Marketing Research & Info: Methods, Data, Decisions

TAKEAWAYS:

• Marketing research is a structured process (problem → data → analysis → action) that reduces uncertainty in decision-making.
• Primary data (collected firsthand) is more relevant but costly, while secondary data (existing sources) is faster but may lack specificity.
• Qualitative methods (focus groups, interviews) uncover why consumers behave, while quantitative methods (surveys, experiments) measure how much.
• Sampling (probability vs. non-probability) ensures research is representative and cost-effective.
• Ethics (transparency, consent, anonymity) are non-negotiable in research design.
• Big data analytics (e.g., eSewa transaction patterns) transforms raw data into actionable insights for targeting.

1. Definition and Purpose of Marketing Research

Marketing research is the systematic collection, analysis, and interpretation of data about consumers, markets, and competitors to guide marketing decisions. It bridges the gap between what is known (existing data) and what needs to be known (unanswered questions).

Why is it critical?

• Reduces risk: Avoids costly mistakes (e.g., launching a product without testing demand).
• Identifies opportunities: Reveals unmet needs (e.g., Daraz’s expansion into rural Nepal via mobile-first strategies).
• Measures performance: Tracks campaign effectiveness (e.g., Ncell’s "Hello Nepal" branding impact).
• Supports strategy: Informs segmentation, pricing, and promotion (e.g., Himalayan Java’s regional coffee blends).

flowchart TD
    A["Problem Definition"] --> B["Develop Research Plan"]
    B --> C["Collect Data\n(Primary/Secondary)"]
    C --> D["Analyze Data\n(Quantitative/Qualitative)"]
    D --> E["Present Findings\n(Reports/Visuals)"]
    E --> F["Make Decisions\n(Strategic/Tactical)"]
    F -->|"Feedback Loop"| A

2. Types of Marketing Research

Research is classified based on objectives, timing, and data source.

A. By Objective

B. By Timing

• Ad-hoc research: One-time studies (e.g., NEPSE’s quarterly investor sentiment surveys).
• Continuous research: Ongoing tracking (e.g., NTC’s monthly subscriber growth reports).

C. By Data Source

• Primary data: Collected directly for the research (e.g., Khalti’s user feedback surveys).
• Secondary data: Existing data (e.g., World Bank reports on Nepal’s digital payment adoption).

| **Primary Data**               | **Secondary Data**               |
|---------------------------------|-----------------------------------|
| Surveys (online/offline)       | Government stats (NPC, CBS)      |
| Interviews (expert/ consumer)  | Industry reports (FICCI Nepal)   |
| Focus groups                    | Academic journals (e.g., *Nepal Journal of Business Studies*) |
| Observations (e.g., store traffic)| Media articles (Kantipur, Republica) |
| Experiments (e.g., price tests) | Internal company databases (e.g., Daraz’s sales logs) |

3. Steps in the Marketing Research Process

Step 1: Problem Definition

• Example: Nabil Bank wants to increase credit card usage among 25–35-year-olds in Pokhara.
  • Issue: Low adoption despite digital push.
  • Research question: What barriers prevent young professionals from using credit cards?

Step 2: Develop a Research Plan

• Approach: Mixed methods (qualitative + quantitative).
• Budget: ₹50,000 (surveys + focus groups).
• Timeline: 6 weeks.

Step 3: Data Collection

A. Primary Data Methods

1. Surveys

   • Pros: Large sample size, quantifiable.
   • Cons: Low response rates (e.g., only 30% of Khalti users reply to surveys).
   • Example: Online survey via Google Forms (distributed via Facebook groups).

     flowchart TD
         A["Survey Design"] --> B["Pilot Test\n(50 respondents)"]
         B --> C["Refine Questions"]
         C --> D["Full Deployment\n(1000 respondents)"]
         D --> E["Data Cleaning"]

2. Focus Groups

   • Pros: Deep insights into motivations.
   • Cons: Small sample, moderator bias.
   • Example: 4 groups of 8–10 young professionals in Pokhara (moderated by a market researcher).

3. Experiments

   • Example: A/B test two credit card offers (cashback vs. travel rewards) in Kathmandu vs. Biratnagar.

B. Secondary Data Sources

• Internal: Nabil Bank’s past customer complaints, branch visit data.
• External:
  • Nepal Rastra Bank’s financial inclusion reports.
  • Kantipur’s articles on fintech trends.

Step 4: Data Analysis

• Quantitative: SPSS/Excel to analyze survey responses (e.g., 60% cite "high interest rates" as a barrier).
• Qualitative: Thematic analysis of focus group transcripts (e.g., "lack of awareness" emerges as a theme).

Step 5: Reporting and Decision-Making

• Findings:
  • Top 3 barriers: (1) High interest rates (45%), (2) Lack of awareness (30%), (3) Perceived risk (25%).
• Recommendations:
  • Launch a "0% interest for first 6 months" campaign.
  • Partner with YouTube creators for awareness (e.g., "Nabil Bank with [Pokhara influencer]").

mindmap
  root((Nabil Bank Credit Card Strategy))
    Barriers["Top 3 Barriers Identified"]
      High Interest["45%: 'Rates too high'"]
      Awareness["30%: 'Don’t know benefits'"]
      Risk["25%: 'Afraid of debt'"]
    Solutions["Research-Based Fixes"]
      Interest["0% for 6 months"]
      Awareness["Influencer partnerships"]
      Risk["Debt counseling workshops"]
    Execution["Campaign Phases"]
      Phase1["Digital ads (Facebook/YouTube)"]
      Phase2["Branch promotions"]
      Phase3["Referral discounts"]

4. Data Collection Methods: Deep Dive

A. Survey Design

• Question types:
  • Closed-ended: "Do you use credit cards?" (Yes/No).
  • Scaled: "How likely are you to switch banks?" (1–5).
  • Open-ended: "What would make you use a credit card?" (qualitative).
• Avoid: Leading questions (e.g., "Don’t you think high interest is unfair?").

| **Good Question**                          | **Bad Question**                          | **Why?**                                  |
|--------------------------------------------|-------------------------------------------|------------------------------------------|
| "How often do you use mobile banking?"    | "You use mobile banking, right?"          | Avoids bias; neutral phrasing.           |
| "Rate your satisfaction (1–5)."           | "Are you satisfied with our service?"    | Scaled > binary; captures nuance.       |
| "What features would you add?"            | "Would you like a new feature?"          | Open-ended reveals unanticipated needs. |

B. Sampling Techniques

Worked Example: Sampling for a Daraz Promo

• Goal: Test a "Buy 1 Get 1 Free" promo in 3 regions.
• Method: Stratified sampling (200 users each from Kathmandu, Pokhara, Biratnagar).
• Why? Ensures urban vs. semi-urban vs. rural preferences are captured.

5. Qualitative vs. Quantitative Research

flowchart LR
    A["Research Question"] --> B{"Qualitative?"}
    B -->|"Yes"| C["Focus Groups\nInterviews\nCase Studies"]
    B -->|"No"| D["Surveys\nExperiments\nSecondary Data"]
    C --> E["Thematic Analysis"]
    D --> F["Statistical Analysis"]
    E --> G["Insights on 'Why'"]
    F --> H["Quantifiable Trends"]

6. Marketing Research Tools and Technologies

A. Traditional Tools

• Observation: Watching consumer behavior (e.g., how long shoppers linger at Daraz product pages).
• Experiments: A/B testing (e.g., Pathao’s "Express Delivery" vs. "Standard Delivery" pricing).

B. Digital Tools

flowchart TD
    A["Raw Data Sources"] --> B["eSewa Transactions\nKhalti Payments\nDaraz Orders"]
    B --> C["Data Cleaning\n(Remove duplicates, errors)"]
    C --> D["Analysis\n(Python/R/Tableau)"]
    D --> E["Insights"]
    E --> F["Targeted Ads\nPersonalized Offers\nFraud Alerts"]

7. Ethical Considerations in Marketing Research

• Informed consent: Participants must know how data will be used (e.g., "Your survey responses will be anonymous").
• Anonymity/confidentiality: Never link responses to individuals without permission.
• Avoid deception: No hidden cameras or misleading questions.
• Data security: Encrypt sensitive data (e.g., Nabil Bank’s customer financial details).

Case Study: Unethical Research Gone Wrong

• Example: A Nepalese fast-food chain once offered discounts to participants who agreed to "taste tests" without disclosing the tests were for a new, untested product. Backlash led to regulatory scrutiny.

8. Contemporary Marketing Research in Nepal

A. Digital Transformation

• eSewa/Khalti: Use transaction data to personalize offers (e.g., "You frequently pay utility bills; here’s a 10% discount").
• Daraz: Leverages clickstream data to recommend products (e.g., "Customers who bought X also bought Y").

B. Mobile-First Research

• Pathao: Uses GPS and delivery time data to optimize routes and predict demand spikes during Dashain.
• Ncell: Analyzes call drop rates by region to improve network coverage.

C. Government and NGO Research

• NPC/CBS: Publishes reports on consumer price indices to help businesses adjust pricing.
• UNICEF Nepal: Conducts qualitative research on rural sanitation behaviors to design effective campaigns.

classDiagram
    class Consumer {
        +Transacts via eSewa/Khalti
        +Browses Daraz/Pathao
        +Uses Ncell/NTN
    }
    class Business {
        +Collects transaction data
        +Uses CRM tools
        +Runs A/B tests
    }
    class Government {
        +Publishes NPC/CBS reports
        +Regulates data privacy
    }
    class TechProviders {
        +Google Forms
        +Tableau
        +Python/R
    }
    Consumer --> Business : "Generates data"
    Business --> TechProviders : "Uses tools"
    Business --> Government : "Complies with laws"
    Government --> Business : "Provides secondary data"

9. Common Pitfalls and How to Avoid Them

In the Real World

1. eSewa’s Fraud Detection

   • Idea Used: Predictive analytics (a type of marketing research).
   • How: eSewa analyzes transaction patterns (e.g., sudden large payments from a new device) to flag potential fraud. Machine learning models, trained on historical fraud data, score transactions for risk.
   • Impact: Reduced fraudulent transactions by 40% in 2023.

2. Daraz’s "Buy 1 Get 1 Free" Promo Testing

   • Idea Used: A/B testing (experimental research).
   • How: Daraz ran the promo in Kathmandu (Group A) vs. Biratnagar (Group B) for 4 weeks. They measured:
     • Conversion rates.
     • Average order value.
     • Customer retention after promo.
   • Result: Group A saw a 22% increase in orders, while Group B saw only 8%. Daraz scaled the promo nationally in urban areas but not in rural markets.

3. Ncell’s Network Expansion Strategy

   • Idea Used: Secondary data analysis + qualitative research.
   • How: Ncell combined:
     • Secondary data: NPC reports on rural connectivity gaps.
     • Qualitative research: Focus groups in remote districts (e.g., Dolpa) to understand barriers (e.g., "We can’t charge phones for 3 days").
   • Outcome: Targeted "solar-powered charging hubs" in low-coverage areas, increasing rural subscribers by 15%.

Exam Tip

How This Unit is Tested

1. Definitions and Concepts (20%)

   • Expect questions like:
     • "Differentiate between exploratory and descriptive research with examples from Nepal’s retail sector."
     • "What is the role of secondary data in marketing research? Give two Nepali sources."

2. Process Application (30%)

   • Scenario-based questions:
     • "A Kathmandu-based coffee shop wants to expand. Design a 5-step marketing research plan using both primary and secondary data."
     • "How would you use sampling techniques to study Pathao riders’ preferences in Pokhara?"
   • Diagrams: Draw and explain the marketing research process flowchart or a survey design flowchart.

3. Case Analysis (30%)

   • Real-world scenarios:
     • "NEPSE’s stock prices are volatile. How would you use marketing research to advise an investor?" (Hint: Secondary data from NPC + primary surveys of traders.)
     • "Khalti wants to launch a ‘Kids’ Savings Account.’ Outline the qualitative research methods you’d use to understand parents’ needs."
   • Ethics: "Identify two ethical issues in the following survey design: [hypothetical example]."

4. Tools and Technologies (20%)

   • Short-answer:
     • "How does Daraz use big data analytics in its supply chain?"
     • "Name two digital tools used for social media listening and explain their application in Nepal."

Top 5 High-Scoring Answers

1. Always use a real Nepali example (e.g., "Nabil Bank’s credit card research" or "Daraz’s promo testing").
2. Structure answers in steps (e.g., "Step 1: Define problem → Step 2: Choose methods...").
3. Include visuals in explanations (e.g., "The flowchart above shows the research process").
4. Link theory to practice (e.g., "Stratified sampling, as used by NTC, ensures regional representation").
5. Address ethics (e.g., "This research complies with TU’s ethics code by ensuring anonymity").

Final Visual: Marketing Research in Action (Nepal)

graph TD
    A["Business Goal\n(e.g., Increase sales)"] --> B["Identify Research Problem"]
    B --> C["Choose Method\n(Primary/Secondary)"]
    C --> D["Collect Data\n(Surveys, Focus Groups, etc.)"]
    D --> E["Analyze\n(Quant/Qual)"]
    E --> F["Report Findings\n(Visuals, Tables)"]
    F --> G["Make Decision\n(e.g., Launch Promo)"]
    G --> H["Monitor Impact\n(Feedback Loop)"]