Utilizing Technology: Analytics • Section 7
Other Economic Analyses A valuable analytical tool to compare multiple properties is mea- suring the Economic Gross Rental Income divided by the area oc- cupied at that time. This is basically measuring your efficiency in your operations by seeing how much income you are generating per square foot of occupied space. By watching the trends, you can compare different facilities in-
dependently of what markets they are in or the fact that they get different rental rates. You are comparing how efficient each one is trending in its own market. One important factor to remember is that when you are actively leasing, your efficiency drops while you are offering more discounts and concessions. This is not a bad thing; one really must be looking at how much you are increasing your income per month over the same time periods, and not just the change in efficiency. In the past, we have only been able to measure past leasing
activity to give us some semblance of what the demand is for our products. However, demand is really determined by qualified requests by our potential customers and how well we convert those requests into actual leases. By merging the requests of our prospects into our management software, we can now determine how many units of a certain type and size we shall lease in any particular month. Having your managers at least manually keep and assimilate this information for you can give you an advantage over your competitors. Knowing your monthly demand by including those who are
scheduled to move out, be auctioned or negotiated out, and nor- mal seasonal move-outs, one can calculate the net activity for the month for any given size unit. In turn, determining in advance what your target for vacancy should be at the end of the month, one can then determine the size of the discount or the type of concession that will assist in reaching your target goals. In infill or stabilized markets, demand should stay fairly con-
sistent from year to year with adjustments due mainly to regional and national economic factors. In high growth suburban markets, we should expect demand to increase yearly in proportion to the growth of the population of the market within your radius or mar- ket area until such growth subsides. As consumers become more familiar with the product, de-
mand also increases. Thirty years ago, demand was in high growth areas in the Southwest on the order of two square feet per capita. Now, those same areas now have demands three times that amount. Again, technology helps by being able to instantly purchase demographic studies online.
Data Scraping Of Competitor Rates. The REITs and private firms now automatically record and analyze the competitors’ rates and specials posted upon the internet. This type of “data scraping” allows you to analyze your rates versus those of your competition to determine how you should set both your standard rates and discounts or concession plans. This saves considerable man-hours gathering this information, and it leads to dynamic pricing similar to the airline industry; a facility can change its prices hourly to match its specific needs and increase its income.
These systems can instantly adjust the rates at the site for the managers, at the call-centers for their operators, and on the various websites for the potential customers. It has been said that Public Storage knows within the minute when it starts a new tele- vision marketing campaign in an area by the activity it receives at its call centers. All of these techniques are now leading the indus- try into “three-tier pricing” of each unit type and size. The lowest price is on the Internet; the highest price is for a walk-in at the site; and another price somewhere in between is for the customer who calls into the call center.
The Future Of Analytics What does the future hold for us with the sophisticated data analysis? New “expert-systems” will utilize the knowledge of the experts in the industry to make better decisions on our opera- tions. Many times, by leaving rate increases to managers, there appears to be an inverse relationship between how much the manager likes the tenant to the amount of rent increase the ten- ant will receive. By using thousands of possible combinations of ways of operating, Artificial Intelligence may, in the future, allow us to optimize and thus maximize our incomes by removing this subjectivity. As the computers “take over,” humans will have to wisely determine when enough is enough to protect both our customers’ and employees’ feelings about our rapid adjustments! In the past, we have typically looked at our facilities as if we
were flying over them at 30,000 feet. Discount and concession decisions were made based upon the overall occupancy of the facility, and typically one plan would apply to the entire facility. As management improved, we were then able to get down to the “street level” by looking at the occupancies of individual unit types and sizes. This brought about rate management. Now, how- ever, operators are going to go to the most granular level by look- ing at the individual tenants in each size and type of unit. You probably know a lot about who buys from you—gender,
geographic location, marital status—it’s all part of developing buyer personas. These data points make up the demographics of your personas, help inform your marketing strategy, and paint a picture of who your buyers are. But there’s another component needed to really understand your buyer. What’s their lifestyle like? What are their daily habits or hobbies? What kind of values and opinions do they have? The answers to these questions are the psychographics of your customer base, and you need to know this information to truly understand who’s buying what you’re selling. Demographics explain “who” your buyer is, while psycho-
graphics explain “why” they buy. Knowing what the day in the life of your buyer persona looks like is undoubtedly valuable when creating an integrated marketing strategy. One software is cur- rently using psychographics to identify specific customer groups to market for particular unit types and sizes. For example, nurses or those in the health care industry are four times more likely to rent small, climate-controlled units than other professions. By having specific targeted marketing campaigns, one can eliminate surpluses of vacant units in very specific sizes thus significantly increasing income that has been out of reach for years.
2015 Self-Storage Almanac 85
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