The Fast Moving Consumer Goods (FMCG) industry, which includes products that are vital to consumers' daily lives, has emerged as an indispensable part of India's consumer economy in the contemporary corporate world. This industry has witnessed steady growth in its market despite market volatility due to digitalization, changing consumer behaviour, rising income levels, and rapid urbanization. Transparency in pricing and digital product experiences have emerged as key determinants of contemporary consumer behaviour.

The revolutionary potential which digital technology may possess for sustainable consumption patterns has now been realized. The role of micro celebrity in the formation of consumer attitude in marketing sustainable FMCG products includes the role of care motivations, which is emphasized in the study by Abdur Rouf, Asaduzzaman Babu, Jamal Uddin [1].

The role of data marketing strategies is emphasized in the study by Sadra Ahmadi, Fatemeh Barkhi, S. R. Nikhashemi in pattern recognition of customer loyalty in FMCG using data mining. The revolutionary potential of IoT and blockchain technology in creating intelligent and sustainable supply chains was discussed in a study by Jianhua Gou, Yatong Li, and Alireza Goli. Though Ozlem Ayaz, Seyedeh Asieh Hosseini Tabaghdehi, and Prerna Tambay discussed the ethical impact of digital footprints from the point of view of SME in their study [3], Yiming Yang, Henry F. L. Chung, and Jonathan Elms discussed relational bonds strategy and B2B performance in multi-channel networks in their study.

The importance of trust and moral behaviour in sustainable business is reaffirmed in both studies. Quality, packaging, branding, transparency in terms of nutritional value, digital visibility, and customer interaction in the online space have all been factored into product development. Affordability, competition, real-time promotions, and customization in the digital space have all been factored into pricing. However, there is a scarcity of available empirical data in terms of the direct effect of digital transformative practices in product and pricing strategies in relation to sustainable consumer purchasing behaviour in regional FMCG markets.

This is despite the fact that numerous studies have already been undertaken in relation to digital practices and the effect that it has on consumer behaviour. There is also a disparity in terms of mid-sized FMCG businesses, basic products such as grains and pulses, and regional markets such as Salem. There is very little research that has been undertaken in terms of the effect of transparency in pricing, sustainable consumer behaviour, and digital product strategies in mid-sized businesses.

The organization is in the process of its digital transformation journey in the FMCG industry. Therefore, it is facing a challenging situation. Due to digitalization, prices are becoming transparent. This is giving an opportunity to the customer to compare prices through various digital means. Due to the fluctuating prices of raw materials, it is becoming challenging for the firm to maintain constant prices.

A lot of investment is required in digital quality monitoring systems to fulfill the customer's demand of consuming products in a hygienic manner. At the same time, it is the need of the hour to implement digital branding techniques to make the customer understand the uniqueness of commodity-based products such as pulses. Therefore, it is becoming challenging for the firm to balance digital pricing with product quality. In this context, the study with special reference to Jeyyam Global Foods in Salem aims at evaluating the impact of digital transformational practices in product and price strategies on sustainable customer purchasing behaviour.

The objectives of the study are: (1) to assess the extent to which consumer purchasing behaviour and buying intentions for Jeyyam Global Foods' pulse products in the Salem region are affected by digital product strategy, which includes online branding, digital visibility, quality communication, and product packaging information; (2) to assess the extent to which consumer perceptions of product value and purchasing behaviour in the FMCG pulses category are affected by digital pricing strategy, which includes dynamic pricing and price transparency through e-commerce websites; and (3) to evaluate the overall impact of digital transformational practices in product and price strategies on consumer buying behaviour and customer satisfaction with Jeyyam Global Foods with the aim of creating useful insights.

The focus of the present study is on implementing digitally transformative pricing strategies in Jeyyam Global Foods, Salem. The organization is dealing with pulse products and gram-based products in terms of sustainable consumer behaviour. The prime focus of implementing digital technology with quality products using pricing strategies is customer satisfaction in terms of sustainable consumer behaviour.

RELATED WORKS

The study titled "Influence leads intention: How micro-celebrity endorsement and care motivations influence sustainable consumption" conducted by Abdur Rouf, Asaduzzaman Babu, Jamal Uddin [1] 2026 has proved that micro-celebrity influencers do play an important role in the formation of trust among the consumers. This study also proved that care motivation and influence are effective tools in the formation of sustainable FMCG consumption. The findings of this study can be used as a paradigm shift for the FMCG industry, which can be applied at once in the form of digital marketing.

The paper "An IoT and blockchain-based multi-objective optimization and machine learning framework for intelligent supply chain design" by Jianhua Gou, Yatong Li, and Alireza Goli [2] 2026  proposed a smart supply chain concept that maximizes sustainability, cost, and efficiency using blockchain, IoT, and machine learning technologies. Jeyyam’s ability to meet its obligations to its customers in terms of quality and hygiene is supported by the paper, which emphasized the utilization of technology in creating smart supply chain concepts and supply chain management systems.

The study "Ethical implications of employee and customer digital footprints: SME's perspective" by Ozlem Ayaz, Seyedeh Asieh Hosseini Tabaghdehi, and Prerna Tambay [3] 2025 deals with the ethical implications of the digital information collected from the customers and employees. The importance of digital footprint from the ethical perspective is highlighted in the study. Ethical digital interaction is essential to establish brand credibility for FMCG brands.

The study "Uncovering consumer loyalty behaviour: A data mining approach in the fast-moving consumer goods sector" carried out by Sadra Ahmadi, Fatemeh Barkhi, and S. R. Nikhashemi [4] 2026 highlighted the importance of the application of data mining techniques to understand the trends of consumer loyalty in the FMCG sector. The study also proved the importance of the application of appropriate digital analytics tools to ensure consumer loyalty, which is linked with Jeyyam’s price intelligence.

The research paper titled 'Relational bonds strategy, organizational learning, and B2B performance: The case of multi-channel network' written by Yiming Yang, Henry F. L. Chung, Jonathan Elms proves that if organizational learning is implemented with the concept of relational management, organizational learning could ensure the success of B2B, especially in relation to digital channel strategies in the FMCG sector.

MATERIALS AND METHODS

Research Design

The objective of this particular research study is to assess the effect of digital transformational practices on sustainable consumer purchasing behavior in the FMCG sector. The type of research that is applied in the case of this particular research study is of a descriptive nature. The type of research that is applied while conducting the primary research in the case of this particular research study is the cross-section survey method. The type of research that is applied while conducting the descriptive research is fact-finding questions and survey questions, which are applicable in the case of describing the variables of a particular time period. Clifford Woody states, "research may be defined as the refinement and redefining of the problem, formulation of proposed solutions in the form of a hypothesis, gathering, organizing and evaluating of data, deduction and conclusion making, and lastly testing of the conclusion to determine whether it is consistent with the formulating hypothesis."

Population and Sample

The target group for this particular study would be the urban and semi-urban consumers of Salem District. The urban and semi-urban consumers of Salem District would be the consumers of pulse products and gram products of Jeyyam Global Foods. The total number of respondents for this particular study would be 94. In order to allow all the members of the population to have an equal chance of being selected as the sample of the population, the probability sampling technique that would be used for this particular study is simple random sampling.

Data Collection

Structured questionnaires, personal interviews, and purchasing behavior tools were used as tools for collecting primary data from consumers and buyers. Articles, websites, journals, books on consumer behavior, and annual reports of firms were used as tools for collecting secondary data.

STATISTICAL ANALYSIS

Independent Variables: Digital Pricing Strategy (Dynamic Pricing, Online Promotion, Transparency in Prices on E-commerce Websites) and Digital Product Strategy (Online Branding, Visibility of Products, Quality of Communication, Information on Products and Their Packaging).

Dependent Variable: Sustainable Consumer Purchase Behaviour (Brand Loyalty, Repetitive Purchase, Purchase Intention).

The software that is used for the purpose of encoding is the Statistical Package for Social Sciences, referred to as SPSS. The data that was collected has been analyzed with the help of the following statistical methods:

• Pearson Correlation: This method was used for the purpose of assessing the extent of relationship that existed between quality-price-driven repeat purchase behaviour and price sensitivity-driven switching behaviour.
• Two-Way ANOVA: This kind of analysis is used in studying the interaction of two factors in relation to consumer perception of product features and consumer loyalty in making purchases. The factors used in conducting the Two-Way ANOVA Analysis in the study include gender and branding.
• Multiple Linear Regression Analysis: This kind of analysis is used in studying the effects of pricing factors and digital product characteristics in relation to consumer behaviour in making purchases.
• Factor Analysis (Principal Component Analysis): Factor Analysis, also known as Principal Component Analysis, is used in studying the factor structure of consumer satisfaction/loyalty factors in digital product pricing.

RESULT

Pearson Correlation – Price Sensitivity and Repeat Purchase Behaviour

• H₀: There is no significant relationship between customers’ tendency to switch to cheaper alternatives due to frequent price hikes and their tendency to make repeat purchases because of good product quality and reasonable pricing.
• H₁: There is a significant positive relationship between customers’ tendency to switch to cheaper alternatives due to frequent price hikes and their tendency to make repeat purchases because of good product quality and reasonable pricing.

The significance value for the results is 0.000. The results are significant since the significance value for the results is less than 0.05. The value of the correlation coefficient for the results is 0.701. The results are significant since the significance value for the results is less than 0.05. The results show that the perceptions are highly correlated since the value of the correlation coefficient for the results is positive. The positive value of the correlation coefficient for the results shows that the perceptions are highly correlated. The value of the correlation coefficient for the results is 0.701. The results show that the perceptions are highly correlated since the value of the correlation coefficient for the results is positive. The positive value of the correlation coefficient for the results shows that the perceptions are highly correlated. The value of the correlation coefficient for the results is 0.701. The results show that the perceptions are highly correlated since the value of the correlation coefficient for the results

Table 1: Pearson Correlation – Frequent Price Hikes and Repeat Purchase Behaviour

Source: Primary data 

Two-Way ANOVA – Branding, Gender and Product Features

• H₀: There is no significant difference between branding and reputation of Jeyyam, gender, and product features like longer shelf life reducing the need to switch brands.
• H₁: There is a significant difference between branding and reputation of Jeyyam, gender, and product features like longer shelf life reducing the need to switch brands.

TABLE – 2

Source: Primary data  

The model is significant as indicated by the significance value, which is 0.000, meaning it is less than 0.05. This means that the null hypothesis is rejected. From the above data, it is very clear that gender is significant at 0.001, which means that male and female consumers have different perceptions towards product features. From the above data, it is also very clear that Jeyyam's reputation and branding are significant at 0.000, which means that there is a strong positive correlation between consumer perception and Jeyyam's product feature and branding. From the above data, it is also very clear that there is no significant difference in the interaction between gender and branding as indicated by the fact that the interaction effect of gender and branding is not significant at 0.056, which is greater than 0.05. From the above data, it is also very clear that the alternative hypothesis H₁ is accepted as indicated by the fact that R2 = 0.391 means that 39.1% variance is explained by the model.

MULTIPLE LINEAR REGRESSION

THE REGRESSION BETWEEN GENDER, AGE AND BRANDING AND REPUTATION OF JEYYAM MAKE ME PREFER THEIR PRODUCTS OVER LOCAL UNBRANDED PULSES

• H0: There is no significant relationship between gender, age and Branding and reputation of Jeyyam make me prefer their products over local unbranded pulses.
• H1: There is a significant relationship between gender, age and Branding and reputation of Jeyyam make me prefer their products over local unbranded pulses.

TABLE – 3

TABLE – 4

The R Square is 0.138. This means that the variation of the independent variables is responsible for 13.8% of the variation of the dependent variable, i.e., the choice of the consumer for Jeyyam in terms of branding and reputation. The ANOVA value is 0.035. Since the ANOVA value is less than 0.05, it is clear that the regression model is statistically significant. As the coefficient values show, the regression model of gender on consumer preference is statistically significant at 0.015. This means that the choice of the consumer is positively influenced by gender. As the coefficient values show, the regression model of age on consumer preference is not statistically significant at 0.446. This means that the perceptions of the consumer for branding and reputation are not influenced by age. This means that the alternative hypothesis is accepted, and the null hypothesis is rejected.

FACTOR ANALYSIS

The Factor Analysis Between Overall Satisfied With Jeyyam Global Foods Products, Would You Recommend Jeyyam Products To Your Family & Friends And High Satisfaction Levels Make Me Less Likely To Switch Brands Even For Lower Prices

TABLE – 5

TABLE – 6

TABLE – 7

TABLE – 8

A very high level of sufficiency for factor analysis is guaranteed by the high level of the KMO index. In this case, the KMO index is very high, i.e., KMO = 0.668. The variables used for the analysis are appropriate for factor analysis, as indicated by the fact that the level of significance for Bartlett’s Test of Sphericity is less than 0.05, i.e., 0.000. It is obvious that only one component is sufficient for explaining 63.026% of the total variables, as indicated by the total variance explained component. The high level of overall satisfaction, 0.824; recommendation intention, 0.789; and reduced switching behaviour, 0.768, is indicated by the component matrix, which implies that each variable is highly correlated with a certain component, which is related to consumer loyalty and satisfaction.

DISCUSSION

Also, the findings of the study proved that the implementation of digital transformation techniques in product and price strategies has a positive and significant influence on sustainable customer purchase behaviour in the FMCG industry. This is in line with the findings of the fundamental literature [6, 7].

The authors of the above-mentioned literature have proved that the happiness of customers, as well as sustainable consumer behaviour, can be achieved through the implementation of digital technologies in product quality and price. From the findings of the Pearson correlation test, it is evident that frequent price increases have a significant influence on brand-switching behaviour (r = 0.701, p = 0.000).

This means that customers in the FMCG industry are highly price-sensitive, and their decisions on repetitive purchases are influenced by price-quality factors. From the findings of the Two-Way ANOVA test, it is clear that gender and branding have a significant impact on the way people perceive product features, but the interaction effect is not significant. This means that though the overall levels of satisfaction differ for males and females, the impact of Jeyyam's branding on consumer perception of product features is the same for both males and females.

The regression study results indicate that the most important factor in predicting customer purchasing behaviour is providing special rates during festivals. This is under the threshold value p < 0.001 and the beta value of 0.475. The importance of digital promotion pricing at contextual moments in FMCG customer purchasing behaviour is confirmed in this study. The results indicate that the variance in consumer purchasing behaviour is explained by this model at 28.4%.

One common factor for the consumer happiness and loyalty variables was found, as the results of the factor analysis show. The factors of customer satisfaction and loyalty explained 63.026%. This confirms the importance of the strategic factors of price trust, brand happiness, and digital product quality in generating customer loyalty for the FMCG industry.

CONCLUSION

The study also reveals that sustainable consumer purchasing behaviour in the FMCG industry is highly influenced by the positive impact of digital transformation techniques used in pricing and product strategies in the industry. The study also reveals that sustainable consumer purchasing behaviour, as in the case of Jeyyam Global Foods, Salem, is highly influenced by maintaining the quality of the product, such as packaging and nutritional value, along with pricing in the digital world, as customers are price-sensitive. Hence, it can be understood that there is a positive effect in client loyalty due to the formation of trust and differentiation of Jeyyam products from other commodities which do not possess any brand name. Purchases done by clients and satisfaction levels have also been positively impacted due to digital promotional strategies, especially festival-based schemes. It has also been understood that customer satisfaction is considered to be the key factor for brand advocacy, which is measured by the primary result variable. The study also proved that customer loyalty, pricing trust, perception of digital products are considered to be of higher predictive potential compared to demographic variables. Digital transformation in quality assurance, pricing intelligence, brand communication, and digital marketing strategies can be proposed as an answer to attain sustainable competitive advantage for overall organizational effectiveness in the FMCG industry.

REFERENCES

1. Rouf, A., Babu, A., & Uddin, J. (2026). Influence leads intention: How caring incentives and micro-celebrity endorsements promote sustainable consumption. Journal of Sustainable Consumption. https://doi.org/10.1016/j.clrc.2026.100394
2. Gou, J., Li, Y., & Goli, A. (2026). An IoT and blockchain-based multi-objective optimization and machine learning approach to intelligent supply chain design. International Journal of Production Economics. https://doi.org/10.1016/j.jer.2025.10.017
3. Ayaz, O., Tabaghdehi, S. A. H., & Tambay, P. (2025). Ethical implications of employee and customer digital footprints: SMEs perspective. Journal of Business Ethics.
4. Ahmadi, S., Barkhi, F., & Nikhashemi, S. R. (2026). Uncovering consumer loyalty behaviour: A data mining approach in fast moving consumer goods sector. Journal of Retailing and Consumer Services.
5. Yang, Y., Chung, H. F. L., & Elms, J. (2025). Relational bonds strategy, organizational learning, and B2B performance: The case of multi-channel network. Industrial Marketing Management.
6. Murugan, M. (2023). Digital Marketing (Kindle ed.).
7. Bhatia, P. S. (2023). Fundamentals of Digital Marketing. Pearson Education.