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Mail Smarter: Using Demographic Data to Your Advantage

Posted by Brian Berg Google+



Marketers spend a great deal of time creating consumer mailing lists of ideal targets for direct mail marketing messages to ensure that their mail piece ends up in the hands of a relevant audience, but how do they capture the right leads?  This week we start a new blog series entitled “Mail Smarter”.  For the next three weeks, we will take an in-depth look at how consumer mailing lists are complied and how marketers can use list selects to their advantage when creating a targeted direct mail campaign. 

The first step of the consumer mailing list selection process involves taking a look at your current database of customers as well as your trade area.  Does your trade area population include more homeowners or renters?  Baby Boomers, Gen-Xers, or Millenials?  Which ethnic groups are represented in the population?  If they are home owners, how likely are they to purchase home furnishings, renovate their homes, or spend leisure-time landscaping their yards?

To analyze market opportunities for your business, you need to examine data and ask questions like the above about residents of your trade area.  This data must include the absolute number of residents, as well as their household characteristics.  Current and projected demographic, lifestyle and consumer spending data about your trade area from secondary sources can provide this information.

It is well understood that product preferences vary across different groups of consumers.  These preferences relate directly to consumer demographic characteristics, such as household type, income, age, and ethnicity.   For this reason, it is not only the amount of demand that truly matters to a local economy.   The mix of consumers also has a major impact on a local economy, and therefore must be thoroughly examined when selecting a consumer mailing list. 

The following provides a starting point in your understanding and interpretation of demographic data in relative to retail spending.

  • Population and households data allow you to quantify the current market size and extrapolate future growth.  Population is defined as all persons living in a geographic area.  Households consist of one or more persons who live together in the same housing unit; regardless of their relationship to each other (this includes all occupied housing units).  Households can be categorized by size, composition, or their stage in the family life cycle.  Typically, demand is generated by the individual or the household as a group.   So, the entire family influences a household purchase, such as a computer or TV.  Individual purchases, on the other hand, are personal to the consumer.  
  • Household income data is a good indicator of residents’ spending power.  Household income positively correlates with retail expenditures in many product categories.  When evaluating a market, retailers  look at the median or average household income in a trade area and will  seek a minimum number of households within a certain income range before establishing a business or setting prices.  Another common practice is to analyze the distribution of household incomes. Discount stores may avoid extremely high or low-income areas.  Some specialty fashion stores target incomes above $100,000.  A few store categories, such as auto parts, are more commonly found in areas with lower household incomes
  • Age is an important factor to consider because personal expenditures change as individuals grow older.  One important stage of life, and a category that’s growing as baby boomers age, is the 65 and older group.  Realizing and catering to the needs of an aging population can be beneficial to any retailer.  Consumer spending on drug stores and assisted care services flourish in areas with a large elderly population.  Accordingly, drug stores often do well in communities with a larger number of people over the age of 65.  In general, though, older populations tend to spend less on the majority of goods and services.  Studies indicate that nightlife and entertainment spending (restaurants, bars, and theaters) by people over 65 is roughly half that spent by those under 65.  Older adults also spend considerably less on apparel than other age groups.  On the other end of the spectrum, toy stores, day care centers, and stores with baby care items do well in areas with many children and infants.  Clothing stores and fast food establishments also thrive in areas with a high adolescent population.  Some entertainment and recreational venues, such as movie theatres and golf courses, serve a broad section of the population.  Others, such as water parks or arcades, target certain age groups.
  • Education levels also figure into the socio-economic status of an area.  Because income increases with advancing educational attainment, many retailers focus on income level rather than education.  There are some exceptions to this, though.  Bookstores are often cited by developers as a business whose success is directly correlated with the number of college educated individuals in the trade area.  Similarly, computer and software stores are often located in areas with high levels of education.  In general, areas with high levels of educational attainment tend to prefer “the finer things.”  That is, they may have a preference for shopping at smaller, non-chain specialty retail stores located in their downtowns.  They also tend to visit cultural establishments like museums and theaters at a frequency over three times greater than those without a college degree.    On the other hand, less-educated populations generally have lower incomes and thus tend to prefer shopping at discount retail outlets and chain stores.  This group also spends more money on car maintenance and tobacco products than those with a college degree.
  • Occupational concentrations of white and blue-collar workers are used as another gauge of a market’s taste preferences.  Specialty apparel stores thrive in middle to upper income areas and those with above-average white-collar employment levels.  Second-hand clothing stores and used car dealerships are successful in areas with a higher concentration of blue-collar workers. Office supply stores and large music and video stores are especially sensitive to the occupational profile.  These retailers target growth areas with a majority of white-collar workers.
  • Ethnicity is another factor retailers consider when choosing merchandise to carry.  Data show that ethnicity affects spending habits as much as other demographic characteristics, such as income and age.  Tastes in goods and services vary between ethnic groups, and local retailers are wise to cater to the different needs of ethnic groups in their trade area.  Ethnicity influences retailers’ product mix, including the lines of clothing they carry, and their advertising.  Retailers that use segmentation based on race and ethnic groups must make sure their efforts effectively measure the true preferences and behaviors of the community.
  • Housing ownership and rate of housing turnover is an important factor for numerous retailers to consider.  Home ownership directly correlates with expenditures for home furnishings and home equipment.  Furniture, appliances, hardware, paint/wallpaper, floor covering, garden centers and other home improvement products all prosper in active housing markets.

No matter the type of customer you cater to BB Direct has a consumer mailing list that will meet your direct marketing needs.  Our consumer data base allows for multitudes of demographic, lifestyle and interest based consumer mailing lists to be generated that will allow you to effectively reach out to your best prospects.  Contact an expert member of our data team at (866) 501-6273 for more information.