Indian Institute of Management, Sambalpur

MBA Batch 2023-25

Assignment on Advance Market Research

Submitted to:

Prof. M Dev Prasad Murthy

In partial fulfilment of Advance Market Research Course

“Objective: Market Research Report on Consumer Preferences for Ready-to-Eat and Ready-
to-Cook Foods in India

Submitted by: - Group 11 Section A

Name Roll numbers

Rohit Yelve 2023MBA079
Anshika Rani 2023MBA010
Divyanshi Aggarwal 2023MBA019
Charitha 2023MBA191
Prashanyt Ramola 2023MBA214
Gunjan Yadav 2023MBA257
Shambhavi Sinha 2023MBA292

Date of submission
22nd September 2024
Table of Contents
Executive Summary ............................................................................................................................... 2
Introduction............................................................................................................................................ 3
Ready to Eat ...................................................................................................................................... 3
Ready to Cook ................................................................................................................................... 3
Industry Overview .................................................................................................................................. 3
Industry Trends ...................................................................................................................................... 4
Research Problem and Objectives ......................................................................................................... 9
Research Background ............................................................................................................................ 9
RESEARCH PHILOSPHY ............................................................................................................. 9
RESEARCH APPROACH............................................................................................................... 9
RESEARCH DESIGN ...................................................................................................................... 9
Research Methodology ........................................................................................................................... 9
MIXED METHOD ........................................................................................................................... 9
Quantitative Methodologies: ....................................................................................................... 9
Qualitative Methodologies:........................................................................................................ 10
Questionnaire Factor Analysis ............................................................................................................ 11
Questionnaire Conjoint Analysis ......................................................................................................... 12
Questionnaire Cluster Analysis ........................................................................................................... 12
Responses ............................................................................................................................................. 13
Anova Test ............................................................................................................................................ 15
Bonferroni Test for Packaging and Healthiness .......................................................................... 16
CHI SQUARE TEST ........................................................................................................................... 19
CONJOINT ANALYSIS....................................................................................................................... 20
FACTOR ANALYSIS ........................................................................................................................... 21
Kaiser-Meyer-Olkin (KMO) Measure: ......................................................................................... 21
Bartlett’s Test of Sphericity: .......................................................................................................... 21
Communalities Analysis: ................................................................................................................ 23
The Principal Component Analysis (PCA): ................................................................................. 23
FACTOR LOADING...................................................................................................................... 24
CLUSTER ANALYSIS ......................................................................................................................... 24
Key Findings………………………………………………………………………………………..30
Conclusion…………………………………………………………………………………………..31

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 Executive Summary
Consumer behavior, preferences, and market dynamics in the Ready-to-Eat (RTE) and
Ready-to-Cook (RTC) snack food categories of India are explored in this report. Applying
quantitative surveys and qualitative interviews, consumer values for taste, health, price,
brand, convenience, and packaging are influenced by income, lifestyle, and consciousness
towards health. The research indicates that, for packaging, convenience, and health, all these
are critical drivers of purchase decisions in which consumers show significant variations in
their preferences along the income groups. Higher-income consumers tend to emphasize
healthiness, with lower-income groups putting greater emphasis on packaging.

Statistical analysis, including ANOVA, shows nonsignificant differences in taste and

convenience preferences. Packaging and healthiness also varied across groups, but to a larger
extent for the higher-income consumers, who were found to pay a premium for health
attributes. Post-hoc tests using Bonferroni reveal further differences, mainly between the
"Above ₹1,00,000" and "Below ₹25,000" income groups. Qualitative insights saw health
consciousness and convenience at the top of the snack decision-making process. Health
consciousness and convenience dominate, particularly in campus environments, where social
influences feature prominently.

The outcomes highlight significant areas for manufacturers and marketers. Regarding product
positioning, health-conscious products may focus on the high-income groups, whereas
attractive and low-cost packaging may better cover the budget-conscious groups. To that end,
specific marketing strategies need to be developed considering these heterogeneous needs.
Winning competitively relevant products in the areas of personalized RTE products and eco-
friendly packaging also catches up with emerging consumer trends. Altogether, it is a very
good study to offer great insights to players in improving their approaches for growing RTE
and RTC snack markets and their further expansion into new regions and demographic
segments.

2
 Introduction

Ready-to-Eat (RTE) Foods and Ready-to-Cook (RTC) Foods are two categories of
convenience foods designed to save time in meal preparation.

Ready to Eat
RTE foods are pre-cooked, processed, or prepared foods that can be consumed directly
without further cooking or preparation. They often require minimal or no heating before
consumption.
Example: Instant Noodles, Packaged Snacks, Canned Foods, Frozen Meals, etc.

Ready to Cook
RTC foods are partially prepared and require minimal cooking or assembly before they are
ready to be eaten. These products save time but still allow the consumer to have some control
over the final preparation.
Example: Instant Soup Mixes, Pasta and Noodle Kits, Frozen Parathas and Rotis, Microwave
Popcorn, etc.

Industry Overview

1. Consumer Behavior and Motivations

• Cultural Factors: How do cultural preferences and traditions influence RTE
consumption? Are there regional variations?
• Lifestyle Changes: How have changing lifestyles (e.g., single-person
households, busy professionals) impacted the demand for RTE products?
• Health Consciousness: What are the specific health concerns driving RTE
consumption? Are there trends towards organic, low-sodium, or gluten-free options?
2. Market Segmentation and Targeting
• Demographic Segmentation: Analyze the RTE market based on age, gender, income
level, and geographic location.
• Psychographic Segmentation: Identify consumer segments based on
lifestyle, values, and attitudes towards food.
• Behavioral Segmentation: Segment the market based on usage rate, brand loyalty, and
purchase behavior.
3. Competitive Landscape
• Major Players: Analyze the market share, product offerings, and strategies of key
players in the RTE industry.
• Emerging Trends: Identify new entrants and innovative products that could disrupt the
market.
• Competitive Advantages: Evaluate the competitive advantages of different RTE
brands, such as product quality, branding, and distribution channels.
4. Technological Advancements
• Packaging Innovation: Explore advancements in packaging technology that can
improve product shelf life, convenience, and sustainability.
• Food Preservation: Analyze emerging techniques for preserving food without
compromising taste or nutritional value.

3
 • E-commerce Integration: Assess the impact of e-commerce on the RTE
market, including online ordering, delivery services, and subscription models.
5. Regulatory and Policy Implications
• Food Safety Standards: Examine the regulatory framework governing RTE
products, including labeling requirements, quality control measures, and safety
standards.
• Government Initiatives: Identify any government programs or policies that could
impact the RTE market,such as subsidies, import-export regulations, or public health
campaigns.
6. Future Trends and Opportunities
• Personalized Nutrition: Explore the potential for personalized RTE products tailored
to individual dietary needs and preferences.
• Sustainable Sourcing: Investigate trends in sustainable sourcing of ingredients and
packaging materials.
• Global Expansion: Analyze opportunities for expanding the RTE market into new
geographic regions.
By addressing these areas, you can develop a more nuanced and insightful analysis of the
RTE market,identifying key trends, challenges, and opportunities for growth.

Industry Trends

Ready To Eat
1. Consumer Behavior and Motivations:
• Health and Wellness:
o Explore the specific health concerns driving the demand for vegetarian and
vegan RTE products. Are there trends towards organic, non-GMO, or plant-
based alternatives?
o Analyze the role of dietary restrictions (e.g., allergies, intolerances) in
influencing consumer choices.
o Investigate the impact of health trends (e.g., ketogenic diet, intermittent
fasting) on the demand for vegetarian and vegan RTE products.
• Ethical Considerations:
o Examine the role of ethical concerns (e.g., animal welfare, environmental
sustainability) in influencing consumer choices.
o Analyze the impact of social media and influencers on promoting plant-based
lifestyles.
• Taste Preferences:
o Identify the key taste preferences of vegetarian and vegan
consumers, including regional variations.
o Explore the demand for authentic and diverse flavors, such as international
cuisines.
2. Market Segmentation and Targeting:
• Demographic Segmentation:
o Analyze the vegetarian and vegan RTE market based on age, gender, income
level, and geographic location.
o Identify specific demographic segments with high growth potential
(e.g., millennials, Gen Z).
• Psychographic Segmentation:

4
 o Identify consumer segments based on lifestyle, values, and attitudes towards
food.
o Explore the demand for convenience, sustainability, and ethical consumption.
• Behavioral Segmentation:
o Segment the market based on usage rate, brand loyalty, and purchase behavior.
o Analyze the preferences of different consumer segments for specific product
types (e.g., breakfast cereals, ready meals, snacks).
3. Competitive Landscape:
• Major Players:
o Analyze the market share, product offerings, and strategies of key players in
the vegetarian and vegan RTE industry.
o Identify the competitive advantages and disadvantages of different brands.
• Emerging Trends:
o Identify new entrants and innovative products that could disrupt the market.
o Explore the potential for mergers, acquisitions, and partnerships among
industry players.
• Competitive Advantages:
o Evaluate the competitive advantages of different RTE brands, such as product
quality, branding,distribution channels, and pricing.
o Analyze the impact of factors like certifications (e.g., vegan, organic) on brand
perception and consumer trust.
4. Technological Advancements:
• Plant-Based Protein:
o Explore advancements in plant-based protein technology that can enhance the
taste, texture, and nutritional value of vegetarian and vegan RTE products.
o Analyze the potential for alternative protein sources (e.g., insects, algae) in the
RTE market.
• Food Preservation:
o Investigate emerging techniques for preserving food without compromising
taste or nutritional value.
o Explore the use of innovative packaging materials to extend shelf life and
reduce food waste.
• Digital Technology:
o Analyze the impact of digital technology on the RTE market, including e-
commerce, online ordering, and personalized recommendations.
o Explore the use of artificial intelligence and data analytics to improve product
development and marketing.
5. Regulatory and Policy Implications:
• Food Safety Standards:
o Examine the regulatory framework governing vegetarian and vegan RTE
products, including labeling requirements, quality control measures, and safety
standards.
o Analyze the impact of food safety incidents or recalls on consumer
confidence.
• Government Initiatives:
o Identify any government programs or policies that could impact the
market, such as subsidies, import-export regulations, or public health
campaigns.
o Assess the potential for government support for plant-based food production
and consumption.

5
 • Sustainability Standards:
o Explore the role of sustainability standards (e.g., carbon footprint, water
usage) in influencing consumer choices and industry practices.
o Analyze the impact of sustainability certifications on brand reputation and
market positioning.
6. Future Trends and Opportunities:
• Personalized Nutrition:
o Explore the potential for personalized vegetarian and vegan RTE products
tailored to individual dietary needs and preferences.
o Analyze the role of genomics and nutrigenomics in driving personalized
nutrition trends.
• Sustainable Sourcing:
o Investigate trends in sustainable sourcing of ingredients and packaging
materials.
o Explore the potential for regenerative agriculture and ethical sourcing
practices.
• Global Expansion:
o Analyze opportunities for expanding the vegetarian and vegan RTE market
into new geographic regions.
o Identify cultural and regulatory challenges in different markets.

Ready to cook

Enhancing and Expanding Your Analysis of the Ready-to-Cook (RTC) Market in India
Building on the provided insights, here are some areas to delve deeper into to create a more
comprehensive and impactful analysis:
1. Consumer Behavior and Motivations:
• Lifestyle Changes:
o Analyze the impact of changing lifestyles (e.g., single-person
households, busy professionals) on the demand for RTC products.
o Investigate the role of time-saving and convenience in consumer decision-
making.
• Health Consciousness:
o Explore the demand for healthier RTC options, such as products with reduced
sodium, sugar, or artificial additives.
o Analyze the impact of dietary trends (e.g., gluten-free, vegan) on the RTC
market.
• Cultural Factors:
o Identify cultural preferences and regional variations in RTC consumption.
o Explore the acceptance of foreign cuisines and international brands.
2. Market Segmentation and Targeting:
• Demographic Segmentation:
o Analyze the RTC market based on age, gender, income level, and geographic
location.
o Identify specific demographic segments with high growth potential
(e.g., millennials, Gen Z).
• Psychographic Segmentation:
o Identify consumer segments based on lifestyle, values, and attitudes towards
food.
o Explore the demand for convenience, sustainability, and ethical consumption.

6
 • Behavioral Segmentation:
o Segment the market based on usage rate, brand loyalty, and purchase behavior.
o Analyze the preferences of different consumer segments for specific product
types (e.g., instant noodles,pasta, snacks).
3. Competitive Landscape:
• Major Players:
o Analyze the market share, product offerings, and strategies of key players in
the RTC industry in India.
o Identify the competitive advantages and disadvantages of different brands.
• Emerging Trends:
o Identify new entrants and innovative products that could disrupt the market.
o Explore the potential for mergers, acquisitions, and partnerships among
industry players.
• Competitive Advantages:
o Evaluate the competitive advantages of different RTC brands, such as product
quality, branding,distribution channels, and pricing.
o Analyze the impact of factors like certifications (e.g., organic, non-GMO) on
brand perception and consumer trust.
4. Technological Advancements:
• Food Preservation:
o Investigate emerging techniques for preserving food without compromising
taste or nutritional value.
o Explore the use of innovative packaging materials to extend shelf life and
reduce food waste.
• Digital Technology:
o Analyze the impact of digital technology on the RTC market, including e-
commerce, online ordering, and personalized recommendations.
o Explore the use of artificial intelligence and data analytics to improve product
development and marketing.
• Supply Chain Management:
o Evaluate the efficiency and effectiveness of the supply chain for RTC products
in India.
o Identify potential challenges and opportunities for improving supply chain
management.
5. Regulatory and Policy Implications:
1. Food Safety Standards:
o Examine the regulatory framework governing RTC products in
India, including labeling requirements,quality control measures, and safety
standards.
o Analyze the impact of food safety incidents or recalls on consumer
confidence.
2. Government Initiatives:
o Identify any government programs or policies that could impact the
market, such as subsidies, import-export regulations, or public health
campaigns.
o Assess the potential for government support for the RTC industry.
3. Sustainability Standards:
o Explore the role of sustainability standards (e.g., carbon footprint, water
usage) in influencing consumer choices and industry practices.

7
 o Analyze the impact of sustainability certifications on brand reputation and
market positioning.
6. Future Trends and Opportunities:
• Personalized Nutrition:
o Explore the potential for personalized RTC products tailored to individual
dietary needs and preferences.
o Analyze the role of genomics and nutrigenomics in driving personalized
nutrition trends.
• Sustainable Sourcing:
o Investigate trends in sustainable sourcing of ingredients and packaging
materials.
o Explore the potential for regenerative agriculture and ethical sourcing
practices.
• Global Expansion:
o Analyze opportunities for expanding the RTC market in India to new
geographic regions.
o Identify cultural and regulatory challenges in different markets.
By addressing these areas, you can develop a more nuanced and insightful analysis of the
RTC market in India, identifying key trends, challenges, and opportunities for growth.

Major Players: Gits Food Products, Mccain Foods India, Haldiram Foods International,
MTR Foods, ITC, Nestle India, Godrej Agrovet, Tata Consumer Products, Venky’s (India), iD
Fresh Food (India).

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 Research Problem and Objectives
The research problem revolves around the limited understanding of how different
consumer groups in India value the various attributes of RTE and RTC snacks. This
study seeks to address this gap by examining consumer choices and trade-offs to inform
manufacturers and marketers on how to better position their products to meet customer needs.

Research Background

Research Philosophy
This study adopts a pragmatic research attitude, acknowledging that both quantitative and
qualitative data are essential to understanding customer preferences and behaviors.
Pragmatism emphasizes flexibility, advocating for multiple methodologies to address
research questions and solve practical problems, ultimately integrating diverse data types to
provide a comprehensive view.

Research Approach
The research is inductive. The research begins with quantitative survey data and qualitative
interview findings. Patterns, themes, and linkages in this data are used to build hypotheses
and insights regarding customer preferences for RTE and RTC meals. This method helps
researchers understand how qualities affect customer decisions and form new hypotheses
from the data.

Research Design
This experiment combines exploratory and descriptive methods. Structured surveys via
Google Forms analyze customer preferences, pricing, healthiness, and convenience on a
broad scale. To explore the subjective experiences and motives behind snack choices, in-
depth interviews are conducted. This mixed-methods approach provides a comprehensive
understanding of customer behaviors.

Research Methodology

Mixed Method
The study combines quantitative (statistical tests and analyses) and qualitative (interviews)
methodologies to investigate RTE and RTC snack consumer behavior.

1. Quantitative Methodologies
The research uses statistical methods to analyze customer preferences and behaviours,
compare group means, assess variable relationships, and evaluate product attribute
significance to identify patterns and trends for product development and marketing.

9
 2. Qualitative Methodologies
In-depth interviews uncover customer motives and preferences, enriching statistical
data. This qualitative method provides detailed consumer profiles, contextualizing
quantitative findings for a more comprehensive view of consumer behavior.

Qualitative Questionnaire

1. Please provide your age, gender, and field of study.

2. How often do you eat snacks outside of the mess?
3. When you do purchase or consume snacks outside the mess, what are the main
reasons behind your choice?
4. What factors are most important to you when choosing RTE or RTC snacks?
Explain why these factors are significant.
5. How do you balance factors like healthiness and convenience when selecting
snacks? Can you provide an example of a recent choice you made and what
influenced it?
6. How does the price of snacks impact your decision-making? Are there specific
price ranges you prefer or avoid?
7. Do you have any preferred brands for snacks? If so, what makes these brands
your choice? How do these brands compare to others you’ve tried?
8. What characteristics define a high-quality snack for you? How do these
characteristics influence your snack choices?
9. Has the packaging of a snack ever influenced your purchase decision? If yes,
how so? What types of packaging do you find appealing or unappealing?
10. How important is the healthiness of a snack to you? Are there specific health-
related factors you look for?
11. How does the convenience of a snack affect your decision to buy it? Can you
give an example of a convenient snack you prefer?
12. In your opinion, how do affordable brands compare with premium brands in
terms of healthiness and overall quality?
13. How does your experience with the mess food influence your snack
preferences outside the mess? For instance, do you seek out different types of
snacks to complement or contrast with what’s available in the mess?
14. Do you feel that the availability of snacks on campus affects your choices?
Are there types of snacks you wish were more readily available?
15. How do social interactions or peer influence impact your snack choices? For
example, do you choose snacks based on what your friends like or
recommend?
16. What improvements would you like to see in the snack options available to
you on campus or nearby?
17. Is there anything else about your snack preferences or purchasing behavior
that you’d like to share?

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Quantitative Questionnaire

Factor Analysis

11
Conjoint Analysis

Cluster Analysis

12
Other Demographic and Psychographic Questions

Responses
At the time of analysis we had 81 responses and the analysis is done on the same.

13
 Tests Conducted

Anova Test BASIC MR TESTS Chi-Square Test

Advanced Marketing Research Tests

Conjoint Analysis Factor Analysis Cluster Analysis

14
1. Anova Test

Null Hypothesis (H₀):

H₀: There is no significant difference in the mean attribute (taste, healthiness, price,
brand, convenience and packaging) scores between the different income groups for RTE
Alternative Hypothesis (H₁):
H₁: At least one income group has a significantly different mean attribute (taste,
healthiness, price, brand, convenience and packaging) score compared to the others.

F-Statistic: The F-value is 1.314.

P-Value: The p-value is 0.276.
Since the p-value (0.276) is greater than 0.05, we do not reject the null hypothesis. This
means there is no significant difference in the means of the dependent variable ,i.e, taste
between the income groups.
Compare F-Statistic to F critical:
F crit: The critical value of F for 3 and 77 degrees of freedom at a 0.05 significance level is
2.723.
Since the F-statistic (1.314) is less than F critical (2.723), this confirms that the differences
between the group means are not statistically significant.
Based on the ANOVA results, there is no significant difference in the importance of taste
among the different income groups. The p-value is higher than the standard alpha level
(0.05), and the F-statistic is below the critical F-value.

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F-Statistic: The F-statistic is 0.599, which is less than the critical F-value of 2.723. This
suggests that the variability between the convenience scores of different income groups is not
significantly greater than the variability within each group.

P-Value: The p-value of 0.617 is greater than the standard alpha level of 0.05. This means
there is no significant difference in average convenience scores between the income groups.

No Significant Difference: Since the p-value is greater than 0.05 and the F-statistic is less
than the critical F-value, you do not reject the null hypothesis. This implies that there is no
statistically significant difference in the average convenience scores among the different
income groups.

F-Statistic: The F-statistic is 3.524, which is greater than the critical F-value of 2.723. This
suggests that the variability between the packaging scores of different income groups is
significantly greater than the variability within each group.

P-Value: The p-value of 0.019 is less than the standard alpha level of 0.05. This means there
is a significant difference in average packaging scores between the income groups.

Significant Difference: Since the p-value is less than 0.05 and the F-statistic is greater than
the critical F-value, you reject the null hypothesis. This implies that there is a statistically
significant difference in the average packaging scores among the different income groups.

Bonferroni Test for Packaging

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The only statistically significant difference is between the income groups "Above ₹1,00,000"
and "Below ₹25,000". This indicates that these two groups perceive or behave differently
regarding the factor packaging.

Average of Packaging score for Above ₹1,00,000 is 2.22

Average for Packaging score for Below ₹25,000 is 4.2
This indicated that people with monthly income below 25000 give more importance to
packaging while snacking as compared to above 1,00,000.

F-Statistic: The F-statistic is 1.192, which is less than the critical F-value of 2.723. This
suggests that the variability between the brand ratings of different income groups is not
significantly greater than the variability within each group.

P-Value: The p-value of 0.318 is greater than the standard alpha level of 0.05. This means
there is no significant difference in average brand ratings between the income groups.

No Significant Difference: Since the p-value is greater than 0.05 and the F-statistic is less
than the critical F-value, you do not reject the null hypothesis. This implies that there is no
statistically significant difference in the average brand ratings among the different income
groups.

17
Statistical Significance
F-Statistic: The F-statistic is 1.047, which is less than the critical F-value of 2.723. This
suggests that the variability between the income groups is not significantly greater than the
variability within each group.

P-Value: The p-value of 0.377 is greater than the standard alpha level of 0.05. This means
there is no significant difference in average prices between the income groups.

No Significant Difference: Since the p-value is greater than 0.05 and the F-statistic is less
than the critical F-value, you do not reject the null hypothesis. This implies that there is no
statistically significant difference in the average price factor among the different income
groups.

F-Statistic and p-Value:

F-Statistic: The F-value is 3.108.
P-Value: The p-value is 0.0312.
Since the p-value (0.0312) is less than 0.05, you reject the null hypothesis. This means there
is a statistically significant difference in the mean healthiness scores between at least some of
the income groups.
Compare F-Statistic to F crit:
F crit: The critical value of F for 3 and 77 degrees of freedom at a 0.05 significance level is
2.723.

Since the F-statistic (3.108) is greater than F crit (2.723), the result is significant.

Significant Differences: This indicates that there are significant differences in the
healthiness scores among the different income groups. This suggests that the income group
affects how individuals rate the healthiness of food.

Bonferroni Test for Healthiness

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The only statistically significant difference is between the income groups "Above ₹1,00,000"
and "Below ₹25,000". This indicates that these two groups perceive or behave differently
regarding the factor healthiness

Average of Healthiness score for Above ₹1,00,000 is 3.41

Average for Healthiness score for Below ₹25,000 is 2.2

This indicated that people with monthly income below 25000 give less importance to
healthiness while snacking as compared to above 1,00,000.

2. Chi Square Test

Null Hypothesis (H₀): There is no association between gender and the primary reason for
choosing RTC foods.
Alternative Hypothesis (H₁): There is an association between gender and the primary
reason for choosing RTC foods.

The degrees of freedom (dF) is ((6-1)*(2-1))=5

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Critical value for dF(5) and significance level of 0.05 is 11.07, so we fail to reject the null
hypothesis.

This means there is no significant association between gender and the primary reason for
choosing RTC foods in the data.

3. Conjoint Analysis

The responses were taken on the scale of 1-10 for the 12 product concepts to perform
conjoint analysis. The users were given 12 product concept to rate on the scale of 1-10.
Dummy variables:

• Brand and Price

• x1: (1) when brand is Premium and price is 100-200 else (0)
• x2: (1) when brand is Regular and price is 50-90 else (0)
• x3: (1) when brand is Value and price is 20-50 else (0)
• Healthiness
• x4: (1) when healthiness is High else (0)
• x5: (1) when healthiness is Moderate else (0)
• x6: (1) when healthiness is Low else (0)
• Packaging
• x7: (1) when packaging is Eco-friendly cardboard box else (0)
• x8: (1) when packaging is Resealable pouch else (0)
• x9: (1) when packaging is Single-use plastic bag else (0)

Part-Worths

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 Regression Equation:
Y (Rating) = 5.829 + (-0.993) (Premium) + (0.179)(Regular) +(0.868)(High) +
(0.446)(Moderate) + (1.668)(Eco-friendly) + (0.7571)(Resealable)
The significance of Regression is 0.0079 < 0.05, therefore it is significant.
Since some of the attributes have p-value > 0.05, hence the significant attributes are:
Premium, High, Eco-friendly packaging, Resealable pouch

Consumer Perceived Value

Concept Perceived Value Concept Perceived Value

Concept 1 7.373 Concept 7 6.4621
Concept 2 6.5861 Concept 8 5.829
Concept 3 6.5861 Concept 9 6.5861
Concept 4 6.504 Concept 10 4.836
Concept 5 7.4551 Concept 11 5.829
Concept 6 5.829 Concept 12 5.829

From the above consumer perceived value we can say that concept 5 which is Regular
Brand (Rs 50-90), High Healthiness and Resealable pouch is the most valued
combination which consumer will prefer and concept 10 which is Premium Brand (Rs
100-200, Moderate Healthiness and Single use plastic) is the least preferred
combination.

4. Factor Analysis

Kaiser-Meyer-Olkin (KMO) Measure

The KMO value of 0.836 suggests that data has a high degree of sampling adequacy,
which is needed for performing factor analysis. Values above 0.6 are considered
acceptable, with higher values indicating better suitability.

Bartlett’s Test of Sphericity

The p-value of 0.000 is highly significant, indicating that correlations between
variables are strong and suitable for factor analysis. This confirms that our data is
appropriate for identifying underlying factors.

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22
From the Scree plot we can observe that we have 3 or 4 factor components which have eigen
value more than 1.

The Principal Component Analysis (PCA):

• Initial Analysis: The first four components together account for a substantial portion of
the variance (69.672%).
• After Extraction and Rotation: The first four components retain their significance but
with a clearer explanation of the data's structure, focusing on how these components
contribute to the overall variance.
Since 4 factors explain the most amount of variance(variance increased by almost 12% when
4 th component was added). We will have 4 factor components to do analysis further.

Communalities Analysis
Most variables have high extraction
communalities, indicating that the
extracted factors explain a
substantial amount of variance for
these variables suggesting that the
variables are well-represented by the
factors identified in the analysis.

Since all the factors have

communality>0.5, therefore we will
consider all the items for rotation and
none of the items are dropped at this
point.

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 Since all the items have component value > 0.5 we will consider all the items except
item 7, “The taste of RTE is as per my liking” , since this item is not loaded in any
factor it will be dropped and only 14 items will be considered in factor component.

Factor Loading
The Rotated Component Matrix is analyzing the factors that influence consumers'
preferences
• Component 1: This component seems to be related to health and
nutritional considerations factors. Question 4,6,8 and 11 load
heavily on this component.
• Component 2: This component appears to be associated with price
and value. Question 10,12 and 15 load on this component.
• Component 3: This component seems to be related to brand loyalty
and reputation. Question 5, 9, 13 and 14 load heavily on this
component.
• Component 4: This component appears to be associated with
convenience and time-saving. Question 1, 2 and 3 load on this
component.
Overall, the analysis suggests that consumers' preferences for RTE and RTC foods are
influenced by a combination of factors, including convenience, health, price, and
brand loyalty.

5. Cluster Analysis
We are doing cluster analysis at last so that business can know which people they should
target which marketing the RTE and RTC food.
81 responses on different items were considered to do cluster analysis. Initially the
clusters were made wherein cluster 1 had all the rating as 5 and cluster 2 had rating 1.

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We have 81 cases for the analysis and all the cases were valid in the analysis and there were
no missing cases as seen from the above table.

We can see that all the 81 cases have been used in

forming the clusters wherein the cluster 1 has 67
cases and cluster 2 has 14 cases
Cluster Distribution: The majority of cases (83%)
belong to Cluster 1, while a smaller portion (17%) is
assigned to Cluster 2.

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Average Linkage (Between Groups)

Agglomeration Schedule
Stage Cluster First
Cluster Combined Appears
Stage Cluster 1 Cluster 2 Coefficients Cluster 1 Cluster 2 Next Stage
1 3 37 .000 0 0 24
2 34 36 .000 0 0 3
3 16 34 .000 0 2 4
4 9 16 .000 0 3 5
5 9 45 1.129 4 0 7
6 69 72 1.192 0 0 11
7 9 65 2.481 5 0 23
8 5 75 4.002 0 0 9
9 5 43 5.100 8 0 19
10 22 58 5.505 0 0 41

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11 23 69 6.020 0 6 15
12 17 81 6.164 0 0 32
13 21 50 6.224 0 0 38
14 40 60 6.233 0 0 44
15 23 31 6.478 11 0 26
16 48 64 7.006 0 0 25
17 41 49 7.055 0 0 28
18 14 78 7.165 0 0 28
19 5 38 7.356 9 0 22
20 7 79 8.140 0 0 32
21 25 74 8.147 0 0 39
22 5 70 8.160 19 0 26
23 2 9 8.245 0 7 29
24 3 28 8.791 1 0 69
25 46 48 8.814 0 16 29
26 5 23 9.047 22 15 37
27 27 68 9.210 0 0 52
28 14 41 9.605 18 17 40
29 2 46 9.737 23 25 34
30 11 76 10.000 0 0 44
31 19 42 10.046 0 0 50
32 7 17 10.373 20 12 45
33 53 59 11.161 0 0 51
34 2 73 11.321 29 0 38
35 13 77 12.004 0 0 59
36 8 52 12.009 0 0 43
37 5 55 12.048 26 0 48
38 2 21 12.119 34 13 39
39 2 25 12.611 38 21 40
40 2 14 12.878 39 28 48
41 22 24 12.976 10 0 54
42 20 54 13.363 0 0 53
43 8 39 13.645 36 0 55
44 11 40 14.089 30 14 46
45 7 30 14.359 32 0 52
46 11 44 14.369 44 0 70
47 10 51 14.639 0 0 58
48 2 5 14.741 40 37 54
49 6 71 16.107 0 0 62
50 19 56 16.371 31 0 64
51 4 53 17.175 0 33 57
52 7 27 17.416 45 27 55
53 20 62 17.599 42 0 60
54 2 22 19.055 48 41 59
55 7 8 19.894 52 43 61
56 26 57 20.000 0 0 77
57 4 33 21.366 51 0 63
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58 10 63 21.444 47 0 65
59 2 13 21.994 54 35 62
60 1 20 22.981 0 53 67
61 7 29 23.323 55 0 66
62 2 6 24.114 59 49 65
63 4 15 25.549 57 0 69
64 19 66 26.281 50 0 71
65 2 10 26.610 62 58 67
66 7 67 28.218 61 0 72
67 1 2 28.629 60 65 70
68 18 32 28.851 0 0 73
69 3 4 29.372 24 63 74
70 1 11 29.576 67 46 71
71 1 19 30.630 70 64 72
72 1 7 34.723 71 66 75
73 18 61 36.229 68 0 75
74 3 80 37.065 69 0 80
75 1 18 44.875 72 73 76
76 1 47 46.220 75 0 77
77 1 26 46.437 76 56 79
78 12 35 53.372 0 0 79
79 1 12 65.937 77 78 80
80 1 3 75.390 79 74 0

In an agglomeration schedule, a significant jump in the coefficients column indicates the

formation of distinct clusters. For identifying the point where the data splits into two clusters,
we should look for the largest gap in the coefficients.
In this schedule, the largest jump occurs between stages 74 and 75, where the coefficient
jumps from 37.065 to 44.875. This indicates the formation of two distinct clusters at stage
74.

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From the Anova table we can see that all the attributes has significance<0.05 which make all
the attributes significant for the cluster analysis.

• Cluster 1: Scores of 5 indicate that individuals in this cluster rate all the factors as highly
important when choosing snacks
• Cluster 2: Scores of 2 indicate that individuals in this cluster rate all the factors as not
important or less important when choosing snacks
Insights
• Cluster 1:
Profile: Individuals in this cluster rate all factors related to convenience, healthiness,
taste, quality, price sensitivity, brand loyalty, and promotional influence as highly
important. They place significant value on the ease of preparation, nutritional content,
variety, and overall quality of the food.
Implications: Marketing strategies should emphasize these key factors. For RTE
foods, highlight their convenience, quick preparation, and variety of flavors. For RTC
foods, focus on the health benefits, control over ingredients, and value for money.
Tailoring promotions to align with their sensitivity to price and brand loyalty can also
be effective.
• Cluster 2
Profile: Individuals in this cluster rate the same factors as less important. They may
not prioritize convenience, nutritional content, taste, or brand reputation as much as
the other cluster.

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 Implications: This group may be less concerned with the attributes typically
associated with RTE and RTC foods or may have different priorities that aren't
captured by the current factors. Further research could help uncover their specific
preferences and needs, potentially leading to more targeted product development or
marketing strategies.

Key Findings

- The demand for high-protein RTE products is rising among fitness enthusiasts.
- The working population's growth has increased the demand for easy-to-prepare RTC
products with a long shelf life.
- Two distinct consumer clusters have been identified: one valuing convenience and taste in
RTE foods, and the other prioritizing health benefits and control over ingredients in RTC
foods.
- Price and value perceptions vary moderately among consumers, indicating a need for
targeted marketing strategies.

Implications for Marketing and Product Development

- For Cluster 1, marketing should emphasize the convenience and variety of RTE foods,
highlighting time savings and appealing flavorus.
- For Cluster 2, marketing should focus on the health benefits and ingredient control offered
by RTC foods.
- Manufacturers should consider the moderate F-values for price and value perceptions when
setting prices and communicating value propositions.

Conclusion
The study provides valuable insights into the preferences of Indian consumers for RTE and
RTC snacks, offering actionable recommendations for product development and marketing
strategies. By understanding the importance of brand, price, healthiness, and packaging,
manufacturers and marketers can better align their offerings with consumer needs, ultimately
leading to more successful market positioning.

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