Revenue Management

Revenue Management Takes the Guess Work out of Setting Prices

by Ahmet Kuyumcu

Self-storage operators face many challenges to ensure profitability, and no process is more foundational than the method an operator uses to make pricing decisions.

Many self-storage businesses performed extremely well after the recession. New supply was slow to come into the market, and demographic and economic growth created storage demand that helped operators capture both rates and occupancies.

However, since 2014, self-storage development has seen significant growth, and the acceleration of new supply entering the marketplace is increasing pricing pressures. Continuing shifts in market conditions can have major impacts that affect your bottom line in ensuing years. To address your pricing challenges, traditional manual and rule-based pricing processes will not be sufficient.

Fortunately, the digital age has taken much of the guess work out of determining the right price for the right product at the right time. Automated revenue management systems enable operators of all sizes to generate optimal price points to make use of every square foot of a facility space to maximize revenues.

Not understanding the totality of the market, including customer move-in and move-out forecasts, occupancy rates, competition, changing demographics, what products your customers are seeking, customer lifetime value, rates you offer, etc., can cost you substantial revenue.

The good news is that revenue management systems aren’t just for the big players in the industry. Any self-storage operator, regardless of whether they run one or one hundred stores, can’t afford not to invest in a revenue management system. Many operators don’t realize that a few move-ins per store will cover the cost of a good system.

Moving in to the Digital Age

Many storage operators rely on “old school” pricing techniques, using current or past occupancy levels as triggers to set prices. In addition, many operators often apply the same rate changes across the board even though the demand mix varies over time.

Some operators don’t take into consideration their competition, while others beat the pavement using traditional mystery shopping techniques to find out what their competition is doing at any given time. This approach stretches available staff thin.

As a result, informed price changes don’t occur nearly as often as they should. Some of the bigger operators change pricing daily and others change their pricing more than once a day. All these “traditional” pricing approaches are reactive and do not account for key factors such as predicted customer demand (both move-ins and move-outs), thereby leaving many opportunities for revenue enhancement on the table.

The world is heading towards digitalization; artificial intelligence and machine-learning algorithms are adding millions to the bottom line of large corporations.

To be an effective competitor in a sometimes-saturated market, you have to be armed with the right technological tools to usher the self-storage industry into the digital age.

The Pricing Challenge

The pricing challenge for operators can be partitioned into five main parts:

  • The self-storage business is highly seasonal with close to 40-percent more rentals in the peak month of May than the slowest month of December. Move-outs are equally seasonal, peaking in August and slowing to the lowest point in February. Demand can also shift quickly throughout the year, based on competition and external micro-economic variables.
  • Competition also plays a key role in your pricing. Often, operators don’t know how to cope with the new competitor opening down the street, or when too many or not enough rentals are observed in their stores.
  • Operators are often guessing rather than knowing what promotions to offer when and how to balance those promotions with expected length of stay (which in itself is highly volatile and hard to predict).
  • Each self-storage product delivers a different value to customers based on unit size, location and attribute, and rents must be aligned accordingly.
  • Existing customer rates must be optimally adjusted to the right frequency considering customer move-out sensitivity as a function of rent increase amount, expected lifetime value of a customer, and demand and occupancy forecasts.

Individually, these challenges can be overwhelming for operators using traditional methods and oftentimes, miss the mark. The facility not only fails to maintain at least a 90 percent occupancy; it fails to meet revenue and profit projections.

Revenue management systems take the guess work out of all these challenges.

For example, in dealing with seasonality, a good revenue management system will consider all the factors that play into your local market. In most markets, April, relatively, has a lower occupancy, and pricing based on occupancy alone will tend to underprice units. A manager may even be tempted to give price concessions during this month to drive up occupancy. A good revenue management system may not allow this to happen and may instead forecast the busy summer season by raising rents earlier.

Conversely, in August, when occupancy is high, many companies overprice their units. Depending on the move-out forecasts, a revenue management system may consider dropping unit prices earlier.

Choosing a Good Revenue Management System

There are several revenue management systems on the market for the self-storage industry. It is critical that you find the one that best fits your company. Many revenue management applications are judgmental and rule-based. For example, being ignorant of competition is very dangerous. However, it is almost as dangerous to follow a pure copy-cat strategy, whereby every price you set is reaction to the marketplace. Many systems blindly follow or use rule-based weighting schemes for competitive price response. This strategy is risky, since it often entails delegating the price-setting responsibility to competitors.

Automating user judgements is not the kind of smart pricing that maximizes revenue. If your judgement is wrong and you automate it, you are making wrong decisions efficiently, but not affecting your bottom line positively.

Competitive prices and promotions should be used as input to setting optimum rents after estimating competitive impact to own customer demand. In some situations, ignoring competitive prices might be the right answer. In other cases, you should go half-way or match them.

Your revenue management system should have a core algorithm that adapts to your local market conditions and evaluates different business scenarios, the worst to the best cases. In business, if you want to maximize your revenue, you’ve got to forecast demand at different price points. The system must look forward, understand the overall market signals, predict move-ins and move-outs, and measure customer price sensitivities so that when the prices change, you know what the customer will do. If these factors aren’t a part of your core algorithms, you’re not going to maximize revenue.

Here are some other things to look for when choosing a revenue management system:

  •  Learn all you can about the revenue management system and the company. Can the company provide testimonials or name clients that are currently using the system successfully? What type of an ROI in revenue increases can be expected when using the system?
  • What is the accuracy of their move-in and move-out forecasting? Is the system forward-looking or rule-based?
  •  What factors do they consider for existing customer rate changes? Do they estimate what customers would do if they raise rates? Do they consider customer lifetime value?
  •  Do they consider impact of discounts and promotions?
  •  Do they consider channel pricing? How do they differentiate between web prices and walk-ins?
  •  How easy is it to use and maintain the system? How much configuration is needed and who does it?
  •  Finally, choose a system that provides good customers service and technical support to help answer your pricing questions.

Ahmet Kuyumcu, Ph.D. is cofounder and CEO of Prorize

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