The Psychology of Real Estate: Using Psychographic Data to Find a Great Self-Storage Location

Figuring out if a plot of land will work well for self-storage is an inexact science, but there are data tools that can help determine if a property is financially viable based on local customer attitudes, aspirations and other psychological criteria. Welcome to the world of psychographics.

One day, while discussing the self-storage facilities they co-own, Bill and Joe wound up debating why some assets outperform others. They’re interested in developing more properties, but they begin to realize that traditional metrics don’t seem to explain what causes extraordinary performance in some properties over others.

Figuring out if a plot of land will work well for self-storage is an inexact science, but there are data tools that can help determine if a property is financially viable based on local customer attitudes, aspirations and other psychological criteria. Welcome to the world of psychographics.

What the Heck Are Psychographics?

Historically, self-storage developers and operators have relied on feasibility studies to determine where to build and forecast future success. While such a study is helpful in deciding whether a site will be viable, it doesn’t get into the heads of the potential customers within a local market or reveal anything about their buying habits.

A feasibility study typically includes a breakdown of demographics, traffic counts and patterns, competition in the area, market demand for space, and market rents and occupancy. It also provides a recommendation for unit mix, an analysis of amenities and climate-controlled space in the market, a pro forma income analysis, and a go or no-go recommendation. That’s a lot of valuable information, but it lacks a psychographic analysis.

Demographics are comprised of statistical data related to a market’s population, providing insight to the number of people in the area and their ages, family status, level of education and income, as well as housing types, the average age and value of property, and more. In contrast, psychographic data classifies the people within a market according to their attitudes, aspirations and other psychological criteria. While demographics are invaluable in determining the financial feasibility of a site, psychographic data helps differentiate between a good location and a great one.

The key difference is understanding who’s residing within your market besides factual population data at an aggregate level. For one, psychographic data describes the personalities, values, opinions, attitudes, interests and lifestyles of potential customers. Second, the information is available at the household level. It’s possible for demographic information from two areas to be similar, while the psychographics and purchasing patterns within them can be vastly different. A great starting point is to compare the tenants at existing self-storage properties with the population in the area.

Psychographic Profiles

Depending on the data provider, there are 60 to 80 psychographic profiles. In addition to location type (rural vs. urban), these vary based on income, education, socio-economic group, age, children at home, and other factors. Different groups have distinct purchasing and spending preferences, as well as varying political preferences.

A good starting point for existing self-storage operators is to compare tenant information against the psychographic profile types of the area population. You’ll find that certain groups are far more likely to use self-storage than the average household.

To understand how this works, let’s consider five hypothetical psychographic groups and their propensity to rent self-storage:

  • Type A: 500%
  • Type B : 200%
  • Type C : 100%
  • Type D: 50%
  • Type E: 20%

These are just for illustrative purposes. In real-world scenario, there would likely be about 70 profiles. However, the range of 500 percent above average to 20 percent below average is typical of household propensity to use a product or service within a geographic area.

The household with an average propensity to rent self-storage is Type C, with a ratio of 100 percent. Conversely, Type E households are only 20 percent as likely to rent self-storage as the typical household. Being aware of the concentration of psychographic profiles that more likely to rent self-storage provides insight to site selection.

Analyzing Current Tenants

Let's get back to Bill and Joe. To determine why some of their properties outperform others with similar demographic profiles, they hire a consulting firm to evaluate and compare tenants from all 10 of their properties against other households in their areas of business. The firm takes their list of tenants and compiles an index with the tendency for each psychographic profile to rent self-storage vs. the overall population.

Bill and Joe have two properties that are exceptional performers, six that are good performers and two that are laggards. The demographics for all 10 facilities—site quality, visibility, level of competition and traffic counts—are similar. The consultant reports that the two exceptional performers are in areas where there’s an exceptional number of Type A and Type B psychographic profiles. The two laggards are in areas with an above-average number of Type D and Type E profiles. The practical implications of the data make it easy for Bill and Joe to see that when investigating new areas in which to build, it makes sense to look for those with a high concentration of Type A and B households.

Scouting a Great Location

Like many storage operators, Bill and Joe have always started the development process by looking for a prospective site and then getting a feasibility study. Psychographics enable a different approach. The partners ask their consultant to identify geographic areas with high levels of Type A and B households. They can then evaluate the level of competition in those areas, identifying which have an average, above average or below average number of storage facilities. They can begin searching for prospective sites after they’ve identified the locations with above-average levels of households likely to rent self-storage coupled with a low or reasonable level of competition.

Using psychographic data doesn’t negate the value of a feasibility study. After all, one bad deal can offset the benefits of five or even 10 smart real estate investments. A feasibility study is cheap insurance against building a poorly performing property, even if the psychographic profile of the area is excellent.

The use of psychographics is just the latest in a long series of innovations since the inception of self-storage. Though it’s not critical to use psychographics to determine if a site is suitable for a successful project, the insight gleaned can increase your number of exceptional performing facilities and minimize the potential for laggard sites.

Patrick O’Connor is co-author of “Big Data in Real Estate—Be a Millionaire,” and president of EnrichedData.com, a U.S. real estate database that provides data and consulting services. He also owns O’Connor & Associates, a U.S. property-tax appeal firm that offers cost segregation, federal tax reduction and appraisal services. He’s been a business entrepreneur since graduating from Harvard Business School in 1983. For more information, e-mail [email protected].

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