Self-Storage · Underwriting Model
Self-Storage Underwriting Model
How to build a self-storage underwriting model: unit-mix revenue, ECRI cadence, achieved vs. street rate, ancillary income, and management-heavy opex.
Why the underwriting model looks different for self-storage
Self-storage revenue is built by unit-mix tier (size and climate control), not a blended $/SF figure, and the model has to separate achieved (in-place) rate from street/web rate; the two diverge because existing customer rate increases (ECRI) lag new-customer asking rates by design.
ECRI is the primary organic growth driver in a self-storage model, applied on a recurring cadence to tenured tenants rather than as a fixed annual escalation, and it gets modeled alongside the churn it induces, since raising an existing customer's rate too aggressively drives move-outs.
Opex is management-intensive relative to other CRE: facility payroll, revenue-management software, and a third-party management fee (commonly 5–7% of revenue) load the expense line more heavily on a percentage-of-revenue basis than in net-leased asset classes.
The self-storage-specific checklist
- 1
Build the rent roll
Verify: unit- or tenant-level detail with rent, term, recoveries
- 2
Project market rent growth
Verify: submarket-specific; avoid flat nationals assumption
- 3
Model recoveries explicitly
Verify: CAM, tax, insurance broken out, not blended
- 4
Run sensitivity on exit cap
Verify: ±75 bps and stress the downside
- 5
Build debt sizing
Verify: LTV and DSCR constraints both checked
- 6
Compute leveraged IRR and equity multiple
Verify: cash flow to equity, not enterprise
- 7
Build a unit-mix revenue schedule by size and climate-control tier
Verify: modeled revenue reconciles to trailing collections within 2%, not a single blended $/SF assumption
- 8
Model ECRI cadence and magnitude off actual increase-letter history
Verify: increase frequency and average % tied to the facility's ECRI log, not an assumed flat escalation
- 9
Separate achieved rate from web/street rate and quantify the lag
Verify: achieved-to-street ratio computed and benchmarked against comp-set facilities
- 10
Size ancillary income off unit count and attach rate
Verify: insurance and merchandise income calculated as unit count × attach rate × monthly premium, not a % of rental income
- 11
Load management-intensive opex at facility-specific staffing level
Verify: payroll and third-party management fee sized to actual FTE count and fee schedule, not a portfolio-average %
- 12
Stress-test churn sensitivity to ECRI magnitude
Verify: downside case models incremental move-outs against a higher ECRI percentage
Metrics that matter for self-storage
| Metric | Target | Calculation |
|---|---|---|
| Achieved-to-street rate ratio | >85% | achieved (in-place) rent / street (web) rate |
| ECRI capture rate | >90% of eligible tenants | tenants receiving a scheduled increase / tenants eligible for increase, net of incremental churn |
| Ancillary income share of EGI | 8–12% | ancillary income (insurance + merchandise + fees) / effective gross income |
| Occupancy (sq ft) | >92% steady-state | occupied SF / rentable SF |
| Revenue per available SF | >$12/yr economy, >$18/yr climate | gross revenue / rentable SF |
| Tenant insurance attach | >85% | insured tenants / total tenants |
Red flags unique to self-storage
-
Achieved rent assumed to converge to street rate within 12 months with no churn cost
closing the achieved-to-street gap requires raising rates on existing tenants, which drives move-outs, assuming instant convergence with no offsetting vacancy overstates near-term revenue
-
Ancillary income modeled as a flat % of rental income instead of unit-count × attach rate
insurance and merchandise income scale with occupied unit count and program attach rate, not with the rental rate, a %-of-rent shortcut breaks as soon as rates move independently of occupancy
-
ECRI increases modeled with no offsetting churn or vacancy assumption
aggressive rate increases on tenured tenants reliably induce some move-outs, a model that captures the rate gain but not the churn cost overstates net revenue growth
-
ECRI under 6% annual
loose rate management leaves real rent growth on the table
-
Climate-controlled share below 30%
non-climate is commoditized; climate-controlled drives premium pricing
-
Tenant insurance attach rate under 70%
ancillary revenue leak; institutional operators target 85%+
-
Street rate vs. in-place rate gap below 8%
limited mark-to-market upside at renewal
Example — self-storage underwriting model walkthrough
Say the target is a 685-unit, 78,500 net-rentable-SF self-storage facility priced at $12.4M, $158/NRSF. Street (web) rate is $1.52/SF/month; achieved rate across the existing tenant base is $1.34/SF/month, an 88.2% achieved-to-street ratio reflecting the normal ECRI lag on tenured customers. At 89% physical occupancy, effective rental income is 78,500 × 0.89 × $1.34 × 12 = $1,124,371.
Ancillary income is built from unit count, not rental revenue. At a 65% insurance attach rate and $9.50/unit/month, insurance income is $53,300; merchandise and administrative fees add roughly $18,500 more for $69,259 total, or 5.8% of effective gross income of $1,193,630. That's below the 8–12% institutional benchmark; either the attach rate is under-marketed on-site or the ancillary program hasn't been fully implemented.
Opex reflects the management intensity of the asset class: facility payroll ($118,000 for 2.2 FTEs), utilities and repairs ($62,000), marketing ($38,000), property tax ($71,000), insurance ($19,000), and a 6% third-party management fee ($71,618) total $379,618. Year 1 NOI is $814,012, a 6.56% going-in cap rate. Debt at 65% LTV caps proceeds at $8.06M; the 1.30x DSCR test implies a slightly higher $9.49M, so LTV binds. The 6% third-party management fee is modeled off the actual fee schedule and payroll off the 2.2 on-site FTEs, rather than a portfolio-average percentage of revenue.
The value-creation case rests on ECRI. Modeling quarterly rate increases averaging 8% for tenants with 12+ months' tenure (62% of the roster), net of an assumed uptick in churn from the increases, projects 5% annual NOI growth, carrying Year 1 NOI to roughly $1,038,900 by Year 6. Street rate stays the reference point for new move-ins while the achieved-rate base catches up. Because storage cap rates have historically held tighter than other CRE through cycles, the exit cap compresses only 10 bps to 6.66%, producing a terminal value near $15.6M. The entire thesis depends on the ECRI-versus-churn modeling holding up in practice, so the increase-letter history, not an assumed flat escalation, anchors the growth rate.
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Get the template →Questions about self-storage underwriting model
Existing customer rate increases (ECRI) are periodic rate hikes applied to tenants already in place, distinct from the street (web) rate offered to new customers. ECRI is the primary organic revenue growth lever in a self-storage model and should be modeled off the facility's actual increase-letter history, including the churn it typically induces.
Street rate is what a facility charges new customers today; achieved rate is the blended rate actually being collected across the existing tenant base, which lags street rate because ECRI is applied gradually and selectively rather than instantly repricing every tenant to the current market rate.
Ancillary income (tenant insurance, merchandise, and administrative fees) should be built from unit count times attach rate times monthly premium, not as a percentage of rental income, since it scales with occupied units and program participation rather than with the rental rate itself.
Self-storage cash flows have historically shown lower volatility through economic cycles due to short-duration, granular leases and low capital intensity, which has kept institutional exit cap assumptions tighter (smaller spreads over entry) relative to office, retail, or hotel underwriting.
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