Consumer Buying Behavior & Decision Rules: Models, Rules & Real Cases

TAKEAWAYS:

• Decision rules (conjunctive, disjunctive, lexicographic) explain how consumers simplify choices under uncertainty, with real-world ties to Daraz’s "minimum cutoffs" (e.g., "4.2+ rating AND under Rs. 2000") and Ncell’s plan comparisons.
• Compensatory vs. non-compensatory models show why a Pathao rider might ignore distance (non-compensatory) but weigh price vs. rating (compensatory) when choosing a ride.
• Consumer heuristics (e.g., "brand loyalty," "price = quality") drive 80% of everyday purchases—visible in Kathmandu’s traffic jams (where drivers default to "most crowded route = safest") or eSewa’s "trusted vendor" badges.
• Organizational buying differs critically from consumer buying in buying centers, negotiation power, and post-purchase evaluation—compare a housewife buying detergent vs. a hotel manager buying bulk towels.
• Decision biases (e.g., anchoring, confirmation bias) explain why Nepali investors overvalue NEPSE stocks based on past peaks or why Daraz shoppers fixate on the first price they see.
• Public policy applications use these rules to design nudge strategies (e.g., NTC’s "default tariff" for prepaid users) or anti-consumerism laws (e.g., banning misleading ads for Himalayan Organics’ "100% natural" claims).

Core Concepts: How Consumers Make Decisions

Consumers rarely evaluate every product attribute equally. Instead, they use decision rules—mental shortcuts—to reduce cognitive load. These rules fall into two broad categories:

1. Compensatory Models: Trade-offs are allowed (e.g., a higher-priced phone with better camera).
2. Non-Compensatory Models: No trade-offs; one failing attribute eliminates the option (e.g., a sunscreen with SPF 30 but "contains parabens" is rejected outright).

1. Types of Consumer Search Activities

Before buying, consumers engage in internal (memory-based) or external (environmental) searches. The depth depends on involvement, risk, and time pressure.

2. Decision Rules in Action: Worked Example

Case: Nabil Bank’s Personal Loan Approval Nabil Bank uses a conjunctive rule for loan approvals with these cutoffs:

• Minimum salary: Rs. 50,000/month
• Credit score: ≥650
• Loan amount: ≤50% of annual income
• Employment stability: ≥1 year at current job

Trace the Decision:

1. Applicant A:
   • Salary: Rs. 60,000 (✅)
   • Credit score: 630 (❌)
   • Result: Rejected (fails credit score cutoff).
2. Applicant B:
   • Salary: Rs. 45,000 (❌)
   • Credit score: 700 (✅)
   • Result: Rejected (fails salary cutoff).
3. Applicant C:
   • Salary: Rs. 70,000 (✅)
   • Credit score: 680 (✅)
   • Loan amount: Rs. 4,000,000 (✅, since 50% of Rs. 840,000 annual income = Rs. 4,200,000)
   • Result: Approved.

Why This Matters: Banks use conjunctive rules to minimize risk. Similarly, Daraz’s "Eligible for Express Delivery" badge uses a conjunctive rule:

• Weight ≤20 kg
• Price ≤Rs. 5,000
• Pin code in delivery zone

3. Compensatory vs. Non-Compensatory Models: A Comparison

4. Heuristics: Mental Shortcuts Consumers Use

Heuristics are rules of thumb that simplify decisions. Common ones include:

5. Consumer vs. Organizational Buying: Key Differences

Organizational buying (e.g., businesses, governments) differs from consumer buying in process, participants, and criteria.

classDiagram
    class ConsumerBuying {
        +Participants: Individual or household
        +Purchase Motive: Personal need/satisfaction
        +Decision Time: Short to medium
        +Evaluation: Subjective (emotions, preferences)
        +Example: Buying a phone for personal use
    }
    class OrganizationalBuying {
        +Participants: Buying center (users, influencers, deciders, gatekeepers)
        +Purchase Motive: Business goals (profit, efficiency)
        +Decision Time: Long (negotiations, contracts)
        +Evaluation: Objective (ROI, specs, vendor reputation)
        +Example: A hotel buying bulk towels from Himalayan Textiles
    }
    ConsumerBuying --> "Uses" DecisionRules
    OrganizationalBuying --> "Uses" DecisionRules

Key Differences Table:

6. Real-World Applications: How Companies Use Decision Rules

Case Study 1: Daraz’s Product Recommendation Algorithm

Daraz uses a hybrid model:

• Non-compensatory: Filters products based on conjunctive rules (e.g., "price ≤Rs. 2000 AND rating ≥4.0").
• Compensatory: Ranks remaining options using a weighted additive rule (e.g., 40% price, 30% rating, 20% shipping speed, 10% brand).

Why It Works:

• Reduces choice overload for shoppers.
• Increases conversion rates by showing only viable options.

Case Study 2: Pathao’s Dynamic Pricing

Pathao uses lexicographic and disjunctive rules:

1. Lexicographic: Prioritize distance (if >5 km, reject).
2. Disjunctive: If driver rating ≥4.8, accept even if slightly more expensive.

Why It Works:

• Matches riders with high-rated drivers (reducing complaints).
• Adjusts prices in high-demand zones (e.g., Thamel during peak hours).

Case Study 3: Nabil Bank’s Credit Card Approval

Nabil Bank uses a compensatory model with weighted scores:

• Income: 40%
• Credit Score: 30%
• Employment Stability: 20%
• Existing Relationship: 10%

Example:

• Applicant X:
  • Income: Rs. 100,000 (✅)
  • Credit Score: 600 (❌, below 650 threshold)
  • Result: Rejected (credit score fails, even with high income).

In the Real World

1. eSewa’s "Trusted Vendor" Badge

   • Idea Used: Availability Heuristic + Social Proof
   • How: eSewa highlights vendors with high transaction volumes and positive feedback, making them seem more reliable. A consumer is more likely to pay Rs. 500 for electricity via a "trusted" vendor than an unknown one, even if prices are similar.

2. Khalti’s "Pay in 3 Installments" Option

   • Idea Used: Lexicographic Rule (Price First)
   • How: Khalti lets users split payments (e.g., Rs. 10,000 in 3 installments). Consumers prioritize immediate affordability over long-term interest costs, using a lexicographic rule: "Can I pay now? If yes, buy."

3. NTC’s Default Tariff for Prepaid Users

   • Idea Used: Default Effect
   • How: NTC sets a default prepaid plan (e.g., Rs. 100 for 1GB). Users often stick with it instead of switching to a better deal (e.g., Rs. 70 for 1.5GB), even though they’d save money.

4. Himalayan Organics’ "Herbal" Marketing

   • Idea Used: Anchoring + Confirmation Bias
   • How: Himalayan Organics anchors their products as "100% natural" in ads. Once consumers accept this frame, they ignore scientific debates about "natural vs. synthetic" ingredients, reinforcing their purchase decision.

5. Daraz’s "Out of Stock" Psychology

   • Idea Used: Scarcity Heuristic
   • How: Daraz shows "Only 3 left in stock!" to trigger urgency. Consumers use a non-compensatory rule: "If it’s scarce, I must want it more."

Exam Tip: How to Score Full Marks

1. For Case Studies (e.g., Himalayan Organics):

   • Structure: Use the STAR method (Situation, Task, Action, Result).
   • Example:

     *"Himalayan Organics uses a disjunctive rule for its ‘Herbal’ line: if a product is ‘certified organic’ OR ‘made with rare Himalayan herbs’, it qualifies for the premium segment. This rule simplifies consumer choice by letting buyers focus on one high-priority attribute (natural ingredients) rather than comparing all chemical compositions."*

2. For Differentiating Terms (e.g., Consumer vs. Organizational Buying):

   • Use a comparison table (as above) and real examples.
   • Avoid: Generic definitions. Instead:

     "While a consumer buying a phone on Daraz might use a lexicographic rule (prioritizing camera quality), a hotel manager buying bulk phones for staff would use a compensatory model, weighing price (40%), warranty (30%), and brand reputation (30%)."

3. For Decision Rules:

   • Always link to a real scenario. For example:

     "A conjunctive rule is used by Ncell when offering free data: ‘If you spend Rs. 500 on calls AND recharge before the 5th of the month, you get 1GB free.’ This ensures only high-value users qualify."

4. For Public Policy Applications:

   • Frame answers around "nudge theory" (Thaler & Sunstein).
   • Example:

     "The Nepali government could use default effects to encourage savings by making NSC (National Savings Certificate) the default retirement plan option in eSewa. Consumers, using the default heuristic, would likely stick with it unless they actively opt out."

5. Avoid Common Mistakes:

   • ❌ "Compensatory models are always better." → Correction: "Compensatory models are better for high-involvement decisions, but non-compensatory rules (like lexicographic) are faster for low-involvement choices like choosing a Pathao ride."
   • ❌ "Heuristics are always bad." → Correction: "Heuristics reduce cognitive load but can lead to biases (e.g., anchoring). Companies like Daraz exploit heuristics (e.g., scarcity) to influence choices."

Quick Revision Checklist

Before the exam, ensure you can: ✅ Define conjunctive, disjunctive, and lexicographic rules with Nepali examples. ✅ Differentiate compensatory vs. non-compensatory models using Daraz/Ncell cases. ✅ Explain 5 heuristics and how eSewa/Khalti use them. ✅ Compare consumer vs. organizational buying with a table + real examples. ✅ Apply decision rules to public policy (e.g., NTC tariffs, NEPSE investments). ✅ Analyze a case study (e.g., Himalayan Organics) using 2+ decision rules.