You have 60 climate controlled 3m x 3m units at your self-storage facility and five are vacant. Yesterday, your nearest competitor, 1.5 km away, decreased its monthly rate on its climate controlled 3m x 3m units by $9. Your units are now $4 per month more expensive than your nearest competitor. Do you adjust your monthly rate or leave it where it is?
Taking a more systematic approach to pricing has enabled companies across a variety of industries to obtain revenue and profitability increases that are typically much greater than initially expected. Although it may seem counterintuitive, given the proliferation of many small companies in the self-storage industry, systematic, state-of-the-art pricing capabilities are now beginning to be within the reach of many self-storage firms, not just the largest ones. Within the United States, such capabilities appear to be yielding revenue improvements from 4 to 10 percent, or more. Importantly, these revenue increases do not simply result from increasing prices; indeed, frequently the prices of some units increase while others decrease. Knowing when to raise or lower prices is certainly a good first step, but this alone is not enough to comprise a revenue management strategy. As we shall highlight, designing your pricing structure to be responsive to customer preferences, both stated and those that only become apparent when the customer is at the store – is also critical towards obtaining maximum benefits.
Clearly, understanding what “to do” to obtain the benefits of improved pricing is valuable. What may not be quite as obvious, however, is that there is also significant value in having a better understanding of what “not to do,” so the pitfalls that have frustrated other self storage firms in their pricing efforts can be avoided. Let’s discuss both the good and the bad associated with three aspects of pricing:
1) Starting rates
2) Move-in concessions
3) Modifying the rental rates of existing customers
Before doing so, however, a quick note on distribution channels. The use of the web to post prices and accept reservations for self storage units appears to be a more common business practice in the United States than in Australasia. While our lack of experience with the Australasia market makes it premature for us to make any recommendations in this area, we can say that the firms in the United States that make it easiest for customers to obtain prices and make reservations via the web have reaped great financial benefits from these capabilities. We expect the same could be true for Australasia – if it is, the early movers in these areas could be big winners if their web functionality is designed and communicated correctly.
To better understand what we have found works well, we highlight approaches that have met with mixed success to show why we have taken a different approach to starting rate pricing analytics in the self-storage industry.
Compared to businesses where revenue management has generally been applied, the storage industry does not offer a good environment to forecast demand with a high degree of accuracy. A typical store might have 30 – 40 move-ins per month, divided up among a number of different unit types and sizes. Not only are the markets for each store relatively small, they often exhibit distinct local characteristics. We have found that the transaction volume at each store is generally much lower than what has proved suitable and desirable to leverage standard forecasting techniques for pricing analytics and revenue management.
Consequently, self-storage firms using transaction-based demand forecasts as the primary basis for their starting rate pricing analytics can obtain volatile results. The underlying mathematical models supporting such approaches tend to require a higher degree of “care and feeding;” in addition, if the business environment changes, the models may not adapt as well as desired.
Another approach that has met with mixed success has been leveraging Rules-Based pricing capabilities offered by some Property Management Systems (PMS). These approaches allow self-storage firms to specify the business conditions that produce price changes. For example, an operator might specify that rates for climate controlled, 3m x 3m units should increase by 10 percent when the unit occupancy increases to 85% and by 5 percent more when unit occupancy exceeds 95 percent. At first glance, this may seem quite reasonable; but when one starts considering competitor rates, seasonality (e.g., higher prices might be supported as the weather gets warmer), the total number of units (e.g., occupancy percentage can imply very different vacancy levels when there is a total of 5, 25, or 100 units), and other factors that can lead to rule adjustments, effectively managing such rules can turn out to be quite a challenge and can consume significant investments of time and effort.
Consequently, we prefer a different approach. We advocate starting with the question, “Is my monthly start rate for unit type X at the right level?” This naturally leads to answering a variety of questions including:
- Do I need to lower my rate to receive additional inquiries?
- 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 the prices of my competitors?
- Is my availability sufficiently limited that I should increase my rate because I will not have any vacancies in this unit type?
- Do I anticipate receiving a lot of inquiries in the near future that I should pro-actively increase rates now?
- Has the occupancy level of this unit type been increasing or decreasing recently?
Such questions lead, rather naturally, to a review of current conditions and an incremental pricing strategy, whereby rates are gradually adjusted. These adjustments, either up or down, are made in response to observed, as well as anticipated, changes in the business environment. Further, the pricing adjustments are made in response to changes in a variety of business-related concerns. In our experience, decision support software based on such a dynamic, multiple signal approach is more easily managed than specifying and adjusting static rules. In addition, since this approach considers a broad range of factors, but can also translate these factors into an overall measure of pricing pressure, it can make a price change recommendations that are more easily evaluated and/or implemented.
Further, it is able to provide important insight about the local market. Finally, it also tends to yield a far more intuitive approach than relying on complex mathematical formulas that are difficult to adjust, as the reasons for the pricing recommendations are easily understood. For example, consider a unit type that is only 55% utilized, but which is priced competitively, has a very high closing rate, and is more highly utilized than a month ago – lowering the rate on this unit type simply because the utilization rate is low may lead to less, not more, revenue; unless, the lowered rate will stimulate sufficient incremental inquiries and move-ins beyond what would have otherwise occurred. Without a systematic way to think about such issues, an operator’s intuition on whether to raise, lower, or keep the current price, is more likely to be wrong.
Beyond adjusting starting rates, we have also found that many self storage customers are more “service sensitive” than “price sensitive” when renting self storage units. Interestingly, their lack of experience with, and knowledge about self-storage makes it difficult to capitalize on this until these customers arrive at the store. For example, visually seeing the need to move a sofa through three hallways with a few turns, rather than having a straight route, may well be the information that a customer needs to decide that it is worth spending $10 more per month for a unit that is more easily accessed. Providing customers with a range of options, in which more conveniently located and available units are priced slightly higher than the available unit that has the lowest price and is the least convenient, has proven to be a very effective way of increasing revenues.
Some self-storage companies have implemented such programs using static unit assignments – that is, specific units have been associated with premium prices. A more successful approach, however, allows for dynamically pricing units and changing the prices of units relative to those that are available. Successfully implementing such a program, including ensuring that store managers appropriately and effectively communicate the choices available to a customer, typically requires changes in both store-level business processes as well as in IT systems. But when done right, revenue increases of 4 – 7 percent appear attainable from this initiative alone; such revenue increases are sufficiently large as to have led some operators to make the required investments and they are benefiting handsomely.
Warren is President of Veritec Solutions, a pricing and revenue management consultancy. He began his career 20 years ago with American Airlines. Warren is an internationally recognised revenue management and pricing expert, especially in business environments where revenue management techniques have not been traditionally applied. For more information visit: www.VeritecSolutions.com