number of units currently rented divided by total available units, expressed as a percentage, according to Inside Self Storage. The denominator is your total rentable unit count, not just the unit type a student typically rents. Collect it by pulling your management summary report on the last day of your student window and recording the figure.
Net move-in rate, also called net rentals, is move-ins minus move-outs within a given period, measured in units per week or month, according to Storable. A positive figure indicates net absorption; a negative figure indicates net churn. The denominator here is time, one week or one month, so be consistent. Collect it by filtering your transaction log for the student window and subtracting total move-outs from total move-ins.
Move-in-to-move-out ratio, or MI/MO ratio, is move-ins divided by move-outs for the same period. Storable's Storage Monitor reported a ratio of 1.18, meaning 118 move-ins per 100 move-outs, in June 2023, illustrating how the ratio is expressed and used to track net demand direction. Collect it from the same transaction data you used for net move-in rate.
How do you run the workflow in order?
- Record your total available unit count on the first day of the window.
- On the last day of the window, open your management summary report and record physical occupancy.
- Filter your move-in and move-out transaction log for the window dates.
- Calculate net move-in rate: total move-ins minus total move-outs, then divide by the number of weeks in the window to get a weekly rate.
- Calculate MI/MO ratio: total move-ins divided by total move-outs.
- Record all three figures in a single row of a spreadsheet alongside the year and window dates.
- Repeat the same pull for the prior year if the data exists, so you have a year-over-year comparison on day one.
What does a hypothetical example look like?
No benchmark is implied by these numbers; they are a starting point for year-over-year comparison.
What should you track alongside the numbers?
- Gate code activations per day during the window as a proxy for actual access volume
- After-hours rental inquiries or calls that came in outside staffed hours
- Move-out dates tenants gave at move-in, so you can forecast the post-rush vacancy wave
- Any units that turned over more than once inside the window
Inside Self Storage notes that most storage facilities peak in May and August and experience a dip from October through January, confirming that the late July through late August student window falls squarely inside the documented seasonal peak. That means your student-season lift is competing with general summer demand, so unit type and gate access data help you separate student-driven rentals from other summer move-ins.
What are the common mistakes and edge cases?
The most common mistake is changing the window dates between years.
A second mistake is using a unit-type subset as the denominator for physical occupancy. Use total available units so the figure matches the industry definition from Inside Self Storage and stays comparable to national figures.
Edge case: if your facility is near multiple colleges with staggered move-in dates, a single August window may miss a July surge entirely. In that case, run a second window for July and track both.
Edge case: a high MI/MO ratio during the student window can mask a large absolute move-out number. Always check the raw move-out count, not just the ratio, so you know how much coverage you need at the gate and on the phone during the post-rush move-out period.
The SSA 2025 Self Storage Demand Study, cited by TractIQ, reports that the share of U.S. households using self-storage climbed from 8.95% in 2005 to 12.60% in 2024. That long-run growth means student-season demand is arriving into a market with more habitual storage users than a decade ago, which can make it harder to isolate the student cohort from general demand growth. Your year-over-year window comparison is more useful than any single-year snapshot for that reason.
What should you do next?
- Open your management software today and confirm you can filter move-in and move-out transactions by a custom date range.
- Write down your student window start and end dates and save them somewhere you will find them next July.
- Pull last year's management summary report for that same window and record physical occupancy, net move-ins, and MI/MO ratio as your baseline.
- Set a calendar reminder for the last day of this year's window to pull the same three figures.
- Add a column to your spreadsheet for unit type and after-hours inquiry count so you build a fuller picture each year.