The power of big data is about understanding patterns of consumer behavior and profiles, particularly information around “life events” such as marriage, divorce, job change and births. Having this data enables you to advertise to prospective clients when these events happen. While you could pay to get this information, some of it you can get on your own without paying a dime. All you have to do is look at your own neighborhood and what’s happening with people and homes there.

Big data No. 1 — Buyer profiles

This might seem a bit invasive, but it’s powerful in a good way. To improve the response rate on your marketing campaigns, figure out who is buying homes in your market. Demographic data is useless for this, as it’s too general and way out of date. To create buyer profiles in a neighborhood, make a list of all the buyers for homes in your neighborhood.

Once you have that list, use these free online resources to get details on those buyers:

  • — full name, age, past employers, education, relatives (gives you insight into who they are more than most sites).
  • — age and relatives.
  • — valid phone numbers (not blocked).
  • — full address and phone.
  • Advanced background checks — verify relationships and other addresses.
  • — full address and phone numbers.
  • — Get info on LLC and other business owners.
  • — Enter {full name + city + “email address”} and look in cached results.

Two of the most valuable big data elements you’ll get are profiles of the industries buyers are coming from (tech, finance, etc.) and family composition.

What you can do with the industry profile knowledge is target your advertising to people who work in those industries in the surrounding area (via print ads) or online. Facebook, Twitter and others all have user profile information related to the industry they work in. That will make your buyer ads more effective because you’re targeting people who buy in your neighborhood.

You can use the family composition data to extrapolate potential candidates for major life events. For example, a single person who bought a condo at a particular age could wed and upgrade their home. You’ll have to gather enough data on buyers in the area to figure out what ages are most commonly associated with certain events (marriage, birth, etc.). You can then target appropriate marketing campaigns to each group.

Big Data No. 2 — Average length of ownership

You can determine the average length of ownership, even broken down by age of home, by looking at past sales in the MLS. To do this, just look at all sales in the past year or so in your neighborhood. Make note of the transaction history and calculate the age in months between the last two transactions. Add up all the months and divide by the number of sales to get the average length in months. Then divide by 12 to get the length in years. Now you can look at any homes NOT sold in the area where the last sale was near that average and you’ve got potential sellers!

If you have the age of the houses being sold, you can organize (simple sort is fine) to see if there is a trend on homes of a certain age. You can also sort by address to see if certain streets or neighborhoods tend to have shorter or longer ownership periods.

The value of this information is in knowing which homeowners are more likely to sell when they’re within six to 12 months of the average. It’s not a guaranteed listing, but it certainly increases your chances.

Big Data No. 3 — Recent births

Take a look at your local paper for recent birth announcements. You can also find this information online at some hospital websites. Gathering a list of recent births gives you parent names, which can be used to find out who they are and where they live.

  • Find new births.
  • Verify family composition.
  • Check on house type/size.
  • Small house + big family = candidate to move.

Once you know where they live, look at the type of home they live in. Using the same sites used to create the buyer profiles, you can find out more about who they are and get a family profile.

If they currently rent, they may be candidates to become first-time homebuyers. If they live in a condo or townhouse, they may be a candidate to upgrade (which means a listing and a purchase). There may be other combinations you’ll need to consider based on your market.

What do you do with all this?

That’s easy — big data is all about refining your marketing. It helps create more opportunities at less cost with faster results. It helps you understand your prospective clients better. It helps you understand the market better. Investing time in this research will pay off in a lot of ways that will make you a better agent overall.

Bryan is the co-founder and managing broker of Catarra Real Estate, a real estate services company that provides highly personalized services to each client.

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