The Current, delivered daily.
Marketers have always used “buyer personas” or, more recently, “avatars,” to pinpoint and describe their ideal target audience. Buyer personas and avatars can get very detailed, from the consumer’s name, age and income level down to their hair color, hobbies, career and the biggest challenges they face in life.
On the other hand, CARLY and HENRY are broader descriptions of a specific target audience. In spite of their gendered names, they can describe any type of consumer as long as they fall into a broad demographic based on age and income level. While their interests, pain points, and geographic region may vary, those belonging to the HENRY segment share enough in common that marketers can use specific tools and tactics to reach them. The same goes for those in the CARLY segment.
For further context, CARLY and HENRY follow in the line of DINKs (Double Income, No Kids), and the Yuppies (Young Urban Professionals) of the 1990s. Much like those cohorts at that time, CARLY and HENRY are key to knowing your respective target audience and reaching them effectively.
Any brand seeking to reach Gen Z in particular and future proof their business in general needs to know the nuances of CARLYs and how to speak their language, especially if they want to engage with this next generation of consumers as they come into their own and eventually start using their own funds for purchases. The same goes for HENRYs, who shouldn’t be overlooked. They make up approximately 40% of all consumer spending, and are especially key for luxury brands, which they have a penchant for purchasing. Let's take a closer look.
So, who are CARLY and HENRY?
CARLY, as coined by the marketing automation company Klaviyo and the media firm Future Commerce, stands for “Can’t Afford Real-Life Yet.” These Gen Z consumers range from age 18 to 25 and if they are spending money, it’s not a lot — yet. Based on Statista figures, shoppers in the US ranging from age 18 to 24 years old make up only 13% of all digital buyers.
But this demographic is brand-savvy and aware, so it’s important to reach them now and begin building brand recognition and loyalty. The day is not far off when CARLY consumers will graduate college and have money of their own to spend. For now, they are spending their parents’ money with fervor, but only on brands that make a positive impact and match their ideals.
HENRY, on the other hand, is the consummate millennial or young Gen Xer, ranging in age from mid-30s to roughly 45. As first detailed in a 2003 Fortune Magazine article, HENRY stands for “High Earner Not Rich Yet.” Members of this market segment — of any gender — earn more than $100,000 yet have investable assets less than $1 million. They make more money than roughly 66% of the U.S. population in 2022, according to statistics from Zippia, but despite remarks during the ‘08 presidential election and the cost of living, are not yet classified as “the wealthy elite.”
Marketers once considered HENRYs as part of the aspirational luxury market, but these individuals do more than just aspire to wealth; they have figured out how to enjoy the finer things in life without virtually limitless income. A Deloitte report discovered that the average HENRY household spends $86,000 annually on luxury goods, including travel, clothing, accessories, and entertainment.
Something more about CARLY
Although CARLYs don’t have a lot of their own money to spend yet, these consumers are savvy shoppers, and they do influence the purchases of their parents and older family members. They are also highly influenced by TikTok trends, Instagram influencers, and their peers. Gen Z is the most digitally savvy, socially skeptical, community-oriented, and nostalgia-driven market segment. It’s not unusual to see them sporting Crocs, Converse, or a Care Bears hoodie, unironically embracing the childhoods of their Gen X parents. But they are also not brand snobs; quality and value is more important than the brand on any product.
CARLY is not superficial. This market segment believes in diversity, sustainability, and social change. To win their hearts and digital wallets — perhaps forever — and build long term customer loyalty, brands should not just pay lip service to these ideals, but make them part of their brand DNA.
What you should know about HENRY
HENRY consumers have more in common with their high net worth older brothers than you might imagine. HENRY will research every purchase online and rely on reviews and the recommendations of peer groups before making a purchase.
HENRY also shares traits in common with CARLY. The market segment is also socially conscious and sustainable — and they have the funds to support their beliefs through their buying choices. Both HENRY and CARLY seek out experiences over “stuff,” and rely on their tribes as a second family.
How HENRY and CARLY differ
Despite their similarities, HENRY and CARLY are also very different in their buying habits. Remember, HENRY has money to spend on luxury goods, while CARLY has less disposable income. CARLY wants products that will last and may defy conventional fashion or what’s popular among older generations. Names don’t matter as much as value and finding brands that align with their ideals. HENRY still cares about prestige, but also wants to know they are getting good value for their money.
Ecommerce tactics to capture HENRY and CARLY
When it comes to online marketing, the way you approach these audiences may differ. Personalization through the use of big data and artificial intelligence algorithms, however, will be a key in reaching both market segments.
From deep product tagging for ecommerce clothing sites to retargeting through Google Ads, it’s important to show these consumers that you know what they are looking for — sometimes even before they do. This level of hyper-personalization will appeal to the HENRY market segment, but it’s an expectation of Gen Z.
Personalization in email marketing to attract HENRY
Email marketing remains a viable tool, especially for millennials and Gen X who tap into their email consistently for work, shopping and entertainment. While millennials increasingly rely on chat platforms like WhatsApp, Messenger, Slack and Telegram, email remains a staple of life for high earners in a business setting. Personalizing an email with not just a person’s name but specific information based on the reader’s past purchase history, demographics, and psychographics can increase click-thru rates by 14%, and conversion rates by six times.
Other examples of personalization in email marketing include:
- Abandoned cart follow-ups
- Product recommendations
- Discounts based on past purchases
Social shopping links to attract CARLY
Although email works for some demographics, younger generations are moving toward other ways to connect with their favorite brands. SMS, for instance, can yield 7.5 times the amount of clicks as an email. Don’t shy away from emojis or GIFs in your texts, either – this, too, can increase engagement and conversions.
Above all else, CARLY consumers want their personalized shopping experience to be easy. Shopping links in Instagram posts and on TikTok deliver exactly what this generation wants: convenience, personalization and the ability to snag whatever catches their eye quickly. TikTok trends have sent CARLY flocking to retail stores to buy everything from Mini Brands collectibles to orange juice and strawberry-adorned dresses. But the joy is not in the hunt. If these consumers can click a link to get what they want quickly, easily, at a fair price and without the environmental impact of a trip to the mall, they will embrace that experience.
What’s next for the top target audiences?
From Yuppies to DINKs, CARLY and HENRY are merely the next incarnation of market segments for retailers. As buying habits have shifted to ecommerce, retailers face new challenges in attracting the most influential demographics.
Understanding what’s important to CARLY and HENRY — and then implementing the right marketing tactics to meet their needs — can be the key to your success.
Ashley Scorpio is the Senior Vice President, Partnerships at Hawke Media. A former Chief Marketing Officer, with over a dozen years of experience in traditional and digital marketing, she is a performance marketing leader that has helped launch and scale digitally native brands. She is nationally-recognized as an 'Amazing Woman in eCommerce’ by Ecommerce Magazine and Yotpo.
Trending in Marketing
Constructor's Eli Finkelshteyn shares principles for responsible use of generative AI, and an experiment.
This is an article about how to approach the use of ChatGPT for improved ecommerce experiences without breaking shopper trust in the process. You probably aren’t expecting Jurassic Park references, but I’m going to make one anyway.
There’s a line of foreshadowing early on where Jeff Goldblum’s character speaks about the complexities and ethics involved in cloning dinosaurs. He says something to the effect of, “Everyone got so excited that they could that they never even stopped to consider if they should.”
ChatGPT, and transformers in general (the technology underlying ChatGPT and a lot of the newer software that’s emerging in the search and discovery world) are incredibly exciting. One of the most exciting parts is how easy it is to build something with ChatGPT, and we’re currently seeing a glut of new software that does just that. Still, what isn’t clear is how to leverage this technology in ways that aren’t just gimmicks, but are actually helpful to people.
It’s clear to just about everyone that we’re in a hype cycle, and that’s why it’s so important for new technology being marketed as “powered by ChatGPT” or “powered by transformers” to prove its business value and usefulness to end users. Not to mix blockbuster movie references, but with great computing power comes great responsibility.
So it’s a good time to ask the multibillion-dollar question: how can technology companies use ChatGPT responsibly and in ways that actually benefit people in the months and years to come?
We’ve adopted some overarching principles internally at Constructor that will serve as our north star as we continue to innovate in this space. As we came up with them, we realized they could be useful as best practices for technology companies in general, and especially those like us who are serving large e-commerce companies. As more and more ecommerce leaders across B2B and B2C evaluate AI solutions in the middle of a hype cycle, we think it’s especially important to publish our principles publicly.
Our hope is that if we stick to these principles, then we’ll maintain our customers’ trust while innovating on new technology, and we’ll do this while doing the right thing for shoppers as well.
1. Experimentation is a prerequisite for ROI
Lots of companies can release a cool-looking new product and make claims about its efficacy, but it’s important for all of us to recognize that we’re early in our understanding of what applications of ChatGPT are genuinely useful to humans, and which are just science projects.
Why? Because the vast majority of those results are still unproven.
With ecommerce technology, for example, it’s important to consider whether a technology partner is going to actually deliver a product that has a legitimate impact on revenue or user happiness. Succeeding at that is ultimately a manifestation of extensive experimentation, including testing, failure, iteration, and re-testing — over and over again. Like most good things, data science takes time. It’s complex, and it’s nuanced.
Why is this so important for all of us in ecommerce tech to recognize? Because if we release a bunch of gimmicky technology and promise it’s the next big thing, then when we do come up with something useful, no one is going to trust us anymore.
The critical takeaway here is that any breathless proselytizing about most ChatGPT-based tech at this stage is counterproductive and simply not honest. If a vendor says they know for certain where the gold is right now, it’s just very unlikely to be true.
That’s the critical difference between a culture of experimentation versus one that’s only interested in shipping the “new hotness,” no matter the results. Before a product goes to market, the company that created it needs to be able to explain, and ideally prove, how it will bring ROI.
Is it just a novelty, or will it — in our case as an ecommerce product discovery company — actually help shoppers discover more products they want to buy in a way that’s more convenient, more natural, or more delightful than what they already have? And how do we know?
At Constructor, we’re excited to be experimenting with ChatGPT and large language models and transformers, both internally and with willing customers. We’re excited about the experiments we’re doing, and we hope the customers testing them are too, but we also want to be very clear that these are still just experiments. I’m providing a sneak peek at one experiment we’re very excited about below, but please read on before watching it:
Because here’s what we’re not doing: we’re not claiming we’ve invented the best thing ever. We’re not promising 10000% ROI. This is an experiment we’re excited about, but there is a real possibility that it doesn’t work out.Taking risks is what innovation looks like. The difference is that at the end of the day, our charter is to create real value (and ideally revenue) for our customers — and we won’t sell them a product that delivers anything less.
2. ChatGPT for ecommerce should be trained on ecommerce data and built for the needs of ecommerce
Ecommerce is full of unique problems and use cases for the ways people find products and content. For example, an add-to-cart and a purchase are both “conversions,” but they’re very much not the same type of conversion. Software that’s built for ecommerce has to understand the distinction, because it’s incredibly important to the KPIs that B2C and B2B ecommerce companies care about.
That’s the primary reason that we built Constructor’s AI core from scratch — the keyword-matching and vector search algorithms that work for general document search just aren’t the best technology to apply to ecommerce product discovery where you have rich feedback from users via their clickstream, along with zero party data like answers in a product-finding quiz. And the same principles apply when we apply ChatGPT to ecommerce.
The idea here is, let’s not try to boil the ocean. We don’t need to create Artificial General Intelligence that can answer every type of human query. We just need to create a very specific form of Artificial Intelligence that does one thing (helping shoppers discover products they’ll love, in our case) very, very well.
In order to return the most personalized, attractive results to a shopper’s query, ChatGPT needs to be augmented with AI models trained on ecommerce-specific data like clickstream behavior, average order values, margins, and product attributes. What’s really exciting here is that it’s the underlying technology itself that has the potential to completely reshape ecommerce. At Constructor, for example, we are working on using transformers to provide better product retrieval and filter out irrelevant results in search queries. It’s possible that this work may have the greatest impact on customer revenue, even more than the “conversational commerce” element of ChatGPT. But we don’t know yet — that’s why we’re experimenting.
(Image courtesy of Constructor)
Another advantage to training transformers on ecommerce data is that it also might mitigate some of the public concerns around ChatGPT’s accuracy. We only surface products for shoppers based on their own zero-party data and an ecommerce company’s own catalog. This heavily limits the types of wrong answers the system can give, and is about as accurate (and effective) as you can get. You may not be able to ask the ChatGPT solution at your favorite retailer about the year Albert Einstein was born, but it will be much better equipped to help you find a shirt you’ll love, or that one snack you tried and enjoyed, but can’t remember the name of. That’s a sacrifice I think most companies will be willing to make.
3. ChatGPT should build — not erode — your customer relationships
We’ll be releasing the full results in the next few months, but our team at Constructor recently performed a survey of 400+ U.S. online shoppers. We found that more than half of them were at least somewhat hesitant about using ChatGPT to find products on websites.
In our current landscape of third-party cookies and data breaches, that response is understandable. And ChatGPT could trigger a similar backlash if it makes shopping uncomfortable or intimidating. New tech can be scary, and it’s a fair concern that you might not want to ask your grocery store to create a shopping list of your regular purchases if it automatically adds sensitive items like gas relief medicine without asking you first.
We don’t have all the answers yet (as a company, an industry, or even a society) for how we’re going to solve these problems. Some of it, especially in this experimental phase, will be creating more transparency for the shopper. Expedia is an example of a company approaching this the right way, in my opinion. They recently launched a ChatGPT interface, and they’re very open about it being experimental and not trying to “trick” customers into using it. It’s a small but important step in building customer trust and delivering the value that leads to long-term relationships.
(Image courtesy of Constructor)
Questions will come up as we break new ground here. They’re important to talk and think about, and that work is the shared responsibility of retailers and the partners they work with. Ecommerce companies and their technology partners coming together to consider these murky waters — and being willing to think through new solutions to put customers first — will be absolutely critical.
A balanced approach
The amount of excitement and buzz around the (virtual) water cooler here at Constructor when it comes to ChatGPT can’t be overstated. Speed to market is a noble pursuit in this agile, volatile economy, and we are experimenting every day to figure out which of our ideas with ChatGPT and transformers will bring customer value and which require rethinking.
But we also want to balance that excitement with humility. When ChatGPT and transformers are raising legitimate questions from consumers, from companies, and even from others in the AI community, moving forward carefully and intentionally is equally important.
In this retail tech arms race, it’s the companies who widely release technology that doesn’t help their customers that have the most to lose. Ultimately, AI shouldn’t exist just for AI’s sake. Artificial Intelligence needs to yield real value if the companies using it want to be valued by their customers. We hope that our customers have come to trust us for doing right by them and their shoppers, but recognize that trust is something we have to constantly earn and maintain. My hope is these principles will help us and the wider technology ecosystem do exactly that as we embark on this next exciting adventure in AI.
Eli Finkelshteyn is co-founder and CEO of Constructor, an AI-powered product search and discovery platform tailor-made for ecommerce. This piece originally appeared on Constructor's blog, and was reprinted with permission.