Video summary
Market Segmentation Strategies: Geographic, Demographic, Psychographic & Behavioral Explained!
Main summary
Key takeaways
Market Segmentation Frameworks (4 main types)
1) Geographic segmentation
- What it is: Split markets using location-based characteristics such as region, country, market size, market density, and climate.
- Why it matters operationally: Creates different target groups by geographic boundaries and supports decisions on where to sell, advertise, and expand.
- Examples
- Luxury car manufacturer: Targets customers in warmer climates so vehicles don’t need heavy weather equipment.
- Marketing platform: Focuses campaigns on urban city centers where target customers are likely to live.
Common process details / use cases
- Classify residential regions/postcodes using census + lifestyle characteristics from multiple data sources.
- Consider as a first step in international marketing: decide whether to adapt products/marketing programs for unique needs of each geographic market.
- Used in direct marketing (e.g., letterbox distribution, direct mail) via geocluster segmentation.
- Government/public sector uses include urban planning, health authorities, police/criminal justice, telecommunications, utilities (e.g., water boards).
2) Demographic segmentation
- What it is: Split the market using statistical attributes such as age, education, income, family size, race, gender, occupation, nationality, and related variables.
- Core assumption: People with similar demographic profiles tend to show similar purchasing patterns, motivations, and lifestyle behaviors, leading to brand/product preference similarity.
- Example cases
- B2C luxury vehicle brand: Targets higher-income audiences.
- B2B enterprise marketing platform: Targets roles like marketing managers at large companies (500+ employees) who can influence/approve purchases for their team.
How it’s implemented
- Can use any variable collected by national census systems.
- Using multiple variables often requires database analysis + statistical methods such as:
- Cluster analysis
- Principal components analysis (PCA)
- These methods require very large sample sizes and can be expensive for individual firms.
3) Psychographic segmentation
- What it is: Split markets based on personality, motives, and lifestyle (i.e., psychological drivers).
- How it’s measured: Often requires research because it’s more subjective than demographics.
- Measured through activities, interests, opinions, and how people spend leisure time.
- Often described as psychometric or lifestyle segmentation.
- Examples
- Luxury car brand: Targets customers who value quality and “status/studs” (as described in the subtitles).
- B2B enterprise marketing platform: Targets marketers/buyers motivated to increase productivity and demonstrate value to executives.
4) Behavioral segmentation
- What it is: Split markets based on how customers act, including interactions with your brand and behavior outside it.
- Examples
- B2C: Target customers who purchased a high-end vehicle in the past 3 years.
- B2B: Target leads who signed up for free webinars.
- Health industry: Segment by health consciousness into low / moderate / highly health-conscious groups.
- Why it’s powerful: Tied to purchase/consumption/usage + decision-making patterns, enabling more targeted marketing.
- Tradeoff: Requires knowledge of customer actions (and often stronger instrumentation/data).
Additional segmentation types mentioned (extensions)
- Generational segmentation: Divide into cohorts by birth date; assumes values/attitudes come from key life events and drive brand preferences.
- Cultural segmentation: Classify by cultural origin to tailor communications; can also measure penetration in cultural segments by:
- Product/brand
- Channel
- Traditional metrics like reach/frequency/monetary value (noted as “reeny frequency and monetary value” in the subtitles)
Operating principle for choosing segmentation (online + offline)
Online market segmentation (data/CRM/DMP driven)
Requirements: Segments should be:
- Identifiable
- Substantial
- Accessible
- Stable
- Differentiable
- Actionable
Data + tooling approach
- Use an online data management system such as a CRM or DMP to analyze customer behavior across attributes.
Behavioral differences tracked online (examples of attributes)
- Time spent actively online
- Number of pages/sites visited
- Time actively viewing each page
- Types of websites visited
Metrics / KPIs mentioned (high level, not numeric targets)
- In cultural segmentation, subtitles reference evidence-based benchmarks based on:
- Reach
- Frequency
- Monetary value
- No explicit company-level targets (e.g., revenue, CAC, LTV, churn) or timelines were provided in the subtitles.
Actionable recommendations implied by the content
- Start with the “who/where/why/how” logic:
- Use geographic for location-specific needs and channel tactics.
- Use demographic for baseline targeting and scalable segmentation.
- Use psychographic when you need to reach customers based on motivation and values.
- Use behavioral when you want to target based on intent and past actions.
- For advanced segmentation:
- Use multi-variable analysis (e.g., cluster analysis/PCA) where you have large datasets.
- For online targeting, build segments using CRM/DMP behavior signals and ensure segments are actionable.
Sources / presenters
No presenters or external sources are identified in the provided subtitles.