ata analytics and AI have transformed how prices are set, including the use of surveillance pricing, or using personal and behavioral data to tailor prices to individual consumers, among the more controversial practices. While not commonly applied in self-storage, the issue is beginning to draw industry attention.
Unlike traditional pricing models based on supply and demand or broad market segmentation, surveillance pricing uses a wide range of data to estimate a consumer’s price sensitivity: browsing history, location, income, credit profiles, and even inferred preferences. Storage operators could potentially use sophisticated software to analyze market conditions, historical leasing data, occupancy, demographic trends, and tenant characteristics like payment history or length of stay to recommend rent and renewal rates.
Some systems can operate across entire portfolios, while others can recommend rents for individual units based on market conditions and tenant demand. For example, if data suggests that a particular renter has limited storage alternatives or is searching in a high-demand area with low unit inventory, the algorithm may recommend a higher rent. Conversely, if a unit has been listed for a long period, the system may suggest lowering the price to attract tenants.
From a business perspective, surveillance pricing offers clear advantages. It enables property owners to maximize revenue, aligning rent levels with market demand and reducing reliance on manual pricing decisions that can be inconsistent or influenced by subjective judgment. Automation can also improve operational efficiency; by continuously adjusting prices in real time, these systems can help maintain occupancy while increasing revenue.
Despite these advantages, surveillance pricing has sparked pushback because it operates behind the scenes. This lack of visibility can erode trust and make it difficult for tenants to understand or challenge pricing decisions. It also requires collecting and analyzing personal data, sometimes from sources tenants haven’t consented to.
Policymakers at all levels are beginning to examine whether existing laws adequately address these practices, and some jurisdictions have proposed or enacted measures to curb perceived abuses. In New York, the Governor has required rental agreements to state: “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.” While the requirement is not specific to self-storage, any operators using surveillance pricing in New York should consider including a similar disclosure on their websites and rental agreements.
Surveillance pricing sits at the intersection of innovation and regulation. It reflects a broader trend toward data-driven decision-making that can improve efficiency and market responsiveness, yet it raises fundamental questions about privacy, fairness, and the appropriate limits of technology.