Introduction to Consumer Complexity
Welcome, creators, strategists, and marketers, as we delve into the enigmatic world of consumer behaviour- an elusive quest that challenges even the savviest among us.
If you’ve found yourself scratching your head, wondering why your one-size-fits-all strategy for wooing Gen Z ends up fitting none, welcome to the club- the “We Thought We Knew Our Customers” club. Many words are used to describe Gen Z, fickle, demanding, and entitled but the simple fact is, that once you dive into the wild world of customer segmentation, you soon come to realise that not all 23-year-olds love avocado toast and TikTok dances. Shocking, I know.
Once upon a time, we thought we had it all figured out, then entered Gen Z, the group as mysterious as Bigfoot but twice as influential on market trends. The twist? Treating Gen Z as a monolith is about as effective as using a flip phone to take a selfie. Spoiler alert: It doesn’t work. And then there’s Gen Alpha, trotting right behind, born with an iPhone in one hand and environmental concerns in the other. Forget digital natives; these kids are digital overlords, reshaping our strategies before they’re even out of nappies.
Our journey starts with an epiphany: Segmentation is not just about demographics; it’s about psychographics, geographics, behaviouristics, and any other “ics” you can think of. It turns out, personalisation is not just a buzzword; but a golden ticket to consumers’ hearts- and wallets. So, how do we crack this nut? By acknowledging that the 20-year-old university student and the 23-year-old young professional might both enjoy coffee, but their reasons, preferences, and purchasing power are as different as night and espresso.
Navigating the complex world of consumer motivation and segmentation, especially within the vibrant tapestry of Gen Z and Gen Alpha, is akin to embarking on an exploration where the map pin keeps moving. The quest to connect with these groups has led many businesses down a path of broad generalisations, a strategy which more often that not misses the mark. The real challenge though, lies not in pinpointing exactly what these younger audiences want, but in understanding the diverse life stages, financial freedoms, and motivations that shape their actions and decisions.
At the heart of effective segmentation is the realisation that even within a single generation like 'Z', there's a spectrum of individuals ranging from those entering their teenage years to young adults navigating the early stages of their careers. These varying life points come with distinct levels of financial independence, access to resources, and social pressures, painting a picture far more complex than a one-size-fits-all demographic label could ever capture.
Personas and Archetypes: Tools for Deeper Insights
When delving deeper, the conversation around segmentation often brings us to the comparison between personas and archetypes. With their detailed breakdown of a character's attributes, personas offer detailed insights into your audience's lifestyle and routines at a given moment in time. However, archetypes are more agnostic, tapping into prevalent motivations and preferences that drive consumer actions and consumer inconsistency. This nuanced understanding allows for flexibility in messaging and product development, ensuring relevance across changing timelines and trends. You can read more about persona and archetype differentiations in my other article.
Beauty brands have been balancing this macro/micro lens this for ages- “Tell us your age, skin type, concerns, values and how you feel today” and voilà, a personalised skincare routine is generated accompanied by cross and upsell strategies. Meanwhile, the banking sector often greets us with the enthusiasm of a government tax form. Imagine if, upon visiting a bank’s website, you were met with a friendly quiz that ends with, “Based on your answers, here’s how to become a financial wizard.” Revolutionary? Absolutely!
Unfortunately- and without generalising, based on my particular experience of working with incumbent banks this rarely happens. Either because they lack the mechanisms to surface and collect enough ‘mindset’ data, or because their experiences are not tailored enough for different audiences to spot niche needs. For those who're a little distant from the world of experience design, here's a basic framework for segmenting a customer base that most businesses will likely use, even banks! For demonstration purposes, I'll continue with the financial theme for now.
Segmentation by region
The country, region, state, city, neighbourhood, and postal code.
Segmentation by demographics
Age, gender, income level, occupation, education level, marital status, family status, dependents.
Segmentation by psychographics
Personality traits (e.g., risk-averse, adventurous, ambitious), lifestyle preferences (e.g., health-conscious, tech-savvy, environmentally conscious), values and beliefs (e.g., socially responsible, financially conservative), interests and hobbies.
Segmentation by behaviour
Transaction history, product use and loyalty, channel preferences (e.g., online, mobile, in-branch) and frequency of interaction.
Segmentation by mindset
Financial goals (e.g., saving for retirement, building wealth, managing debt), financial attitudes (e.g., risk-averse, growth-oriented, cautious), financial literacy, confidence and decision-making styles.
By layering these different segmentation criteria, and continually filtering a customer base, a bank could create increasingly granular and targeted customer groups such as:
💹 Wealth-building millennials living in urban areas who are tech-savvy and affluent.
👛 Suburban retirees who are risk-averse and financially conservative.
🤑 Ambitious, career-focused young professionals living in city centres who prioritise convenience and short-term goals.
This level of detailed segmentation allows businesses to develop highly specific customer profiles and personalised strategies catering to the unique needs, preferences, and mindsets of individual target groups.
As we gaze into our crystal balls (or, more accurately, our analytics tools), it’s clear that the future of customer segmentation will continue to be highly dependant on predictive AI models, that gage the constantly evolving needs of dynamic consumer groups and guesstimate their churn rates and lifetime value. But in the end, the brands that master the art of segmentation and personalisation won’t be those that simply capture market share, or segment their customer base comprehensively, it will be those that win hearts, switch up the conversation and create connections that endure beyond the latest trends.
Practical Applications
Netflix's customer segmentation strategy is a stellar example of using deep data analytics to deliver highly personalised experiences that resonate with diverse audiences, of all ages. Netflix's customer segmentation strategy is a stellar example of using deep data analytics to deliver highly personalised experiences that resonate with diverse audiences, of all ages. By allowing subscribers to create multiple profiles under one account, Netflix gains insight into different household members or groups of connected individuals. This feature is crucial as it enables Netflix to understand viewing habits and preferences at more granular levels.
Each profile collects specific data such as favoured genres, actors, viewing frequency, device and watch location, as well as the type of content that engages users enough to watch completely, rewatch and extend viewership beyond a single episode or season. This helps tailor content recommendations for different viewers and viewing contexts—whether it's a family movie night or an individual's late-night binge.
Moreover, Netflix's segmentation sophistication extends to the subtle interactions users have with the platform. From the choice of avatars that reflect their personalities or moods to viewers' use of subtitles and language settings, each choice provides insights into users' preferences and accessibility needs. The platform's rating system is another smart mechanic. A thumbs up, thumbs down feature allows users to express their 'love', 'like' or 'dislike' directly after watching a series or film, which Netflix incorporates into its predictive models to improve browsing experiences for users and connected groups. Additionally, by tracking trailer plays versus full views, Netflix can gauge preliminary interest versus committed watching behaviours.
All these comprehensive data points allow Netflix to not only keep existing content aligned with users’ preferences but also guide the development of new content that meets the nuanced tastes of its global audience. This strategically ensures Netflix remains at the forefront of content personalisation, enhancing user’s satisfaction and loyalty, whilst ultimately keeping them engaged and subscribed in the long term.
However, understanding different user groups and contexts is only part of the equation. The real magic happens when entire organisations- from marketing to product development, customer support to data science come together to harmonise insights they’re individually collecting. This cross-departmental collaboration isn't just beneficial; it's essential for creating innovative segmentation strategies. It ensures that every touchpoint with the customer is informed by a deep and shared understanding of who they are, what they want, how they interact and what they value.
Here’s where many strategies falter: in the rush to attract consumers, especially those quick to sign up, businesses often overlook the importance of sustained engagement. The allure of capturing attention with a trendy ad or a flashy offer might bring in the numbers, but without a strategy focused on collective sustained engagement, these relationships often lack depth and staying power.
Experience-contributing departments should strive to establish shared goals, KPIs, and regular cross-functional meetings in order to gain a rounded perspective on specific target groups. For instance, quarterly voice-of-the-customer reviews can bring together marketing, sales, product development and customer support teams to analyse customer feedback and adjust engagement strategies accordingly. Open-attendance product usability test sessions focused on refining product experiences not only benefit from product manager, designer, and developer inputs but also from front-line support centre worker observations. Some hyper-consumer-centric companies even organise annual planning retreats to refine long-term brand, product and service goals.
Harnessing Insights for Market Success
So, what's the path forward? It involves a continuous cycle of listening, learning, and iterating. It means not only attracting a wide array of consumers, but also keeping them engaged over time by recognising that behind every data point, trend, and purchase there's a person looking for a meaningful connection. A toast to all the strategists and innovators who dare to delve deep into the intricate web of customer profiling. May your data be insightful, your segmentation be precise, and your personalisation be so spot-on, that you make your customers wonder whether you've been reading their minds.
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