Last week, I shared an NAA Education Conference-inspired blog about not seeing our prospects as commodities, realizing that some prospects are inherently better than others, such  as those who stay at our community longer, pay rent on time, and treat their neighbors with respect.  In a perfect scenario, we would take the "pick of the litter", snagging the absolute best prospects first, and leaving the less-than-ideal prospects for our comps, all while strictly adhering to Fair Housing laws.  The challenge, of course, is to find this information and act on it, by either targeting certain demographics or increasing acceptance criteria to weed out negative prospects.  But the benefit is enormous by finding residents who stay longer, pay rent online, and have the potential to truly fall in love with your community! 

There are countless ways to improve your mix of residents.  In the preparation of this blog, I was able to identify six targeting/screening options, but you will surely find more as you dig deeper.

NOTE:  By attempting to do any targeting as I mention below, it is extremely important to understand Fair Housing laws.  I am not advocating targeting by (or against) any protected class - these suggestions are to encourage targeting for other factors, such as if someone is fitness oriented or a dog lover.  But also be careful to not discriminate unintentionally.  For example, would targeting hockey fans be a problem considering 92% of fans are white?  Consider those implications before implementing.

1) Overall demographic targeting.  This is where you find demographics that have beneficial attributes as residents.  For example, if you found that teachers were more likely to stay longer at a specific location, that would be valuable.  Or maybe you find that those that play intramural sports tend to refer more friends.

2) Individual targeting.  This one is a bit more complicated, as it means finding specific people who are looking for apartments, and seeing if they fit certain criteria in order to target them.  This process must be equally used in all cases and in writing so that accidental Fair Housing violations are eliminated.  Social media data mining would be the plan on this front, analyzing the person before reaching out to them.

3) Enhanced resident referral programs, as discussed in my prior blog. 

4) Enhanced screening criteria.  If someone comes in to lease an apartment outside of your targeting, you still want to maximize your chances of accepting someone who has beneficial qualities.  (NOTE:  These screening criteria must be used consistently for all prospects.)  So consider analyzing your past resident data to identify potential red flags, such as a comparison of your screening criteria relative to the number of skips, how long they stayed at your community, and if they paid late.  For example, you might find that if someone has changed jobs within the past X months/years, they were X% more likely to leave after one year.

5) Finding the perfect match.  For communities that are more niche oriented or have some element that is differentiated, those particular amenities and traits will be better suited for some prospects compared to others.  For example, let's say your community has a "culture" of being highly social and focused on social gatherings.  This type of community would not be conducive to someone who values quiet and their privacy.  Filling an apartment with a quiet resident would gain you money, but it would also take your sanity as they issue noise complaints and complain to office staff.   So actively targeting those who are more social will help ensure that a higher percentage of your prospects are those that have a chance to fall in love with the community, which means they are likely to stay longer and form emotional connections with other residents, both favorite attributes.

6) Smarter outreach marketing.  This is somewhat addressed in number one above, but also handles the reverse side of the argument.  For example, if you have a preferred employer program that includes a company with extremely high employee turnover, or a company that transfers its employees often, you may be inadvertently targeting a lower value resident, as those residents are more likely to leave your community earlier.

The growth of Fair Housing laws has had some negative repercussions on the apartment industry, in that it has led communities to take on a "one size fits all" approach.  In my opinion, this is an overreaction to Fair Housing laws and hurts everybody involved.  It hurts the residents as they are surrounded by others that do not have similar interests and lifestyles, as well as hurts the ability to make friends, as residents are constantly moving.  It hurts the apartment communities by creating a stale social environment where residents leave due to few emotional ties.  By doing more advanced targeting, however, you have the ability to reach fantastic residents who will make your community healthier and more profitable.