When personalizing any marketing communication, it’s easy to default to demographic data. Demographic data is inexpensive and easy to come by, and it’s easy to see how it can be used to increase the relevance of printed and digital pieces. Younger audiences see this message. Older audiences see that one.  People on the East Coast get these products. People on the West Coast get those.

We like to categorize people based on external characteristics that we can readily identify with a number of some kind. Age. Income. Number of children. Credit score. But some categories of products and services cross demographic lines and defy numbers. Products like whole and organic foods, “green” products, and health and fitness. Such categories defy demographic quantification. In these cases, lifestyle data may be more helpful.

For example, if you’re selling running shoes, it makes sense to acquire the names of people who subscribe to running magazines or who have purchased running gear in the past. If you’re selling timeshares, you might want to target people who are frequent travelers or who like to take cruises. In these buckets, you will find people of all ages, genders, and ethnicities, and all walks of life. When it comes to selling hybrid cars, for example, a Millennial in San Francisco may be equally likely to make purchase as a 50-something in Colorado.

One of the challenges with lifestyle targeting is that, within each bucket, there is still tremendous heterogeneity. As a result, you may need to target at multiple levels: lifestyle data first, then demographic data to refine it. For example, as a broad category, “trail runners” cross every demographic. You are as likely to see a 30-something running a 10k as you are a 60-something, but the challenges and motivators are different. The 30-something may be looking to invest in life experiences while being challenged by work-life balance, while the 60-something may be running as a commitment to lifetime wellness while being challenged by the need to protect against injury.

Other examples of demographic-defying lifestyle data include:

• Charitable giving
• Collectibles
• Gourmet Cooking
• Green living
• Home improvement
• Investment
• Pet ownership
• Photography
• Running/jogging
• Self-improvement
• Spectator sports
• Veterans

Start asking yourself what lifestyle buckets your customers might fall into.  Push the boundaries.

If you sell supplies for DIYs, for example, don’t limit yourself to people with lifestyle interests in crafts and home décor. Consider other categories, such as entrepreneurship and small business. Who knows when that passion for building and creating will take off into a full-fledged business! Or which companies might consider carrying a full line of your products to sell to their customers? Or, if you sell trail running gear, consider targeting hard-surface runners, who might never love the additional challenge of leaping rocks and roots or who might appreciate the lower impact of the dirt surface on their joints.

Take the opportunity to brainstorm with your team and explore all of the opportunities. Invest in customer profiling to better understand your customer base and where lifestyle targeting opportunities exist that you might not seen before, then use what you learn to make those customers connections stronger.

I’d like to know . . . what are some of the lifestyles buckets that go together? Where there are buckets where there is crossover and commonality that you have found that you might not have expected?