The intragenerational dynamics of Millennials

Monday and yesterday, I argued that many of the so-called Millennial attributes aren’t unique to Millennials and, in fact, that the dynamics among generations are overblown.

I should stipulate here that it seems obvious that people who have significant events at formative times in their lives may have similar reactions.  Those who lived through the Great Depression were more likely to save as a result.  Similarly, many from this generation don’t like to have extended long-distance phone calls because they used to be very expensive.

Ironically, for me, it’s this belief in formative events that makes me less likely to buy into generational dynamics.  It seems odd to me that for whom 9/11 happened while in college will likely think the same way about security issues on average than someone for whom 9/11 happened while in utero.  Further, to say that their reactions would be preordained seems even more implausible.

All of this could be excused, perhaps, if it led to a usable schema.  After all, if something works in practice but not in theory, it simply begs for better theory.

However, looking at Millennials and saying they act one way or the other as a group is not reliable.  In fact, it would likely be better to look at any other factor than age to get an idea of a person.

This sounds controversial, but let’s take this chart as an example.  While a sdt-next-america-03-07-2014-0-13simple example, President Obama’s appeal among younger voters was a significant part of the narrative in the 2008 election.  

As you can see, white Millennial’s approval rating of President Obama is between white Gen Xers and white Boomers.  Non-white Millennial approval is slightly higher than non-white Boomers, but within the margin of error.

So if you wanted to predict whether someone supports President Obama, it would be far more instructive to know someone’s race than their age.  Or, put another way, a 25-year-old white person is more likely to be like a 65-year-old white person than a 25-year-old non-white person.

Let’s look at more actionable variables for us as direct marketers.  One thing we do know for sure is that Millennials own social media, right?

Right?

Sort of.  They use social media more than other age groups.  However, 11% have no Facebook accounts and 27% use it less than once per week.  And that’s the most used social network.

And, not a surprise, it’s not the same by sex:

sillsgraphic1 Hat tip here 

And there’s significant age variation within Millennials.  About a quarter (27%) of 31-35 year olds use Snapchat, compared with almost two-thirds (65%) of 21-25 year olds.  I should mention that some of the more enlightened generational theorists of my acquaintance talk about how people on the border of generational categories are tweeners and these are spectra, rather than hard dividing lines.  This warms my heart in part because I’m an Xer and my wife is a Millennial despite only a two-year age gap.

This is something for-profit marketers have caught on to.  The Hotwire PR study of communications trends proclaimed the end of trying to talk to Millennials as a monolithic group and more toward addressable media and direct marketing (including print!) to address as individuals.

So the big question I would have is why would you want a strategy for Millennials, when you could have strategies to acquire online advocates as warm leads, renew lapsed donors, and everything else that is actually related to your organization.  I think you’ll find that your walkers look very much like your walkers, your advocates like your advocates, and so on, than your Millennials like your Millennials.

This brings up another question: is it worthwhile to target far younger constituents as a way to get gifts?  My answer is no, with caveats, and I’ll hit the details tomorrow.

Agree?  Disagree?  Let me know in the comments.

The intragenerational dynamics of Millennials

2 thoughts on “The intragenerational dynamics of Millennials

  1. Nick,

    I’ve enjoyed this set of generational posts and your prior ones as well. The generational myth-busting is well articulated and supported and consistent with the more fundamental “miss” by the charity sector (more so than for profit) and that is getting at root cause, the why of behavior.

    Demographics are rarely causal of anything – save for true life-stage products (e.g. baby food) and even then, it is merely defining as in-market or not but giving zero guidance on brand preference and choice, etc…

    This same problem plays out when Charity X slices and dices their file a million ways and low and behold, finds differences, missing the reality of this being a foregone conclusion. The issue is compounded by then appending a bunch of external data and low and behold the differences and interesting (but dangerously irrelevant) bar charts exponentially increase.

    It is over-used and trite but correlation is not causation and this misunderstood fact combined with former being rampantly abundant makes rabbit holes and chasing down them a real problem.

    I’d argue the segmenting by standard and admittedly more business relevant segments like “lapsed” or “online advocates” is only better by comparison to nonsense like generation. But, for the sector to see real growth (bottom line, bigger impact on respective causes) the slicing and dicing needs to be more root cause.

    One example is identity and determining which one is motivating giving – e.g. connection to disease for health charity, connection to community for local/regional charity. Some additional thoughts on this are here, http://www.thedonorvoice.com/want-a-good-donor-experience-and-better-retention-start-with-understanding-donor-identity/.

    At any rate, really good content. Thanks for it.

    Kevin

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  2. Thanks, Kevin. That’s an interesting post linked to that I’d recommend readers check out. and some thought provoking comments.

    There’s a great Latin phrase “ceteris paribus” and it roughly means all other things being equal. (I’ve studied no Latin; my wife, who has, tried to explain all of the nuances of it to me, but when she started talking about the ablative case of a noun, I was done).

    So, ceteris paribus, a Millennial is more likely to engage a non-profit online than a Civic. And ceteris paribus, a Civic is more likely to engage a non-profit through the mail than a Millennial.

    But what we’re both saying is having this as the primary segmentation point is unwise, given there are ones that offer far more information like “have they given before”, “what content are they interested in”, and probably most importantly as you say “why are they giving”. We have to consider, ceteris paribus, what that first line segmentation and customization is going to be. RFM is the default, but it’s a blunt instrument with which to be slicing, since donors don’t think of themselves as a lapsed $30-49.99 multi crosschannel donor. They think of themselves as donating for a reason and like when that reason is played back to them (in the second-person, as you say).

    I would say that some charities are getting better about this. I’ve had the privilege of seeing MADD have cause connection as one of the primary questions for walk registration and customize the communications and experience to that “why.”

    Next week, I’m going to talk a bit about donor intelligence, but the upshot is that there are two ways to get it — to ask for it or to determine it. Ask seems better for things that are or are not without middle ground: you are or are not walking for ACS because you lost a loved one to cancer. It does not seem to do as well when people are being asked what their future self would do or react to, because we know that all future selves are far more charitable and upright than our present self. My future self will not eat that piece of angel food cake, is as rich as Bill Gates and looks like a Hemsworth. My present self is as a rich as that angel food cake and looks like Bill Gates.

    Determined attribution — guessing from what a person as done or modeling for what they will do — is OK as an initial tool (e.g., you don’t need to be a Bayesian to think that someone taking an action alert makes them, ceteris paribus, more likely to take another action alert and donate to activism). But that donor will remain forever a black box where you send in inputs, get your outputs, and do your best to figure out what’s inside.

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