TGM RESEARCH BLOG
How to Do Market Research for Your Business in Eight Steps
Learn how to do market research effectively, from defining objectives to leveraging AI, with best practices and real-world examples for businesses of all sizes.
When You Should Conduct Market Research
Market research performs best when a business decision affects revenue, product direction, brand positioning, market entry, or customer experience.
Here are the 6 most important moments when you should conduct market research.
Here are the 6 most important moments when you should conduct market research.
1. When You Want to Protect Current Revenue
Businesses often focus heavily on growth, but research is equally important for understanding existing customers. Satisfaction, loyalty, churn, and customer experience research can reveal why customers stay, why they leave, and what improvements matter most.
Conduct market research when you need to understand:
- Customer satisfaction and dissatisfaction
- Reasons for churn or reduced engagement
- Drivers of loyalty and repeat purchase
- Service gaps or experience pain points
- Opportunities for upselling or cross-selling
For example, a subscription service may discover that customers are not leaving because of price, but because onboarding is confusing. Without research, the company might wrongly respond with discounts instead of fixing the experience.
2. When You Need to Win New Customers
Market research helps identify which customer segments are most attractive and how to reach them effectively. This is important when acquisition costs are rising or campaigns are struggling to convert.
Research can answer:
- Which audience segments are most likely to buy?
- What problems are they trying to solve?
- Which messages are most persuasive?
- Which channels influence their decision?
- What barriers prevent them from choosing your brand?
3. When Launching a New Product or Service
Before investing in development, production, distribution, or promotion, research can test whether the concept has real potential.
Product and concept research can evaluate:
- Market demand
- Purchase intent
- Product relevance
- Feature importance
- Packaging or design appeal
- Pricing expectations
- Competitive differentiation
- Barriers to adoption
A common mistake is asking customers if they “like” an idea or not. A better research approach examines whether the idea solves a real problem, whether customers understand the value, and whether they would choose it over available alternatives.
4. When Entering a New Market
A product that succeeds in one country or segment may not perform the same way elsewhere. Local behaviors, purchasing power, cultural expectations, regulations, payment habits, media channels, and competitor dynamics can vary significantly.
Market entry research helps you understand:
- Market size and opportunity
- Local consumer behavior
- Competitive landscape
- Brand awareness and trust barriers
- Pricing sensitivity
- Distribution and channel preferences
- Cultural or regulatory considerations
For international studies, translating a questionnaire is not enough. The research design, sample structure, question wording, and interpretation must reflect how people in that market actually think and behave.
5. When Changing Pricing, Positioning, or Messaging
Pricing and positioning decisions can directly affect revenue and brand perception. Market research helps determine how customers perceive value, what they are willing to pay, and which messages create the strongest motivation.
Useful research areas include:
- Price sensitivity
- Willingness to pay
- Value perception
- Brand positioning
- Message testing
- Claim testing
- Competitive comparison
6. When Performance Data Shows a Problem but Not the Reason
Sales data, website analytics, or campaign reports can show that something is wrong, but they often cannot fully explain why.
For example:
- The conversion rate is dropping, but why?
- Awareness is high, but purchase intent is low.
- Customers try the product once but do not return to use it again.
- A campaign generates traffic but not sales.
- A product performs well in one market but poorly in others.
One of the strongest reasons for conducting market research is when internal teams disagree. Research creates a shared evidence base so teams can move from opinion-based debate to decision-making grounded in customer reality.
2 Main Types of Market Research
Market research can be organized in several ways. For business users, the most practical distinction is not overly academic. It is more useful to understand what each type of research helps you decide.
Primary Research
Primary research involves collecting original data directly from your target audience for a specific business question. It is divided into two main categories:
1. Qualitative Research
Qualitative research explores motivations, perceptions, emotions, language, and context. It provides detailed, descriptive insights into the 'why' and 'how' of behavior but is less generalizable. This type of research is often exploratory in nature, which is often the initial step in the research process, helping to lay the groundwork for more conclusive research later on. Methods of exploratory research include:
- In-depth interviews: One-on-one discussions with participants to gather in-depth insights.
- Focus Groups: Moderated discussions with small groups to explore opinions and attitudes.
- Observations: Direct monitoring of behavior in natural settings.
- Case Studies: In-depth investigations of specific instances or scenarios.
- Ethnography: Immersive study of cultures or groups in their natural environment, aiming to understand how people see and interact with the world around them.
Qualitative research is especially useful when you want to explore a topic deeply, understand customer language, develop hypotheses, or uncover motivations that may not be obvious in numerical data.
For example, before designing a survey about pet food purchasing behavior, a brand may conduct interviews with pet owners to understand how they define “healthy”, what ingredients they avoid, and who influences their buying decisions.
For example, before designing a survey about pet food purchasing behavior, a brand may conduct interviews with pet owners to understand how they define “healthy”, what ingredients they avoid, and who influences their buying decisions.
2. Quantitative Research
This research type deals with numerical data and statistical analysis to identify patterns and trends. It offers measurable results that can be generalized, though it may overlook deeper contextual details. It includes:
a. Descriptive Research: This aims to accurately and systematically describe a population, situation, or phenomenon. It focuses on answering the questions of what, where, when, and how. (e.g., Surveys, Observational Studies). Two common types are:
- Surveys: Structured questionnaires to collect data from a large number of respondents.
- Observational Studies: Systematic observation and recording of behaviors or events.
- Observations: Direct monitoring of behavior in natural settings.
- Case Studies: In-depth investigations of specific instances or scenarios.
- Ethnography: Immersive study of cultures or groups in their natural environment, aiming to understand how people see and interact with the world around them.
b. Causal Research: Also known as explanatory research, it aims to identify cause-and-effect relationships between variables, seeking to determine how one variable affects changes in another. Three types included:
- Ad hoc Research: Ad-hoc research is a one-time study designed to answer a specific question. It is often used for product launches, market entry, concept testing, campaign evaluation, or customer understanding projects.
For example, a beverage company may conduct an ad-hoc study to test consumer interest in a new sugar-free product before launch. - Longitudinal Studies: Longitudinal or tracking research measures changes over time. It is useful when businesses need to monitor brand health, customer satisfaction, awareness, usage, loyalty, or market trends continuously.
For example, a brand tracking study may measure awareness, consideration, preference, and purchase intent every quarter across several countries. - Tracking Studies: Regular measurements of specific variables or metrics over time.
c. Exploratory Quantitative Research: While exploratory research is typically qualitative, there are quantitative methods used in the early stages of research to gather initial insights or test research designs:
- Pilot Studies: Small-scale preliminary studies to test research protocols or methods.
- Feasibility Studies: Assessments to determine the practicality of a proposed project or study.
Secondary Research
Secondary research analyzes existing data from various sources such as industry reports, academic journals, government publications, company records, media articles, public datasets, or competitor websites. It is also divided into qualitative and quantitative research. This method involves analyzing any type of research previously collected by someone else.
Each type of research serves different purposes and can provide valuable insights depending on the specific market research objectives. The choice of method often depends on the research question, available resources, and the type of data required for decision-making.
Secondary research is often useful at the beginning of a project because it helps frame the market context, identify existing knowledge, and refine research questions before investing in primary data collection.
However, secondary data may be outdated, too broad, or not specific enough for your decision. That is why many projects use secondary research first, then primary research to fill knowledge gaps.
Each type of research serves different purposes and can provide valuable insights depending on the specific market research objectives. The choice of method often depends on the research question, available resources, and the type of data required for decision-making.
Secondary research is often useful at the beginning of a project because it helps frame the market context, identify existing knowledge, and refine research questions before investing in primary data collection.
However, secondary data may be outdated, too broad, or not specific enough for your decision. That is why many projects use secondary research first, then primary research to fill knowledge gaps.
Primary vs. Secondary Research: Which Should You Use?
Primary research is best when you need fresh, specific, decision-ready insights from your target audience. Secondary research is best when you need background information, market context, or an initial understanding of a topic.
In practice, the best approach is often a combination of both.
For example, a company entering a new country may first use secondary research to understand population size, category growth, income levels, and competitor presence. Then it may conduct primary research to understand consumer attitudes, brand perceptions, pricing expectations, and purchase barriers.
In practice, the best approach is often a combination of both.
For example, a company entering a new country may first use secondary research to understand population size, category growth, income levels, and competitor presence. Then it may conduct primary research to understand consumer attitudes, brand perceptions, pricing expectations, and purchase barriers.
8 Steps to Do Primary Market Research with Example
Conducting market research is a structured process. The exact design may differ depending on the project, but most primary research follows eight core steps.
1. Define Research Objectives
This is the crucial first step because it sets the direction for your entire research project.
A vague objective such as “understand customers” is too broad. A stronger objective would be: “Identify the main reasons first-time customers do not repurchase within 60 days and determine which improvements would most increase repeat purchase.”
Good research objectives should be:
- Specific
- Linked to a business decision
- Realistic within the available timeline and budget
- Focused on the target audience
- Clear enough to guide methodology and questionnaire design
Start by asking:
- What decision will this research support?
- What do we already know?
- What do we still need to learn?
- Who do we need to hear from?
- What would change based on the findings?
- What level of evidence is required?
2. Design the Research Plan
Once you have clear objectives, the next logical step is to plan how you'll achieve them. This step is critical because it determines the quality and relevance of the data you'll collect. The research plan should define:
- Target audience: Define who should participate in the research. This may include demographics, behaviors, purchase history, job role, location, category usage, income level, or decision-making authority.
For B2B studies, this may include company size, industry, seniority, role in decision-making, and technology usage. For consumer studies, this may include age, gender, region, lifestyle, purchase behavior, or category involvement. - Research Type: Use qualitative research when you need depth, language, motivations, or exploration. Use quantitative research when you need measurement, validation, comparison, or statistical confidence. Use mixed-method research when you need both depth and scale.
- Data Collection Method: Based on your research type, select the appropriate data collection method. For qualitative research, methods like focus groups or in-depth interviews are suitable. For quantitative research, options include online surveys, telephone surveys, face-to-face surveys, or mail surveys. Choose the method that best aligns with your research goals, budget, and timeline.
- Sampling Frame: Define the sampling frame, which is the specific list or database from which your sample will be drawn. This could include customer lists, membership directories, or any relevant group that represents your target population. Ensuring a well-defined sampling frame helps in accurately targeting the individuals who will provide the data you need. Companies can gather quantitative data through their own supplied list of contacts, through social media/website traffic, or through the use of a panel provider who has the ability to target and contact the appropriate respondents for your study’s desired sample group.
- Sampling Methods and Size: Determine how participants will be selected (e.g., random sampling for broad representativeness or targeted sampling for specific insights) and choose between probability sampling or non-probability sampling. Define the sample size needed to ensure the reliability and validity of your results, taking into account factors such as statistical power, confidence level, and practical constraints like budget.
Read the comprehensive guide on survey sampling methods. - Questionnaire or discussion guide: The research instrument should translate objectives into clear, unbiased questions. Avoid leading wording, double-barreled questions, unnecessary complexity, and questions that respondents cannot realistically answer.
- Data-quality controls: Plan how the study will detect and remove poor-quality responses. This may include attention checks, speed checks, duplicate detection, geo-validation, device fingerprinting, open-end quality review, consistency checks, and fraud detection.
- Data Analysis Strategies: For qualitative data, consider methods such as thematic analysis, content analysis, or grounded theory to uncover patterns and themes in your research. Quantitative data, on the other hand, often requires statistical techniques like regression analysis, factor analysis, or ANOVA to identify trends and relationships. Additionally, decide on the software tools you'll use for data processing, such as SPSS, R, or NVivo, to ensure efficient and accurate analysis.
- Timeline and Budget: Set milestones for each research phase and estimate costs for data collection, analysis, and reporting. Include contingencies for unexpected challenges to maintain flexibility throughout the project.
- Ethical Considerations: Obtain informed consent, ensure data confidentiality, and comply with relevant data protection regulations (e.g., GDPR). Prioritizing ethics enhances the credibility of your findings and protects your participants.
A research plan should not be treated as an admin document. It is the blueprint that protects the quality of the entire project.
Learn more about a detailed guide on how to create a sampling plan for research projects!
3. Collect Data
Data collection is where the research plan becomes real. The goal is to gather responses from the right audience while maintaining quality, consistency, and ethical standards. For online research, this stage typically includes:
- Programming the survey: to turn the approved questionnaire into a working online survey. This includes building the questions into a survey platform, setting up response options, adding skip logic, randomization, quotas, validation rules, and redirects. You have to make sure the survey is easy to complete on different devices, especially mobile phones.
- Testing survey logic: soft testing, quality assurance, or survey logic testing. The goal is to check whether the survey works exactly as intended.
For example, if the survey is only for people who bought pet food in the last three months, respondents who answer “No” should be screened out. If the survey includes separate sections for dog owners and cat owners, each respondent should only see the questions relevant to them. - Checking translations for multi-country studies: a questionnaire should not simply be translated word for word. It must be localized so that respondents in each market understand the question in the same intended way. If respondents in different countries understand the same question differently, the results may look comparable but measure different things.
- Recruiting online participants / panelists: participants are often recruited through online panels, customer lists, targeted sample sources, or a combination of channels. The key is to recruit people who match the target audience defined in the research plan. For harder-to-reach audiences, such as B2B decision-makers, healthcare professionals, luxury buyers, or niche category users, recruitment requires more careful feasibility checks and fieldwork management. The quality of recruitment has a direct impact on the credibility of the research.
- Launching fieldwork: to open the survey to real respondents. In large research projects, this begins with a soft launch. A soft launch collects a small portion of the total sample first. If issues appear, the team can pause fieldwork, adjust the survey, and relaunch before collecting the full sample.
- Monitoring response quality: online surveys can attract low-quality respondents, bots, duplicate users, or people who rush through the questionnaire without reading carefully. So, response quality must be monitored throughout fieldwork, before they affect the full dataset.
- Managing quotas: control how many respondents are collected from specific groups, such as gender, age, region, income level, product usage, or customer segment. Quota management is important in multi-country research because fieldwork speed can differ significantly by market. Some countries may complete quickly, while others may require more time due to lower incidence rates, stricter targeting, or harder-to-reach audiences.
- Reviewing completion rates: you should review where respondents drop out. If many people quit at the same question, that question may be too difficult, sensitive, repetitive, or poorly formatted.
- Removing fraudulent or low-quality responses: fraud detection tools can support this process, but human review is still important. Some issues are obvious through automated checks, while others require research judgment. Consider implementing bot detection techniques to enhance the integrity of data collected in online surveys.
- Ensuring data privacy and consent: before participating, respondents should understand what data is being collected, how it will be used, and whether their answers will remain confidential or anonymous. You must consider regulations such as GDPR and other local data protection laws depending on where respondents are located.
4. Analyze Data
Data analysis transforms raw information into actionable insights. This phase involves several key steps:
- Data Preparation: Clean and normalize your data, addressing errors, inconsistencies, and missing values. For qualitative data, develop a coding scheme to categorize responses.
- Apply Analytical Techniques follow your research plan: For quantitative data, use statistical methods to identify trends, correlations, and significant differences. For qualitative data, employ techniques like thematic analysis or content analysis to identify recurring themes and patterns.
- Leverage Advanced Analytics: Use market analytics tools to gain deeper insights. This may include segmentation analysis to identify consumer groups, sentiment analysis for understanding emotional responses, or predictive modeling to forecast trends.
Throughout the analysis, use your chosen software tools (e.g., SPSS, R, NVivo) to process and visualize data efficiently. Remember, the goal is not just to describe the data, but to extract meaningful insights that can drive strategic decision-making.
AI can support this stage by helping classify open-ended responses, detect patterns, summarize themes, and speed up data processing. However, human review is still needed to interpret business meaning, cultural nuance, and strategic implications.
AI can support this stage by helping classify open-ended responses, detect patterns, summarize themes, and speed up data processing. However, human review is still needed to interpret business meaning, cultural nuance, and strategic implications.
5. Interpret Findings
While analysis provides data points, interpretation reveals actionable insights. This step bridges the gap between raw data and strategic decision-making.
You need to compare the results against the initial research objectives to determine if they have been met. This process includes evaluating the implications for the business, identifying opportunities, risks, or areas for improvement, and understanding how the data addresses the core problem or opportunity.
To effectively apply these insights, you can focus on:
You need to compare the results against the initial research objectives to determine if they have been met. This process includes evaluating the implications for the business, identifying opportunities, risks, or areas for improvement, and understanding how the data addresses the core problem or opportunity.
To effectively apply these insights, you can focus on:
- Identifying consumer trends that could guide product development.
- Finding gaps in brand perception to inform future marketing campaigns.
- Evaluating ROI of different marketing strategies based on consumer preferences.
The most useful research reports do not simply say “what respondents answered”. They explain what the business should do differently because of those answers.
6. Present Results
Even the best insights are worthless if they're not communicated effectively. This step ensures that your hard work translates into organizational action. Presenting research results involves effectively communicating the research findings to stakeholders to ensure actionable insights are understood and implemented.
Strong reporting should be visual, structured, and decision-oriented. Automated charting, dashboards, and standardized reporting outputs can help you move faster, especially in multi-country or recurring studies where consistency matters.
Tailor your presentation to the audience. Senior leaders usually need strategic implications and decision guidance. Product teams may need feature-level feedback. Marketing teams may need audience, message, and channel insights. Data teams may need technical details and raw tables.
At TGM, reporting is not only about producing charts. The goal is to help teams understand the voice of the customer, compare markets or segments clearly, and move from data to action with confidence.
Strong reporting should be visual, structured, and decision-oriented. Automated charting, dashboards, and standardized reporting outputs can help you move faster, especially in multi-country or recurring studies where consistency matters.
Tailor your presentation to the audience. Senior leaders usually need strategic implications and decision guidance. Product teams may need feature-level feedback. Marketing teams may need audience, message, and channel insights. Data teams may need technical details and raw tables.
At TGM, reporting is not only about producing charts. The goal is to help teams understand the voice of the customer, compare markets or segments clearly, and move from data to action with confidence.
7. Make Decisions
The purpose of market research is to support better decisions. Once the findings are clear, the business must decide how to act.
Research can influence decisions such as:
- Launch, delay, or reject a product
- Adjust product features
- Change pricing strategy
- Reposition a brand
- Enter or avoid a market
- Prioritize one customer segment over another
- Refine marketing messages
- Improve customer experience
- Invest in specific channels
- Redesign packaging or claims
- Strengthen competitive differentiation
Research should not replace business judgment. It should improve it.
- Refine your target audience based on research findings.
- Adjust your marketing mix to better resonate with consumer preferences.
- Develop new campaign concepts that align with discovered consumer motivations.
8. Evaluate and Refine
The market research process doesn't end with implementation. This final step ensures continuous improvement and keeps your strategies aligned with evolving market conditions. Assess the effectiveness of your research-driven strategies:
- Set up KPIs to measure the impact of new marketing initiatives.
- Conduct follow-up research to track changes in consumer perceptions over time.
- Use A/B testing to refine marketing messages based on ongoing consumer feedback.
Additionally, gathering feedback from stakeholders and participants can provide valuable insights into the research process and outcomes. Lessons learned should be documented and used to refine research methods and processes.
How to Use AI to Do Market Research
AI can be leveraged across different stages of conducting market research:
- Data Collection: AI improves data collection by creating adaptive, conversational surveys. For example, Open AI’s GPT-3 model can generate dynamic, conversational surveys that adapt to respondents' inputs in real-time.
To ensure high-quality data collection, advanced tools like Research Shield can be used to identify low-quality or fraudulent respondents that may skew the results. - Data Management: AI streamlines tasks such as data cleaning and privacy protection. For instance, Synthesized automatically removes personal data (PII) while maintaining data quality,
- Data Analysis: AI excels in analyzing both structured and unstructured data at scale. Natural language processing can perform sentiment analysis on open-ended survey responses or social media data.
- Data Visualization and Reporting: AI-powered tools, such as Tableau, can transform complex data into clear, compelling visualizations and reports.
- Insight Synthesis and Accessibility: AI can combine information to create comprehensive insights. For example, Arria NLG's platform gathers data from various sources into easy-to-read summaries, ensuring insights are accessible to all levels of decision-makers in an organization.
- Contingency Planning: Prepare for unforeseen challenges with a contingency plan, including budget reserves and backup team members to maintain project continuity.
By integrating AI into these key areas of market research, businesses can enhance the speed, depth, and actionability of their research efforts. However, remember that AI should complement, not replace, human expertise. The most effective market research strategies combine AI's analytical power with human insight and interpretation. Explore more about the impact of AI on market research.
Using AI in market research also involves challenges, particularly in ensuring data integrity and the ethical use of AI. Data integrity involves maintaining the accuracy and reliability of information, while ethical use ensures that AI applications respect participant privacy and comply with relevant regulations. At TGM Research, we prioritize safety and uphold ethical standards in our AI-driven methodologies. Below are the key safety precautions we implement:
Using AI in market research also involves challenges, particularly in ensuring data integrity and the ethical use of AI. Data integrity involves maintaining the accuracy and reliability of information, while ethical use ensures that AI applications respect participant privacy and comply with relevant regulations. At TGM Research, we prioritize safety and uphold ethical standards in our AI-driven methodologies. Below are the key safety precautions we implement:
- Data Security: Use encryption and access controls to protect sensitive data, ensuring compliance with regulations like GDPR.
- Ethical Principles: Adopts explicit ethical guidelines that prioritize human oversight, fairness, explainability, and societal impact.
- Human Oversight: Implement human-in-the-loop systems to review AI outputs, catching errors and biases before sharing insights.
- Rigorous Testing: Verifies and validates AI outputs against internal benchmarks and real-world outcomes, continuously monitoring for accuracy and bias.
- Transparency: Clearly documents and labels AI-generated content, providing clients with insights into AI methodologies and limitations.
- Data Quality Monitoring: Maintains strict data quality controls, including provenance tracking and de-identification of personal data.
- Monitoring and Testing: Continuously assess AI models for accuracy and bias, retraining them as needed to align with evolving data.
- Client Communication: Clearly explain AI usage in research processes, including limitations and areas of human oversight.
- Incident Response Plan: Prepare a plan for responding to data breaches, including notification procedures and corrective actions.
For more insights, explore our comprehensive responses to ESOMAR’s 20 Questions on AI services.
10 Most Common Market Research Mistakes to Avoid
Effective market research is key to driving strategic business decisions, but common pitfalls can undermine its impact. Here are the 10 key mistakes to watch out for:
- Unclear Objectives: Failing to define specific, measurable goals for your research.
- Sampling Bias: Allowing certain groups to be over or underrepresented in your study, leading to skewed results.
- Ambiguous Questions: Using imprecise or leading questions that can be misinterpreted or influence responses.
- Ignoring Qualitative Data: Relying solely on quantitative data and missing out on valuable insights from open-ended responses.
- Inadequate Sample Size: Using a sample too small to provide statistically significant results.
- Overlooking Secondary Research: Focusing only on primary research and missing valuable existing data.
- Poor Data Analysis: Misinterpreting data or drawing incorrect conclusions due to inadequate analysis techniques.
- Confirmation Bias: Seeking only information that confirms pre-existing beliefs or hypotheses.
- Neglecting to Act on Insights: Failing to implement changes based on research findings.
- Over-Surveying: Bombarding customers with too many surveys, leading to fatigue and low-quality responses.
11 Best Practices to Conduct Successfully a Market Research Project
Adhering to best practices help collect accurate data, draw meaningful insights, and provide actionable recommendations. Here are important considerations to follow when conducting market research:
- Prioritize Data Quality and Integrity: Data quality is paramount for reliable insights. Ensure your sources are credible, and implement stringent quality control measures during data collection to avoid bias or inaccuracies.
- Choose the Right Methodology: Select research methods (surveys, interviews, focus groups etc.) that best fit your objectives and target audience.
- Ensure Representative Sampling: Use appropriate sampling techniques to accurately represent your target population.
- Use a Mix of Research Methods: Balance qualitative and quantitative research to capture a comprehensive view. Qualitative methods like interviews and focus groups offer deeper insights into consumer behavior, while quantitative methods provide broad, data-driven trends.
- Consider Cultural Differences: If you’re researching in different regions or demographic groups, cultural sensitivity is crucial. Tailor your research questions, communication style, and data interpretation to reflect the values and behaviors of each specific market. For example, in Arab-Islamic cultures, consider the right-to-left reading orientation and avoid images of alcohol or pork when designing surveys.
- Maintain Ethical Standards: Adhering to legal and ethical standards is a must in market research. Be mindful of data privacy regulations such as GDPR or CCPA when collecting personal data, and always obtain informed consent from participants. Ensure your research practices comply with local laws and industry guidelines, maintaining transparency and protecting participant confidentiality.
- Leverage Technology and Advanced Analytics: Incorporate AI tools to streamline data processing and automate repetitive tasks, saving time and improving accuracy. Predictive analytics, sentiment analysis, and trend identification tools provide deeper, more accurate insights, helping you stay ahead of market shifts.
- Focus on Actionable Insights: Market research should result in clear, actionable recommendations. Link your findings to practical business solutions and outline the steps needed to implement them effectively.
- Collaborate with Key Stakeholders: Engage stakeholders from different departments throughout the research process. By collaborating with teams in marketing, product development, strategy, and technical, your research will be more aligned with company objectives and lead to stronger business outcomes.
- Present Findings Clearly and Visually: Present your findings in a clear, visually engaging manner. Use charts, graphs, and infographics is the best way to make complex data easy to understand. A well-structured presentation helps stakeholders quickly grasp key insights and take action.
- Consider Geographic Representation: Decide if it's necessary to collect data from smaller regions separately. To ensure national representativeness, a large sample size is often required. If smaller regions make up only a small portion of the total population, you can combine them with larger neighboring regions to ensure national representativeness and reduce costs. For example, in Indonesia, you might combine Bali with Jawa Barat, Nusa Tenggara Timur (East Nusa Tenggara) with Kalimantan Selatan (South Kalimantan), and Maluku Utara (North Maluku) with Maluku.
For more complex or resource-intensive projects, partnering with experienced market research professionals can save time and improve the efficiency of your research efforts. Contact us.
How Does Market Research Differ Across Countries?
Explore country-specific market research best practices, unique opportunities, and local challenges.
Market Research Guide in Europe
Read more about our guide on How to conduct market research.
Market Research Guide in Africa
Read more about our guide on How to conduct market research.
Market Research Guide in Asia Pacific
Bangladesh
Cambodia
Indonesia
Malaysia
Myanmar
Pakistan
Philippines
Sri Lanka
Thailand
Turkmenistan
Uzbekistan
Vietnam
Read more about our guide on How to conduct market research.
Market Research Guide in The Americas
Read more about our guide on How to conduct market research.
