Marketing Research & Info Systems: Methods, Tools & Decision-Making

Core Concepts & Definitions

1. What is Marketing Research?

Marketing research is the systematic gathering, recording, and analyzing of data about problems related to marketing goods and services. It helps businesses:

• Understand consumer needs.
• Identify market opportunities.
• Reduce risks in decision-making.

Why is it critical? Without research, companies rely on guesswork. For example, Daraz uses customer feedback to refine its product recommendations, while Ncell analyzes call-drop data to improve network coverage.

2. Types of Marketing Research

Marketing research is classified based on purpose, timing, and methodology:

mindmap
  root((Marketing Research))
    Exploratory
      Purpose: "Generate insights"
      Methods: "Focus groups, case studies, pilot surveys"
      Example: "Nepal Tourism Board studying why foreign tourists avoid Chitwan"
    Descriptive
      Purpose: "Describe market characteristics"
      Methods: "Surveys, observational studies"
      Example: "Khalti analyzing user demographics for digital wallet growth"
    Causal
      Purpose: "Test cause-and-effect relationships"
      Methods: "Experiments (A/B testing)"
      Example: "YouTube testing if shorter videos increase watch time"

Key Difference:

3. Marketing Research Process

A structured 5-step approach ensures reliable insights:

flowchart TD
  A["1. Define Problem & Objectives"] --> B["2. Develop Research Plan"]
  B --> C["3. Collect Data"]
  C --> D["4. Analyze Data"]
  D --> E["5. Present Findings & Take Action"]

Step-by-Step Breakdown

1. Define the Problem

   • Example: Nabil Bank wants to know why young customers avoid loans.
   • Tools: SWOT analysis, market trend reports.

2. Develop Research Plan

   • Choose secondary data (existing reports) or primary data (new surveys).
   • Example: eSewa uses government census data (secondary) + customer app feedback (primary).

3. Collect Data

   • Primary Data Sources:
     • Surveys (Google Forms, phone interviews).
     • Observations (e.g., watching how customers use Khalti at a mall).
     • Experiments (e.g., A/B testing ad colors on Facebook for a Nepali brand).
   • Secondary Data Sources:
     • Government reports (Nepal Rastra Bank’s economic data).
     • Industry publications (e.g., Daraz’s annual sales reports).

4. Analyze Data

   • Use statistical tools (SPSS, Excel) to find patterns.
   • Example: NTC analyzes call data to predict network congestion in Pokhara.

5. Present & Act

   • Convert insights into actionable strategies.
   • Example: Himalayan Java uses customer feedback to introduce low-sugar coffee blends.

4. Data Collection Methods

A. Primary Data Collection

B. Secondary Data Collection

• Sources:
  • Internal (company sales records, CRM data).
  • External (government stats, industry reports).
• Example: Nepal Stock Exchange (NEPSE) uses historical stock trends to advise investors.

5. Sampling Techniques

Not every customer can be surveyed! Sampling selects a representative subset.

mindmap
  root((Sampling Methods))
    Probability
      Simple Random: "Every customer has equal chance"
      Stratified: "Divide by groups (e.g., age, income)"
      Cluster: "Divide by regions (e.g., Kathmandu vs. Pokhara)"
    Non-Probability
      Convenience: "Easy-to-reach customers (e.g., mall shoppers)"
      Snowball: "Referrals from initial respondents"
      Quota: "Fixed numbers per group (e.g., 50% male, 50% female)"

Worked Example: Pathao’s Rider Survey

• Problem: Pathao wants to improve wait times in Lalitpur.
• Method: Stratified sampling (dividing riders by income: <Rs. 20k, Rs. 20k–50k, >Rs. 50k).
• Finding: Low-income riders wait longer due to traffic; Pathao introduces express lanes for them.

6. Marketing Information Systems (MIS)

An MIS is a structured system that collects, stores, and analyzes marketing data to support decision-making.

Components of MIS

classDiagram
  class MIS {
    +Internal Reports
    +Marketing Intelligence
    +Marketing Research
    +Decision Support Systems
  }
  class InternalReports {
    +Sales data
    +Customer databases
  }
  class MarketingIntelligence {
    +Competitor analysis
    +Economic trends
  }
  class MarketingResearch {
    +Primary data collection
    +Secondary data analysis
  }
  class DSS {
    +What-if analysis
    +Predictive modeling
  }
  MIS --> InternalReports
  MIS --> MarketingIntelligence
  MIS --> MarketingResearch
  MIS --> DSS

Real-World Example: Google’s MIS

• Internal Reports: Tracks YouTube watch time per country.
• Marketing Intelligence: Monitors TikTok’s growth to adjust ad strategies.
• DSS: Predicts which ads will perform best in Nepal based on past data.

7. Decision Support Systems (DSS) in Marketing

A DSS uses models and algorithms to simulate scenarios. Example:

• NTC uses DSS to predict network demand during Dashain/Tihar.
• Daraz uses DSS to optimize warehouse locations for faster deliveries.

How DSS Works:

1. Input Data (e.g., past sales, weather forecasts).
2. Apply Models (e.g., regression analysis).
3. Generate Insights (e.g., "Stock 20% more diwali items in January").

8. Ethical Considerations in Marketing Research

Unethical practices damage trust. Key guidelines:

• Informed Consent: Customers must know they’re being surveyed.
  • Example: Khalti clearly states in its app that data is used for "service improvement."
• Anonymity: Protect identities in surveys.
• No Deception: Avoid misleading questions (e.g., "Do you hate our product?").
• Data Security: Comply with laws (e.g., Nepal’s Data Privacy Act, 2018).

Case Study: Facebook-Cambridge Analytica Scandal

• What Happened? Cambridge Analytica used unauthorized Facebook data for political targeting.
• Lesson: Always ensure ethical data sourcing.

In the Real World

1. eSewa: Using Primary Research to Improve UX

• Problem: High cart abandonment in the eSewa app.
• Method: A/B testing (Group A saw a "Pay in 3 installments" option; Group B saw none).
• Result: Group A’s conversion rate increased by 18%.
• Impact: eSewa now promotes installment plans for high-ticket items (e.g., smartphones).

2. Ncell: Secondary Data + Predictive Analytics

• Problem: Frequent call drops in hilly areas.
• Method:
  • Secondary Data: Used NTC’s network coverage maps.
  • DSS: Predicted drop zones using call logs and terrain data.
• Solution: Installed additional towers in Dhading and Sindhupalchowk.
• Outcome: Call drop rate reduced by 30% in 6 months.

3. Daraz: Customer Segmentation via Surveys

• Method: Stratified sampling of 10,000 users (divided by age, location, purchase frequency).
• Finding: Millennials in Kathmandu prefer cash-on-delivery, while Lalitpur shoppers use digital wallets.
• Action: Daraz now offers location-based payment options.

Exam Tip: How to Score Full Marks

1. Case Study Analysis (Most Common Question)

• Structure Your Answer:
  1. Problem Identification (What was the issue?).
  2. Research Method Used (Surveys? Experiments?).
  3. Data Collection (Primary/secondary? Sampling technique?).
  4. Findings & Recommendations (How did they solve it?).
• Example Question: "Apple Watch launch case study."
  • Your Answer:

    Apple used exploratory research (focus groups with fitness enthusiasts) to identify demand for a health-focused smartwatch. They collected primary data via surveys and prototypes and secondary data from competitor analysis (Fitbit, Samsung). The causal test (A/B testing watch bands) proved that sleek designs increased sales. Recommendation: Always combine qualitative (focus groups) and quantitative (surveys) data for tech products.

2. Differentiate Between Concepts

• Primary vs. Secondary Data:
  • Primary: Collected firsthand (e.g., NTC interviewing customers about signal issues).
  • Secondary: Existing data (e.g., World Bank reports on Nepal’s GDP growth).
• Proactive vs. Reactive Marketing:

  Proactive	Reactive
  Anticipates trends (e.g., Daraz stocking Diwali gifts in October)	Responds to trends (e.g., Khalti adding UPI after RBI’s push)
  Uses predictive analytics	Relies on past data

3. Short-Answer Tips

• Define Marketing Research:

  "The systematic process of gathering, recording, and analyzing data to solve marketing problems and identify opportunities."

• Components of MIS:

  "1. Internal reports (sales data), 2. Marketing intelligence (competitor trends), 3. Marketing research (primary/secondary data), 4. Decision support systems (predictive modeling)."

Quick Revision Table

Final Note: Marketing research is not just surveys—it’s the backbone of smart decisions. Whether it’s eSewa reducing cart abandonment or Ncell predicting call drops, data drives success. Master the process, know the tools, and apply it to real cases—that’s how you’ll ace the exam!