Quick Commerce Trends & Consumer Behaviour in Indore 2026

Impact of Quick Commerce Apps on Buying Behaviour of Households in Indore

Blinkit • Zepto • Swiggy Instamart • BB Now

Aishvi Gandhi

MBA E-Commerce, Xth Semester

Under the guidance of Dr. Sona Fating

146

Indore

April 2026

Institute of Management Studies, Devi Ahilya Vishwavidyalaya

Major Research Project — Aishvi Gandhi

Presentation Overview

Introduction & Significance

Research Objectives

Research Methodology

Quick Commerce Landscape in India

Target Audience & Market Profile

Key Findings & Behavioural Analysis

Hypothesis Testing & Outcome Analysis

Challenges, Recommendations & Conclusion

The Quick Commerce Revolution

Quick commerce has evolved beyond emergency delivery — it is now embedded convenience infrastructure in India

Compresses the distance between need recognition and purchase completion

Reduces the behavioural cost of stepping out, planning ahead, or tolerating stock-outs

India's grocery category is especially susceptible: contains both repetitive staples and low-planning top-up items

Once consumers learn that a shortage can be solved in minutes, inventory discipline inside the home weakens

Why Indore is Analytically Important:

Sits at the intersection of tier-2 urban growth and rising digital familiarity

Strong kirana culture + expanding appetite for on-demand services

Consumers are more value-sensitive and relationship-oriented than metro consumers

Not a simple metro clone — makes findings richer and more nuanced

Quick commerce in Indore is convenience-led, basket-expanding, and household-relevant — but still hybrid rather than fully substitutive.

Why This Study Matters

Significance of Research

1. Industry Growth

• Quick commerce is one of the fastest-scaling layers of Indian retail. • Datum Intelligence 2024 survey: sharp rise in 10-min delivery interest across 10 Indian cities.

2. Platform Scale

• Blinkit (Eternal): millions of monthly transacting customers, hundreds of cities. • Swiggy Instamart: aggressive multi-city dark-store expansion.

3. Indore Context

• Tier-2 city with kirana culture, price-consciousness and digital growth. • Forces a disciplined interpretation beyond standard metro assumptions.

4. Academic Value

• Brings together: convenience orientation, low-involvement purchase triggers, impulse buying. • Focuses heavily on price-value trade-offs and channel coexistence.

This study fills a critical gap: understanding quick commerce behaviour in a high-growth, value-conscious, tier-2 Indian city.

Research Objectives

Dominant Usage Drivers

To identify the reasons driving quick-commerce usage among respondents in Indore.

Impulse Buying Extent

To measure the extent to which quick commerce is associated with impulse buying.

Grocery Budget Impact

To evaluate the perceived impact of quick-commerce usage on monthly grocery budgets.

Categories & Stickiness

To identify the most frequently ordered product categories and platform stickiness across apps.

Convenience Economics

To assess delivery-time expectations, fee sensitivity, and the behavioural economics of convenience.

Retail Displacing Patterns

To determine whether quick commerce is displacing kiranas or coexisting in a hybrid retail pattern.

Research Methodology

Research Design

Descriptive research design

Primary data collection

Structured questionnaire-based survey

Data Collection

146 valid respondents

City: Indore

Questionnaire responses coded and organized into category-wise tables

Analytical Methods

Frequency analysis

Percentage analysis

Midpoint-based descriptive estimation for order-value brackets

One-tailed binomial hypothesis testing

Output

Frequency tables

Cross-tabs

Visualizations

Behavioural propositions tested statistically

Why this methodology is appropriate

The goals are to identify adoption drivers, understand behavioural tendencies, and interpret findings for platform strategy — descriptive-analytical approach is perfectly suited.

Quick Commerce Platforms: The Big Four in India

These are not fringe operations — they represent distinct psychological offers to consumers and are reshaping India's Rs. 7 lakh crore grocery market.

Blinkit

Strong top-of-mind awareness

Dense mainstream convenience identity

Backed by Eternal (formerly Zomato)

Millions of monthly transacting customers

Present in hundreds of cities

Swiggy Instamart

Benefits from ecosystem familiarity

Leverages Swiggy's food delivery network

Multi-city dark-store expansion

Strong urban presence

Zepto

Fast, youth-friendly positioning

Assortment-rich catalogue

10-minute delivery promise

Strong appeal to digitally native users

BB Now

Grocery credibility of BigBasket brand

Trusted for quality and variety

Appeals to household and family segment

Valid Analytical Base: 146 Respondents | City: Indore

Respondent Profile: Who Was Surveyed?

Age Group Distribution

18–25 years

88 (60.3%)

60.3%

26–35 years

37 (25.3%)

25.3%

36–50 years

14 (9.6%)

9.6%

50+ years

7 (4.8%)

4.8%

85.6% of respondents are aged 18–35

Occupational Composition

Student

69 (47.3%)

47.3%

Private/Govt Employee

37 (25.3%)

25.3%

Business/Self-Employed

24 (16.4%)

16.4%

Homemaker

16 (11.0%)

11.0%

72.6% are students or salaried employees

This youth-weighted, digitally fluent sample captures the consumer layer most likely to normalize app-first replenishment. Their habits establish new household expectations.

Why Do People Use Quick Commerce? — Primary Adoption Drivers

CONVENIENCE BEATS DISCOUNTS

What This Means Strategically

Convenience-led users are willing to pay a small premium

They optimize for time recovery, not absolute cheapest price

Platform stickiness is driven by ease, not promotions

Basket expansion happens naturally in low-friction environments

App Preference & Ordering Frequency

Blinkit + Instamart = 76.7%

of primary preference — market has concentration but not monopoly.

Ordering Frequency

83.6% order at least once a week

— quick commerce has crossed the novelty threshold into habitual behaviour.

What Are People Ordering?

Product Categories

Vegetables / Fruits

42 (28.8%)

93.3

Packaged Grocery

36 (24.7%)

80.0

Snacks / Beverages

27 (18.5%)

60.0

Milk / Bread / Eggs

19 (13.0%)

42.2

Personal Care

13 (8.9%)

28.9

Paan / Tobacco items

9 (6.2%)

20.0

“The use case has expanded

BEYOND

emergency replenishment. Vegetables & fruits lead — this is mainstream grocery adoption, not just snack top-ups.”

Fresh produce (28.8%) shows deep

household integration

— not just junk food

Packaged grocery + snacks = 43.2% —

habitual and impulse

categories combined

Category depth signals broader household relevance and

growing platform stickiness

Impulse Buying: The Hidden Engine of Quick Commerce

82.9%

of respondents buy unplanned items — often or sometimes

Yes, often

47.9% (70 respondents)

Sometimes

34.9% (51 respondents)

No, never

17.1% (25 respondents)

The app functions as both fulfilment engine AND demand trigger. When the path from thought to purchase is short, the psychological cost of adding one more item becomes trivial.

Short purchase path

removes friction

encourages unplanned additions

Visual prompts & suggested items

converts browsing into buying

Impulse buying + budget pressure

68.5% report increased grocery spending

Impulse buying is not a side effect — it is a

STRUCTURAL FEATURE

of the quick commerce channel design.

Budget Impact & Spending Behaviour

Budget Impact

68.5% report increased grocery spending after using quick commerce apps

Yes, marginally

48.6%

n=71

No, it is about the same

28.1%

n=41

Yes, significantly

19.9%

n=29

No, I save due to discounts

3.4%

n=5

Average Order Value

~Rs. 291.8 per order

Rs. 200–300

61.0% (n=89)

Rs. 300–400

24.0% (n=35)

Rs. 400–500

11.0% (n=16)

Below Rs. 200

4.1% (n=6)

Monthly Spend Distribution

~Rs. 2,671.2

Rs. 1,000–2,500

41.8% (n=61)

Below Rs. 1,000

21.2% (n=31)

Rs. 5,000+

19.9% (n=29)

Rs. 2,500–4,999

17.1% (n=25)

Quick commerce creates real budget effects. The convenience dividend and impulse leakage are occurring simultaneously — users save time but lose budgeting discipline.

Delivery Time Expectations & Fee Sensitivity

91.8% now consider 30 minutes or less as the ONLY acceptable convenience window

Only 20.5% are willing to pay. 79.5% are conditional or resistant.

Respondents want premium-infrastructure service at mass-market economics. They expect 30-min delivery but resist paying the Rs. 15–30 fee that makes it possible.

Once 30-min delivery becomes the norm, even slight delays feel disproportionate — the expectation itself becomes a competitive liability.

Are Kiranas Being Replaced?

Hybrid Retail Reality

Bulk Staples Preference

Mostly local kirana/supermarket

108 (74.0%)

74%

Mix of both

34 (23.3%)

23.3%

Mostly quick commerce

4 (2.7%)

2.7%

97.3% still rely on kiranas, supermarkets, or mixed channels for bulk staples (rice, wheat, oil, pulses)

Change in Kirana Visits

Not changed

78 (53.4%)

53.4%

Reduced somewhat

49 (33.6%)

33.6%

Reduced significantly

15 (10.3%)

10.3%

Increased

4 (2.7%)

2.7%

Over half of respondents show NO reduction in kirana visits

The Hybrid Model

Quick Commerce

Urgent, fragmented baskets

Impulse purchases

Convenience-driven top-ups

Kiranas

Bulk staples

Trust & relationships

Value-conscious stocking

Credit availability

The evidence does not support displacement. It supports BASKET SEGMENTATION.

Each channel serves a different role in the household's grocery ecosystem.

Hypothesis Testing — Statistical Validation

Hypothesis

Test

Result

p-value

Decision

Convenience is cited significantly more often than discounts

One-tailed binomial

78 out of 94 chose convenience

p = 2.89e-11

Supported

A majority report impulse buying often or sometimes

One-tailed binomial

121 out of 146

p = 1.32e-16

Supported

A majority consider 30 minutes or less acceptable

One-tailed binomial

134 out of 146

p = 1.51e-27

Supported

Bulk staples still sourced mainly via kiranas/mixed mode

One-tailed binomial

142 out of 146

p = 2.09e-37

Supported

Convenience vs discounts

Statistically conclusive

— platform value is about friction reduction, not savings

Impulse majority

82.9% confirms

structural channel-induced spontaneous purchasing

Time compression

Near-unanimous expectation reset

— 30 min is the new grocery standard

Kirana coexistence

Overwhelmingly confirmed

— hybrid structure is stable, not transitional

All four hypotheses are strongly supported at extremely low p-values — the findings are not coincidental but reflect a consistent and robust behavioural pattern.

Pain Points & User Satisfaction

Biggest Problems on Quick Commerce Apps

Delivery fee / surge fee

69 (47.3%)

Higher visible prices

44 (30.1%)

Out-of-stock items

23 (15.8%)

Late delivery

8 (5.5%)

Wrong or missing items

2 (1.4%)

Key Insight

Cost-related frustrations

77.4%

(delivery fee + higher prices) account for 77.4% of all pain points — users are not rejecting the convenience proposition, they are objecting to the

VALUE EQUATION

Overall Satisfaction

3.55

/ 5.0

Satisfaction is moderate — useful enough to retain users but not frictionless enough to stop comparisons

A channel with average satisfaction of 3.55/5 creates a strategically unstable equilibrium: habits are strong, but resentment remains available for competitors to exploit.

Fee transparency

biggest retention lever

Price perception

competitive vulnerability

Operational quality

secondary concern but growing

SUMMARY SNAPSHOT

Key Findings at a Glance

YOUTH-LED

85.6%

Aged 18–35. Digitally fluent, emphasizing app-first behaviour.

CONVENIENCE-FIRST

53.4%

Primary driver is convenience, not discounts (11%). Friction-reducing market.

HABITUAL USE

83.6%

Order at least weekly. Quick commerce is now routine, not an exceptional event.

IMPULSE BUYING

82.9%

Acknowledge impulse purchases. Channel design actively triggers unplanned spending.

BUDGET PRESSURE

68.5%

Report increased grocery spending. Avg order: Rs.291.8 | Monthly: Rs.2,671.

SPEED EXPECTATION

91.8%

Accept only 30 minutes or less. Delivery expectations permanently compressed.

HYBRID STRUCTURE

97.3%

Still use kiranas for bulk staples. Represents coexistence, not market displacement.

Quick commerce in Indore is a normalized convenience layer — not a replacement system.

It has altered timing, impulse, and budgeting while leaving room for kiranas and value-based decision-making.

Recommendations & Strategic Implications

Strengthen Convenience Credibility

Focus platform messaging on ease-of-use and time-saving, not just discount promotions

Transparent Fee Design

Hidden/variable delivery charges create strong resentment; clear upfront pricing improves retention

Budget Management Tools

Offer monthly spend trackers and cart value warnings to reduce invisible leakage and build user trust

Defend Fresh Category

Vegetables, fruits, and packaged grocery lead orders — invest in quality, availability, and freshness perception

Kirana Hybrid Strategy

Kirana retailers should adopt WhatsApp ordering and local delivery to compete selectively in convenience

Segmented Targeting

Students, salaried employees, homemakers, and older users respond to different triggers — personalize the value proposition

Future Research

Extend to joint households, multiple cities, festival-season effects, and platform loyalty subscription dynamics

The core strategic insight: platforms that solve for fee transparency and price perception will deepen loyalty more effectively than any advertising campaign.

Quick commerce in Indore is convenience-led, basket-expanding, and household-relevant — but hybrid rather than fully substitutive.

What the study confirms

Behavioural normalization is real. 83.6% weekly usage, 82.9% impulse buying, and 91.8% compressed time expectations confirm that quick commerce has reshaped grocery habits.

What the study cautions

Kiranas are not displaced. 97.3% still rely on traditional channels for bulk staples. The retail structure remains hybrid and segmented by basket type.

What this means

This is not just a tech story. It is a behavioural economics story about convenience, impulse, budget discipline, and the limits of digital substitution in a value-conscious tier-2 city.

Limitations & Future Scope

Youth-heavy sample → future research should include broader age mix

City-specific → multi-city comparative studies needed

Self-reported data → observational/transactional data would strengthen findings

Festival/seasonal effects, hostel vs family households, loyalty subscriptions — all warrant separate investigation

Aishvi Gandhi

Guide: Dr. Sona Fating

IMS, DAVV

MBA E-Commerce Xth Semester

2026