For decades, credit unions and other financial institutions have known when, where, and what to market and cross-sell to their members based on life stages. Even before data analytics could tell them exactly what each one of their members was looking for, financial institutions could look at a member, estimate their age, and determine based on that what products and services they might need following the general life stages of a member: going to college, graduating, getting a job, getting married, buying a house, having a baby, saving for retirement, and retiring.
Financial institutions often assume these life stages happen in this order, with a few exceptions, so they can estimate a member’s life stage and needs based on their age. A teenager, for example, probably won’t be shopping for a home loan anytime soon, but they might be in need of their first checking account or a decent credit card with a small limit to start building credit. It would also be a great time to talk to them about student loans and what you offer. On the other hand, a young couple might be in need of a home loan or a savings account to save for a wedding, a baby, or a trip.
The recipe for success, therefore, was easy; step one: figure out a member’s current life stage, step two: offer the corresponding products, step three: profit.
Life stages are becoming less orderly and less defined
But some argue that tracking the life stages (especially when those stages are assumed based on age) of a member is now both unnecessary and often incorrect. First, with current data mining options and analytics possibilities, credit unions don’t need to guess what a member is looking for, they can track purchases, spending patterns, and more to determine what their members are in need of and what products would suit them best.
Furthermore, age tends to be less of an indicator than it once was, and many people are straying away from typical life stages. Young couples are often not as quick to buy homes (especially in the current market) or have children due to either a lack of funds or career goals. With an average savings amount of only $5,000, millennials in particular are less eager or able to do so. In fact, according to a study done by SoFi and Modern Fertility, 60% of women surveyed stated they were delaying childbearing due to finances while 3 out of 5 noted they were delaying starting a family until they reached a certain point in their career.
As for buying a house, nearly 70% of millennials, according to a 2019 study from the rental platform Apartment List, say they cannot afford a house due to rising prices. That number increased to 77% by 2022. Therefore, an age group financial institutions might have once labeled as house-hunting, baby-having members, are more likely to spend their funds on education, travel, or big-budget purchases. This means that seeing a member in their 20s or 30s and offering a home loan might not be the slam dunk it once was, especially when credit unions could probably gain more insight and more accurately pinpoint a member’s needs with data analytics.
This applies to other life stages as well. Many are delaying retirement (or retiring much younger than planned), and older students (25+) are making up increasingly larger portions of college campuses. Life stages are trading places, blending together, or ceasing to exist at all. Considering all this, many financial institutions are wondering if life stages—even when tracked via data—are worth the effort anymore. If any member could need any product at any time, is trying to guess their needs based on an assumed life stage at all effective?
Is there a need for life stages still?
There’s no easy answer to this question, unfortunately. At the end of the day, I’d argue there are a few reasons to not do away with them quite yet. After all, while there might be shifts in when people hit certain life stages (if they ever do), the change is not so drastic as to render life stages useless. They have a time, place, and purpose.
Life stage tracking can be effective in widespread marketing campaigns in which credit unions are looking to draw in as many people as possible with a wide net. After all, while they may not be the most accurate of indicators, they can still be a safe bet. Targeting younger members with ads on first-time homebuyer loans or middle-aged members with retirement account options will most likely still bring in a fair amount of interest. Although, such campaigns would probably do even better if created using data to determine which members—based on spending habits, transactions, and account status—would fit with the product being marketed. But if credit unions lack the time, manpower, or funds to do so, life-stage marketing will do the job.
For their part, credit unions seem to be sticking with life stages. On a quick search, I found several credit union sites that offered a life stages page, where they distinctly broke up their products into said stages and offered further information for members. While this approach might be satisfactory, it leaves little to no wiggle room for those members not operating within those limits or hitting different stages at different times.
For instance, one credit union’s “career-oriented” life stage was only advertised to those who were recently graduated, had gotten their first job, and were establishing credit. It provided information on how to open credit cards and tips for getting a good credit score. It offered no resources for older members who may be well into a successful career looking at potential business loans, investment options, etc., or for those delaying other life stages to establish strong savings and build retirement, as based on the title, I incorrectly assumed it would. The sections immediately following were (as you might have guessed) building a wedding fund, buying a house, and planning for parenthood.
Alternatively, track lifestyles, not stages
There are absolutely missed marketing and sales opportunities by operating in such rigid and inflexible stages. Instead of trying to fit members into one box, consider alternative methods to assess member needs. With current data possibilities, there’s no reason to limit what stages a member can be in and when. One such method would be to track lifestyles instead of stages, as one data analytics company, Segmint, recommends.
Dividing your member base into lifestyles offers more flexibility and specificity to determine member needs, along with creating more personalized and targeted marketing opportunities. Credit unions can use Key Lifestyle Indicators (KLIs) to determine which categories each member belongs to, and there’s no limit to the amount of KLIs one member could have, as opposed to life stage tracking, which places members into one clear-cut bracket. Some examples of KLIs are checking account holder, homeowner, competitive credit card user, having a child in college, traveler, has a competitive mortgage, small business owner, or home improver.
By taking advantage of this data, credit unions can compile detailed and accurate pictures of each member’s lifestyle and in turn, their needs. Instead of sending out widespread marketing campaigns to those you assume fit into a certain stage based on age, use KLIs to send targeted campaigns, like offering small business loans to every member tagged as a small business owner. Or offer personal loans to those travelers, home improvers, or big-budget spenders. This may require more work than standard life stages would, but I’d wager that overall, credit unions would be much better off focusing on the data and getting to know their members on a more individual level.
Not useless, but not the best
Life stage tracking has been the bread and butter of financial institutions for decades, and while it may be proving itself to be outdated, financial institutions are unlikely to do away with it altogether. But these clear-cut life stages are limiting to members and, therefore, limiting to your credit union in terms of what you can offer members, when you can offer it, and how successful that endeavor will be.
In the end, only credit unions can determine if life stage tracking is worth it for them. But while these defined stages may stick around a while longer, credit unions would do well to begin exploring what data analytics tools are available to them and how they might utilize such data to create individualized experiences for their members, along with developing much more effective and beneficial methods for marketing and selling. Both the credit union and its members will be better off for it.
