---
title: Why Demographics Fail
summary: Why age, income, and location never predict purchase behavior, and what psychographic targeting does instead.
est_minutes: 18
sort: 1
---

#### LESSON 1: Why Age, Income, and Location Don't Predict Purchase Behavior

Most businesses build customer profiles that look like this:

"Our target customer is a 35-55 year old professional earning $75,000-$150,000 annually, living in suburban areas with 2-3 children."

This profile feels specific. You can visualize this person. Marketing teams nod in agreement. Everyone moves forward confident they know their customer.

Then they run campaigns targeting this demographic. And the results are mediocre at best.

Why? Because demographics don't predict purchase behavior.

**The Demographic Illusion**

Demographics create an illusion of precision. You have numbers. You have data. It feels scientific.

But here is the problem: **correlation is not causation**.

Yes, your current customers might be 40 years old on average. But that does not mean age caused them to buy. It just means the people who happened to buy from you happened to be 40.

**Example:**

Your SaaS product sells to "companies with 50-200 employees."

You analyze customers. Average company size: 87 employees.

You conclude: "Our ICP is 50-200 employees."

You target companies in this range.

Results: 2% conversion rate.

**Why it failed:**

Company size didn't predict purchase. What predicted purchase was:

- They recently hired a VP of Operations (trigger event)
- They were scaling fast and systems were breaking (pain point)
- They valued efficiency over cost savings (psychographic)
- Previous solution had failed (readiness)

None of these correlate with employee count.

A 45-person company with those characteristics converts at 15%. A 150-person company without them converts at 1%.

**Demographics told you nothing useful.**

**The Three Demographic Lies**

**Lie #1: "Our customers are millennials"**

Millennials are people born between 1981-1996. That is 41 million people in the US alone.

Do all 41 million want your product? No.

Do they all have the same problems? No.

Do they all make decisions the same way? No.

"Millennial" tells you someone's birth year. It tells you nothing about purchase intent.

**What actually matters:**

Not their age, but their life stage and values.

A 32-year-old startup founder and a 32-year-old corporate middle manager are both millennials. They have nothing else in common regarding purchase behavior.

The founder values: Speed, innovation, risk-taking, efficiency. The manager values: Stability, proven solutions, risk mitigation, approval from above.

Same age. Completely different customers.

**Lie #2: "Our customers earn $100K+"**

Income feels like it should predict purchase. Higher income = more money to spend.

But purchase decisions are not about having money. They are about how you prioritize spending that money.

**Example:**

Person A: Earns $120K, drives a 10-year-old Honda, shops at Costco, invests aggressively.

Person B: Earns $120K, drives a new BMW, shops at Whole Foods, carries credit card debt.

Same income. Completely different customers.

Person A will not buy your premium service even though they can afford it. They optimize for value and efficiency.

Person B will buy your premium service even though they probably should not. They optimize for status and convenience.

Income did not predict the purchase. Values and priorities did.

**Lie #3: "Our customers live in major metropolitan areas"**

Location tells you where someone lives. It does not tell you why they would buy.

Yes, cities have more people. So you will have more customers there by sheer volume. But conversion rate? Not predicted by location.

**Example:**

E-commerce company sells premium outdoor gear.

Assumption: Target urban areas (more people, higher income).

Reality: Conversion rate in rural Montana is 3X higher than New York City.

Why? Rural customers actually use the gear. It solves real problems (weather, terrain, lifestyle).

Urban customers might buy it for the aesthetic or weekend trips. Lower intent, higher return rates, worse LTV.

Location didn't predict purchase. Lifestyle and usage patterns did.

**Why Demographics Feel Right But Perform Wrong**

Demographics are popular because they are:

1. **Easy to collect**
   - Age, income, location are on every form
   - Public databases have this data
   - You can buy demographic lists
2. **Easy to understand**
   - No interpretation required
   - "40-year-old" is clear
   - Marketing team can visualize it
3. **Easy to target**
   - Ad platforms offer demographic filters
   - Facebook: Target by age, location, income
   - LinkedIn: Target by job title, company size

But easy does not equal effective.

**The problem:**

Platforms want you to spend money. Broad targeting = more impressions = more spend.

Demographic targeting is broad by design. "Everyone aged 35-55" is millions of people. Most of whom don't want your product.

This serves the platform, not you.

**The Data That Actually Predicts Purchase**

If not demographics, then what?

**Purchase behavior is predicted by:**

1. **Psychographics** (Module 4)
   - Values and priorities
   - Attitudes and beliefs
   - Interests and lifestyle
   - Personality traits
2. **Behavioral patterns** (Module 7)
   - What problems they are actively trying to solve
   - How they research solutions
   - What triggers purchase decisions
   - Past purchase behavior
3. **Situational context** (Module 5)
   - Life stage and transitions
   - Business stage and transitions
   - Trigger events (funding, hiring, failure of previous solution)
   - Timing and urgency
4. **Jobs-to-be-Done** (Module 6)
   - What "job" they are hiring your product to do
   - What outcome they are trying to achieve
   - What alternatives they are considering
   - Why previous solutions failed

These factors predict purchase. Demographics do not.

**The Demographic Paradox**

Here is the paradox: Your best customers might share demographics. But those demographics are not why they bought.

**Example:**

You sell project management software. You analyze customers:

- 80% are companies with 20-100 employees
- 70% are in technology or professional services
- 90% are in coastal metros

You conclude: These demographics define your ICP.

**But the real pattern:**

All your customers share:

- Rapid growth (doubled headcount in 18 months)
- Distributed teams (remote or multi-office)
- Previous tool was failing (usually spreadsheets or free tools)
- Leader values transparency and accountability
- Budget authority to make decisions quickly

These are NOT demographic traits. These are behavioral and psychographic traits.

The demographics? Coincidental.

Tech companies in coastal cities happen to grow fast and go remote. But it is the growth and distribution that predict purchase, not the location and industry.

**If you target "tech companies in San Francisco," you will waste money on mature, slow-growth companies that look like your ICP but will never buy.**

**If you target "fast-growing distributed teams outgrowing their current tools," you will find customers in Austin, Denver, Miami, and Des Moines that convert.**

**The Cost of Demographic Targeting**

What does demographic targeting actually cost?

**Example calculation:**

Campaign budget: $10,000 Demographic targeting: "35-55 year olds, $75K+ income, urban areas" Potential reach: 5 million people

Actual target: People solving the problem your product solves Actual market: 50,000 people (1% of demographic reach)

Your ads get shown to 5 million people. 4.95 million do not care and will never buy.

Results:

- 10,000 clicks at $1 CPM leads to 100,000 impressions
- Click-through rate: 0.5% (most are curiosity clicks from non-buyers)
- 500 clicks at $20 CPC
- Conversion rate: 2% (most visitors are not in-market)
- 10 conversions at $1,000 CAC

**Now run the same campaign with behavioral targeting:**

Target: "People who recently searched for [your solution category], visited competitor sites, and match behavioral patterns of past customers"

Results:

- 10,000 clicks from 200,000 impressions (higher CTR because relevant)
- Click-through rate: 5% (people actively looking)
- 500 clicks at $20 CPC (same spend)
- Conversion rate: 10% (qualified traffic)
- 50 conversions at $200 CAC

**Same budget. 5X more customers. 80% lower CAC.**

The difference? Targeting intent and behavior, not demographics.

#### LESSON 2: The Shift from Demographic to Psychographic Targeting

Demographics describe who someone is. Psychographics describe how someone thinks.

If you want to predict purchase behavior, you need to understand how people think.

**What Are Psychographics?**

Psychographics are the psychological attributes that drive behavior:

1. **Values** - What they believe is important
2. **Attitudes** - How they view the world and specific topics
3. **Interests** - What they care about and engage with
4. **Lifestyle** - How they live day-to-day
5. **Personality** - How they approach decisions and risk
6. **Opinions** - What they believe about specific issues

These predict purchase better than demographics because they explain *why* someone buys, not just *who* bought.

**Psychographic vs Demographic: The Difference**

**Demographic Profile:**

- Age: 35-50
- Income: $100K+
- Location: Urban
- Education: College degree
- Family: Married, 2 kids

**Psychographic Profile:**

- Values: Efficiency, time-savings, quality over price
- Attitudes: Embraces technology, skeptical of marketing
- Interests: Productivity, self-improvement, business optimization
- Lifestyle: Busy professional, time-constrained, values convenience
- Personality: Risk-aware but willing to try new solutions if proven
- Opinions: Believes in investing in tools that save time

Which profile helps you write better ads? The psychographic one.

Which helps you choose channels? The psychographic one.

Which helps you craft offers? The psychographic one.

Demographics tell you nothing about messaging. Psychographics tell you everything.

**How Psychographics Change Marketing**

**Demographic Messaging:** "Software for 40-year-old managers"

**Psychographic Messaging:** "For leaders who refuse to waste time on manual processes"

The first targets age. The second targets values (efficiency) and identity (leaders who optimize).

**Which converts better?**

A 35-year-old efficiency-obsessed founder: Ignores first ad, clicks second.

A 45-year-old manager who accepts manual work: Ignores both ads.

The 35-year-old is "outside" your demographic target but inside your psychographic target. They convert.

The 45-year-old is "inside" your demographic target but outside your psychographic target. They do not convert.

**Psychographic targeting finds buyers. Demographic targeting finds people who fit a profile but do not buy.**

**The Five Core Psychographic Dimensions**

**1. Values - What Drives Decisions**

Values are fundamental beliefs about what is important.

**Example values that predict purchase:**

B2C:

- Status vs practicality
- Experiences vs possessions
- Convenience vs cost savings
- Sustainability vs affordability
- Innovation vs tradition

B2B:

- Growth vs stability
- Speed vs perfection
- Innovation vs proven solutions
- Efficiency vs cost cutting
- Control vs delegation

**How to use values in targeting:**

If your customer values speed over perfection:

- Messaging: "Ship faster, iterate as you go"
- Not: "Perfect your process before launching"

If your customer values status:

- Messaging: "Join [impressive company names]"
- Not: "Save money with our affordable solution"

Values determine messaging tone, offer structure, and proof points.

**2. Attitudes - How They View The World**

Attitudes are opinions and perspectives on specific topics.

**Example attitudes:**

Toward technology:

- Early adopter vs late majority
- Tech-savvy vs technophobe
- Excited by new tools vs frustrated by learning curves

Toward purchasing:

- Impulse buyer vs extensive researcher
- Price-sensitive vs value-focused
- Loyal to brands vs constantly switches

Toward change:

- Embraces change vs resists change
- Proactive vs reactive
- Innovator vs risk-averse

**How to use attitudes:**

Early adopter attitude leads to messaging focused on "Be the first to..."

Late majority attitude leads to messaging focused on "Join thousands of..."

Risk-averse attitude leads to messaging focused on guarantees, proof, social proof

**3. Interests - What They Engage With**

Interests tell you where to find your customer and what topics resonate.

**Example interests:**

B2C:

- Fitness, nutrition, wellness
- Travel, adventure, experiences
- Personal finance, investing
- Home improvement, DIY
- Fashion, style, trends

B2B:

- Productivity and efficiency
- Leadership and management
- Sales and marketing strategies
- Financial optimization
- Technology and automation

**How to use interests:**

If target customer is interested in "productivity hacks":

- Content topics: Time management, automation, efficiency
- Channels: Productivity podcasts, blogs, Reddit communities
- Partners: Productivity tool companies for co-marketing

Interests determine content strategy and channel selection.

**4. Lifestyle - How They Live**

Lifestyle is day-to-day behavior and how they spend their time.

**Example lifestyle factors:**

Work:

- Remote vs office vs hybrid
- Entrepreneur vs employee vs freelance
- Side hustle vs full-time focus
- Workaholic vs work-life balance

Personal:

- Urban vs suburban vs rural
- Active vs sedentary
- Social vs introverted
- Family-focused vs independent

**How to use lifestyle:**

Remote worker lifestyle leads to emphasis on "works from anywhere," async benefits

Workaholic lifestyle leads to emphasis on "get more done in less time"

Family-focused lifestyle leads to emphasis on "spend more time with family"

Lifestyle determines timing, channels, and problem framing.

**5. Personality - How They Make Decisions**

Personality traits predict how someone approaches purchase decisions.

**Example personality dimensions:**

Decision-making style:

- Analytical (needs data, research, comparison)
- Intuitive (trusts gut, decides quickly)
- Social (needs validation from others)
- Methodical (follows process, needs structure)

Risk tolerance:

- Risk-seeking (early adopter, tries new things)
- Risk-averse (waits for proof, needs guarantees)

Communication preference:

- Direct and concise
- Detailed and thorough

**How to use personality:**

Analytical personality leads to comparison charts, data, ROI calculators

Intuitive personality leads with story, emotion, vision

Risk-averse personality leads to free trial, money-back guarantee, case studies

Social personality leads to testimonials, community, social proof

**Psychographic Targeting in Practice**

Let's compare two companies selling the same product with different targeting:

**Company A: Demographic Targeting**

Product: Meal delivery service

Target: "Busy professionals aged 30-45, $80K+ income, urban areas"

Messaging: "Healthy meals delivered to your door"

Channels: Facebook ads to 30-45 year olds in cities

Results: 1.5% conversion, $85 CAC, 40% churn in first 3 months

**Company B: Psychographic Targeting**

Product: Same meal delivery service

Target: "Health-conscious professionals who value time but feel guilty about not cooking, believe in investing in health, frustrated by meal planning"

Messaging: "You shouldn't have to choose between health and time. We handle the planning, prep, and cooking so you can focus on what matters."

Channels: Health podcasts, productivity blogs, fitness app partnerships

Results: 8% conversion, $35 CAC, 15% churn in first 3 months

**Same product. 5X better conversion. 60% lower CAC. 60% lower churn.**

The difference? Company B targeted psychology, not demographics.

**Building Psychographic Profiles**

You do not need expensive research to build psychographic profiles. You need to ask better questions.

**Instead of asking:**

- How old are you?
- What's your income?
- Where do you live?

**Ask:**

- What problem were you trying to solve when you found us?
- What did you try before us that didn't work?
- What made you decide to buy now vs 6 months ago?
- What almost stopped you from buying?
- What do you value most about our solution?

These questions reveal psychographics:

- Problem = pain point and motivation
- Previous attempts = what they value (why those failed)
- Timing = trigger events and urgency drivers
- Hesitation = risk tolerance and decision-making style
- Value = what benefits matter (features they ignore tell you what doesn't matter)

**Module 4 covers how to extract and use psychographic data systematically.**

#### LESSON 3: How Fortune 500 Companies Actually Profile Customers

Small businesses target demographics because it is easy. Fortune 500 companies target psychographics because it works.

Here is how sophisticated companies actually build customer profiles.

**Case Study 1: Apple**

Apple does not target "people aged 25-45 with income over $75K."

Apple targets psychographics:

**Apple Customer Psychographic Profile:**

Values:

- Design and aesthetics over specs
- Simplicity over customization
- Brand identity and status
- Integration and ecosystem

Attitudes:

- Willing to pay premium for quality
- Early adopter of new technology
- Values brand loyalty
- Sees technology as extension of identity

Lifestyle:

- Creative professionals, entrepreneurs, students
- Values productivity and creativity
- Engaged with design, media, arts

Personality:

- Intuitive decision maker (not spec-comparison buyer)
- Values emotional connection to products
- Community-oriented (wants to be part of something)

**How Apple uses this:**

Messaging: Never leads with specs. Leads with experience, feeling, identity.

"Think Different" appeals to self-identity as innovator. "It just works" appeals to value of simplicity. "Shot on iPhone" appeals to creative identity.

Channels: Design conferences, creative communities, education institutions

Retail: Apple Stores are designed for experience and community, not transactions

**Result:** Apple has the most loyal customer base in technology. Not because of demographics, but because of psychographic alignment.

**Case Study 2: Patagonia**

Patagonia does not target "outdoor enthusiasts aged 30-60."

Patagonia targets values-based psychographics:

**Patagonia Customer Psychographic Profile:**

Values:

- Environmental sustainability and activism
- Quality and durability over fashion trends
- Authentic experiences over material goods
- Corporate responsibility

Attitudes:

- Skeptical of corporate greenwashing
- Willing to pay premium for ethical products
- Values transparency
- Believes individuals can drive change

Lifestyle:

- Outdoor activities (climbing, hiking, skiing)
- Minimalist consumption (buy less, buy better)
- Politically and socially engaged
- Values experiences over possessions

Personality:

- Thoughtful, deliberate purchaser
- Research-driven decision making
- Community-oriented
- Mission-driven

**How Patagonia uses this:**

Messaging: "Don't buy this jacket" (anti-consumption, sustainability message)

"We're in business to save our home planet" appeals to a mission-driven identity

Products: Worn Wear program (repair, reuse) appeals to values

Channels: Environmental activism, outdoor communities, sustainability conferences

Corporate actions: 1% for the Planet, political activism, supply chain transparency

**Result:** Patagonia commands premium pricing and extreme loyalty because customers align with values, not just product category.

**Case Study 3: Salesforce**

Salesforce does not target "companies with 500+ employees in tech."

Salesforce targets B2B psychographics:

**Salesforce Customer Psychographic Profile:**

Values (company level):

- Innovation and digital transformation
- Growth and scalability
- Customer-centricity
- Data-driven decision making

Attitudes (decision-maker level):

- Embraces cloud technology
- Willing to invest in long-term platforms
- Values integration and ecosystem
- Sees CRM as strategic, not tactical

Lifestyle (business operations):

- Fast-growing companies
- Distributed or scaling teams
- Complex sales processes
- Multiple stakeholders in buying decisions

Personality (decision-maker):

- Visionary leadership style
- Risk-tolerant with proven solutions
- Values community and peer validation
- Long-term thinking over quick fixes

**How Salesforce uses this:**

Messaging: "Customer 360" speaks to the customer-centricity value

"Trailblazer Community" speaks to identity and belonging

Dreamforce conference builds community and reinforces identity

Channels: Executive thought leadership, innovation conferences, peer networks

Sales process: Multi-stakeholder demos, focus on transformation not features

**Result:** Salesforce dominates enterprise CRM not through feature superiority but through psychographic alignment with how innovative companies see themselves.

**Case Study 4: Peloton**

Peloton does not target "affluent consumers aged 30-50 interested in fitness."

Peloton targets psychographic patterns:

**Peloton Customer Psychographic Profile:**

Values:

- Convenience and time efficiency
- Community and motivation
- Investment in health and wellness
- Status and lifestyle signaling

Attitudes:

- Willing to pay premium for at-home convenience
- Motivated by social connection and competition
- Values structured workouts and guidance
- Sees fitness as part of identity

Lifestyle:

- Busy professionals and parents
- Time-constrained but health-conscious
- Values home-based solutions
- Engaged with digital/social fitness

Personality:

- Goal-oriented and competitive
- Community-driven (needs external motivation)
- Consistency-focused
- Achievement-oriented

**How Peloton uses this:**

Messaging: Not about the bike. About the community, the instructors, the experience.

"Together we go far" is a community appeal

Instructor culture: Parasocial relationships drive retention

Leaderboards and achievements: Gamification for competitive personalities

Channels: Influencer partnerships, digital communities, word-of-mouth

**Result:** Peloton created a cult-like following not through product features (it is a stationary bike) but through psychographic alignment around community, achievement, and identity.

**The Pattern Across All Four Companies**

Notice what none of these companies lead with:

- Age ranges
- Income brackets
- Geographic locations
- Education levels

Instead they target:

- **Values** - What customers believe is important
- **Identity** - How customers see themselves
- **Motivation** - What drives behavior
- **Community** - Who they want to belong with

**This is psychographic targeting in action.**

**How to Apply This to Your Business**

You do not need Apple's budget to use psychographic targeting.

You need to shift your profiling questions from:

**Demographic questions:**

- How old is our customer?
- What do they earn?
- Where do they live?

**To psychographic questions:**

- What do they value?
- How do they make decisions?
- What do they believe about our category?
- Who do they want to be?
- What problems are they trying to solve?
- Why did they choose us over alternatives?

**Module 2 teaches you how to collect psychographic data from your existing customers.**

**Module 4 teaches you how to build complete psychographic profiles.**

**Module 9 teaches you how to validate that your psychographic targeting is working.**

**The Fortune 500 Secret**

The secret is not a secret. It is just hard work.

Large companies invest in understanding customer psychology because it works. They do not target demographics because they have learned demographics waste money.

Small businesses target demographics because it is easy and platforms make it easy to filter by age, income, location.

**But easy does not equal profitable.**

The businesses that win are the ones that do the hard work of understanding customer psychology and targeting based on how people think, not who they are.
