TGM RESEARCH BLOG
What are Consumer Insights? A Guide to Understand Your Target Market
11 Types of Consumer Insights with Examples
1. Demographic Insights
Demographic insights provide a factual picture of who your customers are. They include basic traits like age, gender, and income, as well as more detailed aspects such as education, occupation, and geographic location. These insights are essential for segmentation, allowing businesses to identify distinct groups and tailor offerings to each.
Example: TGM Vietnam E-commerce Insights 2025 found that female shoppers are twice as likely as male shoppers to value customizable shopping options, such as personalized products or flexible delivery dates. Tailoring online experiences with personalization and flexibility could resonate more strongly with women, giving brands a clear opportunity to design gender-sensitive marketing and product features.
Demographic insights provide a factual picture of who your customers are. They include basic traits like age, gender, and income, as well as more detailed aspects such as education, occupation, and geographic location. These insights are essential for segmentation, allowing businesses to identify distinct groups and tailor offerings to each.
Example: TGM Vietnam E-commerce Insights 2025 found that female shoppers are twice as likely as male shoppers to value customizable shopping options, such as personalized products or flexible delivery dates. Tailoring online experiences with personalization and flexibility could resonate more strongly with women, giving brands a clear opportunity to design gender-sensitive marketing and product features.
2. Psychographic Insights
Psychographic insights explore the values, interests, attitudes, and lifestyles that influence why customers behave the way they do. They go beyond “who” the customer is and reveal the underlying motivations shaping decisions. Marketers often use psychographics to refine messaging and align brand values with consumer expectations.
Example: The TGM Global Sustainability Report found that 43% of consumers see high costs as the biggest barrier to adopting sustainable lifestyles. This highlights a tension: people value sustainability but feel excluded by price. A brand that emphasizes affordability, positioning eco-friendly options as accessible rather than premium, can build stronger connections with this audience.
Psychographic insights explore the values, interests, attitudes, and lifestyles that influence why customers behave the way they do. They go beyond “who” the customer is and reveal the underlying motivations shaping decisions. Marketers often use psychographics to refine messaging and align brand values with consumer expectations.
Example: The TGM Global Sustainability Report found that 43% of consumers see high costs as the biggest barrier to adopting sustainable lifestyles. This highlights a tension: people value sustainability but feel excluded by price. A brand that emphasizes affordability, positioning eco-friendly options as accessible rather than premium, can build stronger connections with this audience.
3. Behavioral Insights
Behavioral insights analyze what customers actually do when interacting with a brand. This includes purchase history, browsing patterns, app usage, and social media engagement. Such insights reveal friction points and habits, helping businesses optimize experiences and predict future actions.
Example: A global FMCG company wanted to improve its online store experience and discovered that many shoppers abandoned carts when shipping costs appeared at checkout. By testing free shipping thresholds, the company reduced abandonment and boosted order values. This highlights a tension: people value sustainability but feel excluded by price. A brand that emphasizes affordability, positioning eco-friendly options as accessible rather than premium, can build stronger connections with this audience.
Behavioral insights analyze what customers actually do when interacting with a brand. This includes purchase history, browsing patterns, app usage, and social media engagement. Such insights reveal friction points and habits, helping businesses optimize experiences and predict future actions.
Example: A global FMCG company wanted to improve its online store experience and discovered that many shoppers abandoned carts when shipping costs appeared at checkout. By testing free shipping thresholds, the company reduced abandonment and boosted order values. This highlights a tension: people value sustainability but feel excluded by price. A brand that emphasizes affordability, positioning eco-friendly options as accessible rather than premium, can build stronger connections with this audience.
4. Feedback Insights
Feedback insights come directly from consumers’ voices, through surveys, interviews, reviews, and support tickets. Unlike demographic or behavioral data, feedback captures perceptions and emotions, giving businesses unfiltered views of needs, frustrations, and satisfaction.
Example: A hotel group receives repeated reviews mentioning long check-in lines. Acting on this feedback, they introduce mobile check-in options. The change reduces complaints, improves guest satisfaction, and strengthens repeat bookings.
Feedback insights come directly from consumers’ voices, through surveys, interviews, reviews, and support tickets. Unlike demographic or behavioral data, feedback captures perceptions and emotions, giving businesses unfiltered views of needs, frustrations, and satisfaction.
Example: A hotel group receives repeated reviews mentioning long check-in lines. Acting on this feedback, they introduce mobile check-in options. The change reduces complaints, improves guest satisfaction, and strengthens repeat bookings.
5. Purchasing Data Insights
Purchasing data insights focus on the hard numbers of buying behavior. They show which products sell, how often people buy, and what patterns emerge over time. This type of insight is invaluable for demand forecasting, pricing, and cross-selling.
Example: A children’s bookstore notices that sales of educational workbooks spike every August as school resumes. Using this insight, the store launches back-to-school bundles and promotions, driving higher seasonal sales.
Purchasing data insights focus on the hard numbers of buying behavior. They show which products sell, how often people buy, and what patterns emerge over time. This type of insight is invaluable for demand forecasting, pricing, and cross-selling.
Example: A children’s bookstore notices that sales of educational workbooks spike every August as school resumes. Using this insight, the store launches back-to-school bundles and promotions, driving higher seasonal sales.
6. Customer Journey Insights
Customer journey insights map the full experience a customer has with a brand, from first discovery to repeat purchases and loyalty. They highlight key touchpoints, show where customers drop off, and reveal opportunities for improvement.
Example: A meal delivery service realizes many potential customers abandon sign-up after the menu selection stage. By simplifying the onboarding flow and offering sample menus upfront, the company reduces churn at this critical step.
Customer journey insights map the full experience a customer has with a brand, from first discovery to repeat purchases and loyalty. They highlight key touchpoints, show where customers drop off, and reveal opportunities for improvement.
Example: A meal delivery service realizes many potential customers abandon sign-up after the menu selection stage. By simplifying the onboarding flow and offering sample menus upfront, the company reduces churn at this critical step.
Specialized Consumer Insight Types
Beyond the foundational categories, there are also specialized types of consumer insights. These don’t stand apart as raw data categories, but they represent recurring themes businesses look for when interpreting demographic, behavioral, and feedback data. They help you dig deeper into motivations, emotions, and specific buying contexts.
7. Motivational Insights
Motivational insights show the reasons people choose certain products or brands. This type of insight is often developed from psychographic insights and feedback insights.
Example: TGM Global Food Delivery Insights 2024 revealed that 43% of users picked their most-used delivery app primarily because they trusted the brand name, while another smaller group valued fast order acceptance and processing. This shows that trust and efficiency are stronger motivators than price or even restaurant variety.
Motivational insights show the reasons people choose certain products or brands. This type of insight is often developed from psychographic insights and feedback insights.
Example: TGM Global Food Delivery Insights 2024 revealed that 43% of users picked their most-used delivery app primarily because they trusted the brand name, while another smaller group valued fast order acceptance and processing. This shows that trust and efficiency are stronger motivators than price or even restaurant variety.
8. Emotional Insights
Emotional insights capture feelings that drive choices like trust, excitement, or fear.
Example: insurance renewals often hinge on peace of mind. These insights are closely tied to psychographic insights and can also surface through behavioral insights.
Emotional insights capture feelings that drive choices like trust, excitement, or fear.
Example: insurance renewals often hinge on peace of mind. These insights are closely tied to psychographic insights and can also surface through behavioral insights.
9. Occasion-Based Insights
Occasion-based insights link purchases to moments or events.
Example: bakeries see cake sales rise during birthdays and holidays. They are commonly identified using purchasing data insights and customer journey insights.
Occasion-based insights link purchases to moments or events.
Example: bakeries see cake sales rise during birthdays and holidays. They are commonly identified using purchasing data insights and customer journey insights.
10. Price Sensitivity Insights
Price sensitivity insights reveal how consumers react to pricing and willingness to pay.
Example: young users seek low cost, while professionals pay extra for speed. This type often draws on purchasing data insights and feedback insights.
Price sensitivity insights reveal how consumers react to pricing and willingness to pay.
Example: young users seek low cost, while professionals pay extra for speed. This type often draws on purchasing data insights and feedback insights.
11. Pain Point Insights
Pain point insights identify frustrations or barriers in the experience.
Example: complicated return policies discourage repeat e-commerce customers. These are usually uncovered through customer journey insights and feedback insights.
Pain point insights identify frustrations or barriers in the experience.
Example: complicated return policies discourage repeat e-commerce customers. These are usually uncovered through customer journey insights and feedback insights.
7 Core Qualities to Ensure Your Consumer Insights Are Valuable
Valuable consumer insights share a few common qualities:
- Specific: They focus on a clearly defined behavior, need, or trend rather than being vague or overly broad.
Example: Identifying that younger customers abandon carts at the payment stage is more useful than simply saying “checkout is difficult.” - Actionable: A good insight points directly to what the business can do next.
Example: An insight such as “customers abandon their carts mainly because delivery times feel too long” clearly leads to the action of offering faster or same-day shipping. - Surprising: Valuable insights often challenge assumptions or reveal something unexpected, helping brands break out of the status quo.
Example: An insight showing that “customers choose the premium plan not for the extra features but for the sense of status it provides” overturns the assumption that functionality alone drives upgrades. - Relevant: They connect directly to the brand’s goals, product portfolio, and customer challenges, making them meaningful for the business context.
Example: An insight revealing that “most first-time buyers discover the brand through mobile ads” directly supports a company’s goal of scaling digital channels. - Timely: Insights matter most when they reflect current market conditions and evolving consumer needs.
Example: An insight such as “eco-conscious consumers now actively avoid single-use plastics” is highly relevant today, whereas older data on packaging habits may no longer apply. - Authoritative: Strong insights are grounded in reliable data and evidence, giving decision-makers confidence to act on them.
Example: An insight that “seventy percent of surveyed users say they would recommend the product if customer support were faster” carries weight because of its solid evidence base. - Decision-Driving: Above all, a valuable insight is one that influences real business choices, shaping strategy and leading to measurable impact.
Example: An insight such as “customers hesitate to make repeat purchases because refill options are unclear” directly leads to the decision to redesign the subscription model.
Three Consumer Insights Examples That Worked and What You Can Learn
Here are 3 real-life consumer insight examples (or campaigns based on insights) you can use, along with what they reveal and lessons to learn:
1. Coca-Cola “Share a Coke”
Coca-Cola replaced its logo on bottles with popular individual names, nudging people to find bottles with their names or friends’ names and share them.
Context & Challenge:
By 2013, carbonated soft drinks in the US had been declining for nine consecutive years. Half of all American teens hadn’t consumed a Coke in the previous year, and many perceived it as their parents’ drink “trusty but dusty”. The brand needed to reconnect with a younger audience and drive trial.
Insight revealed:
Coca-Cola’s Teen Attitude and Usage Study revealed a serious perception problem: many young people saw Coke as their parents’ drink, “trusty but dusty”. Even more concerning, only 13% of teens considered Coke to be unique. This shows the perception gap: Coke = iconic but irrelevant for young people.
At the same time, teens were gravitating toward brands that felt personal and socially shareable. This gap created an opportunity: if Coke could make the product feel more “for me” and easy to share with friends, it could rebuild relevance with a new generation. Academic research later explained why this approach resonated, putting a name on a bottle tapped into identity and recognition, turning a drink into a personal statement (Culig Suknaic, 2025).
What Coca-Cola did:
The brand swapped its logo on 20-ounce bottles for 250 of the most popular teen names in the US. To spark sharing, it launched the hashtag #ShareaCoke, partnered with influencers, and even set up interactive billboards and kiosks where teens could see their names on Coke bottles.
Lesson:
Use personalization (even small touches) to deepen emotional connection. An insight into wanting to feel seen translated into packaging that drives engagement and sales.
Source: US Coca-Cola: Persuading Teens to ‘Share a Coke’ case study (The Market Research Society (MRS).
Context & Challenge:
By 2013, carbonated soft drinks in the US had been declining for nine consecutive years. Half of all American teens hadn’t consumed a Coke in the previous year, and many perceived it as their parents’ drink “trusty but dusty”. The brand needed to reconnect with a younger audience and drive trial.
Insight revealed:
Coca-Cola’s Teen Attitude and Usage Study revealed a serious perception problem: many young people saw Coke as their parents’ drink, “trusty but dusty”. Even more concerning, only 13% of teens considered Coke to be unique. This shows the perception gap: Coke = iconic but irrelevant for young people.
At the same time, teens were gravitating toward brands that felt personal and socially shareable. This gap created an opportunity: if Coke could make the product feel more “for me” and easy to share with friends, it could rebuild relevance with a new generation. Academic research later explained why this approach resonated, putting a name on a bottle tapped into identity and recognition, turning a drink into a personal statement (Culig Suknaic, 2025).
What Coca-Cola did:
The brand swapped its logo on 20-ounce bottles for 250 of the most popular teen names in the US. To spark sharing, it launched the hashtag #ShareaCoke, partnered with influencers, and even set up interactive billboards and kiosks where teens could see their names on Coke bottles.
Lesson:
Use personalization (even small touches) to deepen emotional connection. An insight into wanting to feel seen translated into packaging that drives engagement and sales.
Source: US Coca-Cola: Persuading Teens to ‘Share a Coke’ case study (The Market Research Society (MRS).
2. Spotify — Personalization Powered by Machine Learning
Context & Challenge:
With hundreds of millions of tracks available, listeners face “choice overload” and struggle to discover music they truly enjoy. Early solutions like radio DJs or manual tagging (e.g., Pandora) couldn’t scale. Spotify needed a way to deliver personal discovery to millions of users while competing in an increasingly crowded streaming market.
Insight revealed:
Spotify saw that personalization could become its competitive advantage if powered by machine learning. According to a Harvard Digital (RCTOM) analysis, machine-generated personalized playlists like Discover Weekly and Release Radar already accounted for 31% of all listening on Spotify, up from less than 20% two years earlier (Harvard Digital RCTOM, 2018). This growth confirmed that users valued tailored recommendations and discoveries.
What Spotify did:
Machine learning turned personalization into a strategic moat. By analyzing listening data at scale and adapting in real time, Spotify transformed music discovery into a signature experience that kept users engaged, loyal, and less likely to switch platforms.
Source: Harvard Digital, “Spotify + The Machine: Using Machine Learning to Create Value and Competitive Advantage,” Nov 13, 2018.
With hundreds of millions of tracks available, listeners face “choice overload” and struggle to discover music they truly enjoy. Early solutions like radio DJs or manual tagging (e.g., Pandora) couldn’t scale. Spotify needed a way to deliver personal discovery to millions of users while competing in an increasingly crowded streaming market.
Insight revealed:
Spotify saw that personalization could become its competitive advantage if powered by machine learning. According to a Harvard Digital (RCTOM) analysis, machine-generated personalized playlists like Discover Weekly and Release Radar already accounted for 31% of all listening on Spotify, up from less than 20% two years earlier (Harvard Digital RCTOM, 2018). This growth confirmed that users valued tailored recommendations and discoveries.
What Spotify did:
- Deployed multiple ML models
- Acquisitions for ML strength: Echo Nest (2014), Sonalytic (2017), and Niland (2017) expanded Spotify’s recommendation capabilities.
- Continuous testing: A/B experiments and iterative design ensured recommendations became more accurate and stickier over time.
Machine learning turned personalization into a strategic moat. By analyzing listening data at scale and adapting in real time, Spotify transformed music discovery into a signature experience that kept users engaged, loyal, and less likely to switch platforms.
Source: Harvard Digital, “Spotify + The Machine: Using Machine Learning to Create Value and Competitive Advantage,” Nov 13, 2018.
3. IKEA – Small-Space Living Solutions
Context & Challenge:
By 2020, more than half of the world’s population was living in cities, and rising urbanization meant shrinking home sizes. Consumers faced the challenge of fitting sleep, work, leisure, and social life into limited square meters.
Insight revealed:
IKEA research showed a growing demand for multifunctional and flexible furniture that could adapt to different activities throughout the day, such as sleeping, working, relaxing, and socializing. Beyond practicality, people also wanted to express their lifestyle and identity in small spaces. The tension: limited space but unlimited human needs.
What IKEA did:
In response, IKEA began developing transformable furniture such as a foldable bed-desk hybrid that converts from a workspace into a bedroom, complete with built-in storage. These solutions were piloted in Poland and Hong Kong in 2023, with prototypes featured in the Existence Maximum – Big Ideas on Small Spaces exhibition at the IKEA Museum.
Lesson:
This case shows how cultural and lifestyle insights can fuel innovation. By observing urban living constraints and understanding the emotional need for both functionality and self-expression, IKEA turned consumer insight into product design that directly solves a pain point while enhancing everyday life.
Source: Inter IKEA Newsroom – IKEA looks to innovation for new small-space solutions (Dec 2022).
By 2020, more than half of the world’s population was living in cities, and rising urbanization meant shrinking home sizes. Consumers faced the challenge of fitting sleep, work, leisure, and social life into limited square meters.
Insight revealed:
IKEA research showed a growing demand for multifunctional and flexible furniture that could adapt to different activities throughout the day, such as sleeping, working, relaxing, and socializing. Beyond practicality, people also wanted to express their lifestyle and identity in small spaces. The tension: limited space but unlimited human needs.
💡 One of IKEA’s core research methods is ethnographic studies, spending full days in people’s homes to observe how they eat, work, clean, relax, and even argue over storage space.
What IKEA did:
In response, IKEA began developing transformable furniture such as a foldable bed-desk hybrid that converts from a workspace into a bedroom, complete with built-in storage. These solutions were piloted in Poland and Hong Kong in 2023, with prototypes featured in the Existence Maximum – Big Ideas on Small Spaces exhibition at the IKEA Museum.
Lesson:
This case shows how cultural and lifestyle insights can fuel innovation. By observing urban living constraints and understanding the emotional need for both functionality and self-expression, IKEA turned consumer insight into product design that directly solves a pain point while enhancing everyday life.
Source: Inter IKEA Newsroom – IKEA looks to innovation for new small-space solutions (Dec 2022).
How to Collect Quality Consumer Insights
To understand consumers well, you need to combine qualitative research that uncovers the “why” behind behavior with quantitative research that explains the “what” and “how many.”
1. Primary Qualitative Methods: Digging into motivations
- Customer interviews and focus groups: Speaking directly with customers gives rich, detailed feedback in their own words, adding depth that raw numbers miss.
- Feedback channels: Support tickets and feedback forms often reveal pain points and requests straight from real users.
- Open-ended online surveys: Distributing questionnaires with open-ended questions to capture detailed, qualitative responses in consumers’ own words.
- Ethnographic research: Immersing in people’s everyday environments to observe habits, unspoken needs, and small frustrations that surveys often miss.
2. Primary Quantitative Methods: Measuring patterns at scale
- Close-ended online surveys: Using structured questions with predefined answer choices (like multiple choice, ratings, or yes/no) to generate measurable, quantitative data that can be easily analyzed at scale.
- Behavioral data: Tracking how people use your website, app, or products shows actual preferences and usage habits.
- Web analytics: Analyzing traffic, clickstreams, heatmaps, and user flow provides clues about consumer interests and decision paths.
- A/B testing & experiments: Running controlled tests that expose consumers to different versions of a product, feature, or message. By comparing which option they prefer or engage with most, you uncover insights into consumer preferences, motivations, and decision triggers.
- Panel research: Using large, representative samples across markets to measure opinions and behaviors consistently over time.
Learn more: How to choose high-quality online research panels: 3-step vetting guide
3. Passive / Ongoing Feedback Methods
- Online reviews: Customer reviews across platforms reflect real purchase experiences and perceptions.
- Net Promoter Score (NPS): A quick way to assess loyalty by measuring how likely customers are to recommend your brand.
- Social listening: Tracking consumer conversations and sentiment across social media, forums, and review sites to uncover opinions and cultural shifts.
- Secondary research: Using published sources such as industry reports, competitor analysis, and market studies to gain context.
- Transaction & purchase data: Point-of-sale records, loyalty programs, and CRM systems reveal buying frequency, basket size, and repeat behaviors.
For a practical roadmap, see our guide on turning consumer data into actionable insights that help you target the right audience.
How to Find Consumer Insights in a World Full of Data
While conducting your own research is powerful, it’s not always practical to start from scratch. Often, the fastest way to understand your market is to tap into existing, trustworthy data sources. Not every source will give you a ready-made “insight”. Instead, think of them as building blocks you analyze to uncover what consumers want, need, or struggle with:
- Global market data providers: Platforms like Statista, Euromonitor, and Kantar offer industry-wide reports, trend tracking, and benchmarks. Useful for context, though some require paid access.
- Consumer behavior & search/survey-based reports: Sources like Think with Google, TGM StatBox, and TGM Research Insights collect insights through online surveys and search data, showing what people are searching, buying, or talking about, with fresh category-specific trends.
- Social media listening reports: Track discussions and sentiment across platforms to uncover consumer opinions, cultural shifts, and campaign impact.
- Socio-economic & demographic data: Institutions such as the United Nations, International Monetary Fund, and World Bank provide free national-level data that helps explain broader forces shaping consumer behavior.
- Other specialized sources: ResearchGate (academic studies) and Metric.vn (e-commerce tracking) offer niche but valuable datasets for deeper analysis.
Among these, consumer behavior surveys, search trend data, and social media listening are the most directly related to uncovering real consumer insights.
However, the challenge is less about availability and more about knowing which reports and datasets are reliable and relevant. Want to know which reports you can trust and how to evaluate them? Read our complete guide on finding reliable consumer insights with practical tips.
However, the challenge is less about availability and more about knowing which reports and datasets are reliable and relevant. Want to know which reports you can trust and how to evaluate them? Read our complete guide on finding reliable consumer insights with practical tips.
