By Warren Lieberman
Will reducing the price of your 10-by-10 storage units increase the number of move-ins you receive this month and lead to an increase in revenue and profit, or will you get the same number of move-ins and simply make less money?
Will increasing the monthly rental rate of a current customer by $12 instead of $8 result in that customer moving out more quickly, or will you receive an additional $4 a month from that customer without affecting the amount of time he rents with you?
How well are you able to answer these and other questions relating to your self-storage pricing decisions?
Taking a systematic, data-driven approach to pricing has enabled companies across a variety of industries to increase their revenue and profit. Now these state-of-the-art pricing capabilities are coming within reach of many self-storage businesses, and not just the largest ones. In the United States, such tools appear to be yielding revenue improvements of as much as 4 percent to 10 percent, and even more for some operators.
Combining data-driven pricing with innovative distribution methods and the appropriate organizational structure to execute pricing decisions gives storage operators significant advantages over their competitors. Knowing what to do to reap the benefits of improved pricing is extremely valuable. Let’s discuss three important aspects: start rates, move-in concessions, and rate modifications for existing customers.
Start Rates
Compared to other businesses where pricing analytics have been applied, the storage industry doesn’t have a very good environment for forecasting demand with much accuracy. A typical store might have 30 to 40 move-ins per month, divided among various unit types and sizes. Not only does each facility have a relatively small market, it often exhibits distinct local characteristics. Demand estimates for a specific unit type will often vary by location.
When it comes to setting your facility’s start rates, the accuracy of forecasting models can be limited by data scarcity and variability. The transaction volume at each store is generally much lower than what has proved suitable and desirable for pricing analytics and revenue management. Further, the underlying mathematical models tend to require a high degree of support—attention from staff as well as statistical knowledge that may not be readily available. Finally, if the business environment changes, the models may not adapt well. Consequently, self-storage companies that rely on demand forecasts to determine their start rates get mixed results.
Another approach with varied success is the use of rules-based pricing capabilities like those offered in some management-software systems. This approach allows a facility operator to specify the business conditions that produce price changes. For example, he might stipulate that rates for climate-controlled, 10-by-10 units increase by 8 percent when occupancy reaches 85 percent, and by another 5 percent when occupancy exceeds 95 percent.
At first glance, this may seem reasonable. However, when you start changing these parameters by seasonality, store location, total number of units and other factors, effectively managing and updating these rules becomes quite challenging and can take significant time and effort.
Here’s a different approach. Start with the question, “Is my monthly start rate for unit-type X at the right level?” This leads to other questions:
- Do I need to lower my rate to receive additional inquiries or move-ins?
- Is my closing rate (i.e., my ability to turn inquiries into move-ins) satisfactory?
- Am I losing too much business to my competitors? How should my price compare to theirs?
- Is my inventory in a particular unit type low enough that I should increase the rate?
- Do I anticipate a seasonal increase in inquiries in the near future (e.g., from college students)? If so, should I proactively increase rates now even though I have many units available?
- Has the occupancy level of this unit type been increasing or decreasing recently?
- How long has it been since I changed my rate? Have I given the market enough time to react? If I made a recent change, have market or competitive conditions fluctuated sufficiently that another modification is appropriate?
These questions naturally lead to a review of current conditions and an incremental pricing strategy through which rates are adjusted gradually. These increases or decreases are made in response to observed and anticipated changes in the business environment. Modeling an array of business factors and providing recommendations on how to adjust prices yields a dynamic, multi-signal approach that’s more easily managed than specifying and adjusting static rules. In addition, giving price analysts access to the conditions that drive price yields a far more intuitive approach than complex mathematical formulas that are difficult to adjust.
Many storage customers are more service-sensitive than price-sensitive. Giving them a range of options in which the more conveniently located units are priced slightly higher has proven to be a very effective way of increasing revenue. Some operators have implemented such programs using static unit assignments—that is, specific units have premium prices. A more successful approach, however, allows for dynamically pricing units based on those that are available. Although this may require a change in store-level business processes and IT systems, revenue increases of 4 percent to 7 percent appear attainable.
Move-In Concessions
It’s not uncommon for 40 percent or more of a store’s customers to rent units for at least a year. When such a high percentage of month-to-month renters are longer-term customers, it’s easy to believe that offering a “free month at move-in,” “50 percent off the first two months” or some other aggressive promotion is an acceptable concession to ensure long-term business. Although it may not be easy to quantify the extent to which rentals are increased by discounts, under certain conditions, it’s giving up revenue unnecessarily. At worst, it may result in replacing profitable, long-term rentals with less desirable ones.
An analysis of historical rental data has allowed us to quantify the extent to which length-of-rent distributions vary based on the type of promotion the customer receives. Knowing the percentage of renters who stay one, two or three months, etc., allows us to estimate the impact of various concessions, especially for highly occupied unit types. This knowledge has led operators to revise their discounting policies and practices.
Rate Modifications for Existing Customers
Some self-storage operators rarely change their rates for existing customers. Others raise rates annually but won’t increase them to more than the current “street” or “market” rate. Providing general guidance on the extent to which rates can be increased is tricky because local conditions can be important in determining the best strategy. While some customers move out shortly after receiving a rate-increase notification, many don’t. When carried out at the right time, increases can create significant incremental revenue.
Market-segmentation analyses suggest that commercial customers are often less sensitive to rate increases than residential tenants. Up to a point, the rate at which customers shorten their length of stay is no different when their rate is increased. Whether that point is 8, 10 or 12 percent, it’s likely to be influenced by local conditions. Customer behavior suggests that increasing rates by relatively small percentages (e.g., less than 5 percent) is frequently the wrong strategy, as it leads to approximately the same number of early move-outs while leaving money on the table from existing customers.
We’ve all heard stories about customers who moved out because of their displeasure with a rate increase, but there are many more customers who accepted the increase or moved out for other reasons. Analyzing or estimating the financial impact of rate increases can be relatively straightforward (if the historical data is available) and extremely valuable. Such insights can drive up several percentage points of additional revenue from existing customers.
By collecting basic pieces of information on lease and store performance, self-storage staff can act selectively on each piece of business. What they frequently lack are structured support tools that could enable them to make better decisions. It’s not easy for managers to evaluate how similar customers have responded to a price increase in the past, and they usually have no tools to understand the potential profitability and risks of future increases. When used well, business-intelligence software, pricing analytics, revenue-management models and decision-support tools that drill down to the individual transaction level can be very profitable.
Take Small Steps
Thinking about systematic, data-driven pricing can be overwhelming, which can easily lead to inaction. But relying primarily on intuition and experience can create a lost revenue opportunity. The potential benefits of systematic pricing are great. Just take small steps. Consider one aspect at a time—website improvements, starting rates, rates increases, etc.—and work on improving your capabilities in that area.
There are many ways to begin. You can use your current staff to develop some basic analytics, subscribe to a service that provides Web-based prices and basic pricing analytics in your market, or leverage the expertise and guidance of pricing consultants. In a year or two, you’ll be looking back and wondering why you didn’t take a more active approach sooner.
Remember, systematic pricing is a journey. Small, incremental steps add up, and so will your revenue and profit.
Warren Lieberman is president of Belmont, Calif.-based Veritec Solutions, which offers a range of consulting services, including pricing analytics, revenue management, sales and operation planning, to self-storage and other industries. For more information, call 650.620.0000; e-mail [email protected]; visit www.veritecsolutions.com.
