Reforecasting self-storage revenue after a rent-increase campaign

The initial case opens at 92.8% unit occupancy and 92.7% square-foot occupancy. It carries the operator's scheduled increases into in-place rent and assumes that move-outs are replaced during the same 90-day period. Rental revenue reaches $4.550 million after vacancy, promotions, delinquency and the spread between in-place rents and current asking rates.

The observed case does not apply a general occupancy haircut. It replaces the assumed campaign response with the tenant-level outcomes already recorded: 468 tenants remain in their units, 88 transfer, 128 move out and 74 new tenants move in. The revised roll-forward ends at 90.3% unit occupancy and 89.4% square-foot occupancy.

Gross potential rent at current asking rates is actually $80,000 higher in the revised case. That increase is outweighed by the occupied-square-foot loss, move-in promotions, delinquency and the loss of above-street in-place rents on vacated units. Year 1 NOI falls by $350,000.

The rate-increase file identifies 684 tenants, their prior rent, scheduled increase and effective date. That cohort is matched to subsequent move-out and transfer records rather than inferred from two rent-roll snapshots. A transfer remains an occupied tenant but changes the unit, square feet, rent and insurance charge attached to the account.

The initial case expects 616 tenants to remain, 28 to transfer and 40 to leave. The observed response is materially different: 468 remain in their current units, 88 transfer and 128 leave. The 74 replacement move-ins offset part of the count loss, but 51 receive a first-month promotion and enter at the current move-in rate rather than the departed tenant's rent.

The timing also matters. A tenant billed at the new rate for twelve days before moving out has not accepted the increase for the forecast period. The model records the higher rent through the move-out date, the vacancy interval, the replacement rent at move-in and the promotion as it is earned. It does not annualize the highest monthly billing run.

Unit occupancy alone understates the change. The portfolio loses 54 occupied units, or 250 basis points of unit occupancy. It loses 7,780 occupied square feet, or 330 basis points of square-foot occupancy. Tenants are moving out of large climate-controlled and drive-up units, while part of the refill occurs in smaller promoted units.

Transfers require the same treatment. The old unit stops contributing rent on its transfer date; the new unit begins at the transferred rent and fee schedule. Treating all 88 transfers as retained rent would preserve the tenant count while overstating occupied square feet and monthly revenue.

The unit-type roll-forward also controls the refill assumption. A vacant 10-by-30 drive-up unit is not filled by demand for a 5-by-5 climate-controlled unit. Asking rates, lead volume, promotions and days vacant are applied to the inventory actually available in each category.

Gross potential rent is rebuilt from the current asking rate for each unit type and the months that inventory is available. It rises from $4.780 million to $4.860 million. Vacancy and unavailable-unit loss increases by $165,000 because the observed move-outs are not replaced on the initial schedule.

Promotions and concessions increase by $70,000. Delinquency, credits and bad debt increase by $35,000. The initial case also contains $160,000 from the favorable spread between scheduled in-place rents and current asking rates. That spread disappears as higher-rent tenants leave or transfer and their former units refill at advertised move-in rates.

Tenant insurance, administration and other revenue is tied to occupied accounts rather than held at the initial margin. It falls by $50,000. Operating expenses decline by the same amount because some card fees, insurance costs and property-level labor flex, while property taxes, security, utilities and most payroll remain in place. Year 1 NOI falls from $3.290 million to $2.940 million.

At the $42 million purchase price, the initial NOI produces a 7.83% going-in yield. The $25.2 million loan is constrained by 60% LTV and opens at a 13.06% debt yield, above the 12.5% minimum.

The observed NOI produces a 7.00% yield. At 60% LTV, debt yield falls to 11.67%. The debt-yield constraint sizes proceeds at $23.520 million, $1.680 million below the initial case. Required purchase-price equity increases from $16.800 million to $18.480 million.

The operating response is not limited to a single downside. The next increase can be staggered by tenure and spread to street rate. Large vacant units can be repriced to recover occupancy while current in-place rents remain unchanged. The operator can also continue the current increase policy and carry the observed move-out rate into the remaining eligible tenants. Each case has a different achieved-rent and debt result.

Cap Orbit can work across the dated rent rolls, tenant ledger, rate-increase campaign, customer notices, unit inventory, move-in and move-out activity, transfer records, web rates, promotions, insurance and fee reports, debt quote and existing acquisition workbook in the same deal. Each campaign tenant can be matched to the unit and billing history that follows the notice.

From there, you can have Cap Orbit rebuild occupied units and square feet by day, distinguish a transfer from a retained unit, apply promotions over their actual term and reconcile posted rates to achieved rental revenue. The revised operating case carries through ancillary revenue, property expenses, NOI, debt yield, proceeds and equity in the existing model.

The same deal record supports the operating treatments that matter here: lower move-in rates on large vacant units, staggered increases by tenure, a revised promotion schedule or another campaign at the observed response rate. Each case returns the same connected outputs—tenant retention, transfer activity, unit and square-foot occupancy, achieved rent, NOI, debt and equity.

That is the standard for AI on this asset class. The useful result is not a summary of asking-rate growth. It is an acquisition case in which every rate notice, tenant response, vacant day, promotion and unit transfer resolves into achieved revenue and the capital required to own the portfolio.