A Study on the Shifting Consumer Buying Habits in Hyderabad: E-Commerce and Traditional Retail Perspectives
Dr. Nagunuri Srinivas*
St. Joseph’s Degree & PG College, Hyderabad
*Corresponding author
DOI: https://doi.org/10.51244/IJRSI.2025.120700048
Received: 08 July 2025; Accepted: 10 July 2025; Published: 31 July 2025
The study analyses consumer shopping behaviour in the city of Hyderabad with respect to modern and traditional retail formats. The online shopping is still growing well in Indian cities, where people have access to the internet and smart devices making them shop from anywhere, anytime. “People still want to buy from physical stores as they need to touch and feel goods whilst having immediate possession along with the personal touch,” adds Anu. Our paper investigates the motive behind consumers’ decision of whether to buy online or offline as well as identifying the advantages and disadvantages of both ways of buying. Our study uses both our survey results and interviews with 400 participants that form a broad-spectrum group of varying ages, financial statuses, and careers.
Studies say e-commerce is great for snap purchases of cheap stuff across a spectrum but people prefer to touch and buy stuff right now. Shoppers age 18-34 are quicker to turn to online shopping and are increasingly turning away from physical stores, including those who buy clothes and electronic goods. Increased price sensitivity largely determined how customers behaved, and this ties back to the fact that many people choose online shopping because they can get a better deal. The research found that personalised treatment, and meeting sales experts while shopping in-store are factors that people like.
The study demonstrates that the complement of online and offline store operations can fulfil the demands of today’s customers more effectively. Retailers will have to provide seamless multichannel buying experiences and to enhance the quality of price and service across all shopping alternatives. Ramping up the availability of eco-friendly products as well as discounts and offers also benefits retailers to get more customers and augment business for both models, the study found.
This study provides important purchase behaviour insight by which the retailers and policy-makers can strive for better serving the booming urban population in Hyderabad. This study illustrates how, through the conjuncture of service traditions and technological systems, the retailer can combine them effectively for sustained success and to win the retail race.
Keywords: Consumer behaviour, e-commerce, traditional retail, shopping habits, urban consumers, omnichannel strategy, price sensitivity, Hyderabad, retail trends, personalized service.
The recent decades have seen drastic changes in consumer purchasing decision-making patterns as a result of technology advancements social changes and new ways of shopping. The e-commerce movement has been felt globally and it has revolutionized retail practices. Urban India has brought online shopping to the masses, through smartphones and internet access. Given that Hyderabad is among the fastest growing cities in India, it has ideal conditions to look at purchase habits and have an eye on transformation in modern retail. The rising middle class in Hyderabad, combined with a digitally enabled consumer base or every big retailer in the market, has encouraged an upsurge in online shopping for electronics appliances food fashion and more. Physical stores are doing fine as people still like to see and try on products and receive rapid service and personal attention even as online shopping continues to surge.
The research examines shopping habits of cit of yer Hyderabad from traditional retail and e-commerce. This research looks at shopping habits because people are now shopping widely online even as they continue to rely heavily on traditional stores. That they can purchase in both streams at the same time raises the question of what may push one to one option over the other. Customers rely on convenience features, returns policy, multi product choices and purchase experience to decide this. Knowing which store methods can best help perform on such disparate types of shopping are great value to businesses looking for more productive store operations and happier customers.
The sprouting online shopping sites in Hyderabad can be attributed to competitive pricing, Product variety and range with the added comfortable benefits of home shopping. Bricks-and-mortar retail still caters to the shopper who wants to walk away with products on the spot and have touch-and-feel experiences with knowledgeable store workers. The research presents how Hyderabad consumers evaluate each retail concept through their purchase patterns while investigating how price sensitivity, convenience, product quality and shopping experience influence their decisions.
This research will help in understanding the growth of e-commerce and its traditional counterpart in this region of India and enable new shopping literacies to develop among Hyderabad consumers. Our study offers businesses and retail stores guidance on how to tailor their business models to the ways in which customers are changing the way they shop.
Importance Of the Study
Such research can round out the picture of how Hyderabad consumers shift shopping patterns in the face of intensifying online vs. Place competition. Both marketers and retailers had better learn how the patterns of consumer shift from shopping online to offline and vice versa last, as e-commerce companies rapidly expand through India. Studies confirmed that the behaviour of consumers is influenced by a number factors which include Shopping convenience, Prices, Product preference and the general environment of purchase (Laudon & Traver, 2020). The research offers indispensable insight into what the adoption of digital retail is doing to consumers in India’s ascending marketplaces as they continue to cherish physical shopping.
Findings of the research are directly applicable to firms that operate in Hyderabad where digital adoption and fast pace of urban development necessitates for domain knowledge. “Hyderabadites are telling businesses what they value most is ease instead of price, so businesses in India need to keep in mind that a physical store will automatically allow you to cater to all types of consumers by tweaking design, feel and services, so why not do it!” While, traditional retail stores are currently still dominated, by the report from Kumar and Sharma (2020) that majority customers are preferred to buy E-commerce is still gaining people’s hearts due to its convenient access and lower price. This study investigates the consumers’ motivation between online and in-store shopping as well as its influencing condition.
The research is important as it examines the impact of technology on shopping behaviour with rising digitalisation. Comprehending how consumers integrate physical and digital purchasing approaches is crucial for the evolution of online shopping platforms and enables firms to develop connected shopping experiences. Research by Venkatesh and Mehta (2019) suggests that the omnichannel approach is among the best ways to improve customer loyalty and engagement for businesses. Our study offers fresh perspectives on Hyderabad’s urban consumers selection of shopping venues for digital and traditional shopping centres.
The findings of the study would provide direction for the area policy makers who would like to see these two store formats to be successful in Hyderabad. Policy leaders use the research to inform better programs to assist retailers in creating systems that are friendly to various types of customers. Knowledge of consumer shopping trends would enable the prediction of India’s retail future as both brick-and-mortar (traditional) and online shopping develops proportionally in the growing Indian market (Patel 2021). ′[This research] expands the available knowledge for practitioners in the retailing sector and provides a learning tool for students of consumer behaviour.
Raji et al. (2024) examined the increasing use of instruments of artificial intelligence in e-commerce and its effects on buyer behaviour. Researchers detail how AI tools such as product recommendation engines and targeted marketing sell products to shoppers in other ways. Our study considers various AI applications over e-commerce websites which recommend products depending on user actions and preferences to develop personalized shopping experiences. Our method is all the better for shopping for both sides because it enables us to make more sales by showing customers products that match their wants at exactly the right times.
New study finds that AI explanations of e-commerce markets allow businesses to understand shopping behaviour and anticipate changes for increased impactful product promotion. These days e-commerce companies rely on powerful machine learning algorithms to build increasingly accurate profiles of their customers as AI technology matures. The report predicts that next-generation online stores will read consumers’ desires without waiting for them to say what they want. Using AI, platforms can better retain their customers by providing unique customer experiences that align with what an audience wants.
Rita and Ramos (2022): In 2022, Rita and Ramos performed a bibliometric analysis for monitoring the trends in the global research on consumer perceptions of sustainability of e-commerce. They found that consumers still care about sustainability when shopping online, as e-commerce has increasingly led to retail sales. They referred to published work to show that relatively more research on the impact of e-commerce sustainability measures on consumer responses. Their study suggests that sustainable practices impact consumer trust, build brand loyalty and affect purchases. Our research shows that sustainability is now a key component of successful online shopping because there is a greater consumer concern for the environment.
The study specifies content contexts through which consumer buying practices relate to sustainability practices by focusing on sustainable technology use and sustainable purchase decision-making during online transactions. Investigators analyse how e-commerce firms can address consumers’ sustainability demands and still remain profitable. Our research demonstrates how consumer behaviour meshes with current environmental practices, so e-commerce companies can discover how to best serve their market and run a sustainable business. The researchers indicate that future research should examine how sustainable e-commerce development affects consumer behaviour and industry transactions in the long-term.
Wagner et al. (2020) review the interaction of consumers in different online channels through their multichannel buying process. Their studies try to understand how customers move among platforms like websites, apps and social media before they buy something. The study suggests retailers have to provide seamless shopping experiences on every touch point to satisfy consumers who shop both online and offline. Customers hop between digital and physical touch points as they browse products across multiple devices, which connect numerous online platforms.
The research findings demonstrate the ways in which customers take buying decisions when they can use different digital channels simultaneously. How easy and fast it is to process platform information across various interactions is what customers see, and they are making their decisions based on that. The study shows that those firms that blend their digital sales approaches create happy sales customers and recoup their customers and increase sales effectiveness. The researchers recommend e-commerce companies developing an enhanced strategy of multichannel sales where every contact point is beneficial and useful for consumer decision-making process of shopping.
Urne and Agrawal assessed the total body of work to demonstrate the impact of e-commerce on the buyer decision. Exposing that in their research, the authors demonstrate that e-commerce has never owned consumer decision making, not in the way it does today, where quickness and range merge seamlessly with instant availability of products. Their research explores the way digital influences consumer shopping behaviour with the ease of online comparison and detailed product descriptions in addition to user-based feedback platforms. As the study said, consumers have more power than ever, thanks to e-commerce that allows them access to tons of information to make better product decisions.
The research paper sheds light on how trust works – in forms of secure transactions and responsive customer service – reduces the perceived risks that consumers experience about electronic commerce. The author discussed that though it gets advantages, however still online shopping has disadvantages such as product returns and the feeling of being alone while browsing shopping sites. Their findings prompt them to recommend that future research should examine how Internet businesses can better meet the needs of their customers, with a greater degree of personalisation of both services and products.
Wang and Ng examined competing pricing strategies used by digital and brick-and-mortar commerce over consumer preference patterns and distribution mechanisms. Studies have shown alternative shopping methods to give customers new options to purchase goods through Internet-based platforms. E-commerce lets customers find better deals because businesses can cut down on operating costs and display more product options. Today’s consumers pay more attention to cost and become better informed more quickly these days, as they comparison shop between various online stores. Studies show that it’s more challenging than ever for brick-and-mortar stores to retain their clientele in the age of digital shopping.
Research takes a look at how physical stores are adapting to today’s digital marketplaces. Their websites and technology are becoming increasingly important to traditional retailers, as well, so that they can simply provide better and more valuable services to their customers. Traditional retailers, despite all they have done to change with the times, still cannot offer the personally curated and easy shopping experience offered by their Web and mobile counterparts. Companies also need more online and offline options to offer better service to today’s consumers, Wang and Ng said. Our perspective teaches enterprises to integrate aspects of physical and digital commerce to boost brand loyalty and drive increased foot traffic.
In the recent work of Amin and Mahasan (2019) investigates how consumers decide which type of store to shop; a traditional or modern store. This study indicates that shoppers decide with multi-criteria such as products wah offer, store location attractiveness, price opportunites and buying support. E-commerce is convenient, cheaper — and not even close to being as popular among consumers; who prefer an old-fashion retail store because it allows to feel and inspect a product, the authors added. People Prefer doing clothes and electronics shopping at physical stores because they want to see and try out things before they purchase it.
Trust of the consumers also impacts their method of shopping in all markets as revealed by result. Emerging market customers who shop online don’t trust ecommerce, like to try products before purchasing them. When customer service levels and attention to protecting customer identity increase by online retailers there is an impact on customer purchase behavior, such as the amount of purchases made. The authors demonstrate that consumers use traditional and modern ways of shopping that correspond to their desired lifestyle and shopping applications.
Objectives Of the Study
Scope Of the Study
This study examines how consumers shop in Hyderabad encountering both web and brick-and-mortar stores. This study primarily examine what features such as convenience of shopping price options selection of products retail environment play a role in the shift from stores to online store for purchase preference. Using a heterogeneous sample of consumers of all ages income classes and educational levels, this study examines buying behavior to clarify the factors affecting the way different consumers make their purchasing decisions.
This study invests- gates the impact of the digital commerce on retail store nowadays and the strategies of physical retail stores to compete with web-based stores. The study looks at how these omnichannel strategies are being used by retailers to bridge the gap between physical stores and online shopping as well as to strengthen customer relationships. Our analysis considers the fast growing retail district in Hyderabad, as it reflects actual customer behaviours under a dynamic market situation. The research will look at what customers think of online versus physical stores today and examine the way shopping patterns have shifted as a result of COVID-19.
This study provides insights on the implications for marketers, policymakers, and researchers of shifts in consumers behaviour and considerations of effective retail strategies for today’s changing environment.
Both the techniques of research are employed by the researcher in analysing the E-commerce shopping behaviour of the Hyderabadi consumers for traditional shopping as well. To have a spread representation from different age levels income strips, and education background we selected 400 respondents through stratified random sampling. Our study plan involves templates of structured questionnaires with Likert and multiple-choice questions, as well as 20 qualitative interview responses. These are the tools that we can use to understand the consumer trend between these two models.
Our team will do the statistical patters and tests on what drives purchase decision and do thematic studies on what are the trends in business based on the interview. Our study is ethically sound linking continuous dementia data collection, ensuring participants receive a full briefing of the study and that their data remain confidential. Our study is restricted to urban customers of Hyderabad and not taking the rural customers from all over India.
Analysis And Interpretation
Table No: 1- Descriptive Statistics
55 and above | Prefer not to say | Single | 18-24 | Male | Widowed | 25-34 | Female | Divorced | Under 18 | Other | Married | 45-54 | 35-44 | |
Age Group | 63 | 0 | 0 | 62 | 0 | 0 | 58 | 0 | 0 | 78 | 0 | 0 | 63 | 76 |
Gender | 0 | 88 | 0 | 0 | 82 | 0 | 0 | 102 | 0 | 0 | 128 | 0 | 0 | 0 |
Marital Status | 0 | 0 | 99 | 0 | 0 | 87 | 0 | 0 | 105 | 0 | 0 | 109 | 0 | 0 |
From the table it is observed that 74% of participants are between 25 and 34 years old with smaller groups in both the 45-54 and under 18 age ranges. Our results show that female participants account for 128 responses while only 82 come from male participants. The survey shows that out of all responses married people represent the highest group at 109 followed by the single at 99 participants. Data shows younger adults and married individuals form the largest parts of the study population.
Table No: 2- Descriptive Statistics
Highest Level of Education | |||||||
Doctorate or higher | Master’s degree | Some college or technical education | Bachelor’s degree | High school or lower | Total | ||
Monthly Household Income | ₹40,001 – ₹60,000 | 9 | 11 | 19 | 16 | 11 | 66 |
More than ₹80,000 | 14 | 21 | 19 | 17 | 18 | 89 | |
₹60,001 – ₹80,000 | 18 | 17 | 11 | 12 | 8 | 66 | |
₹20,000 – ₹40,000 | 17 | 16 | 17 | 17 | 22 | 89 | |
Less than ₹20,000 | 17 | 25 | 24 | 11 | 13 | 90 | |
Total | 75 | 90 | 90 | 73 | 72 | 400 |
The study displays how people at different income levels achieved their highest education degree. Most respondents with a bachelor’s or master’s degree live in the ₹20,000 – ₹40,000 and ₹40,001 – ₹60,000 income bands. People with high school or below education appear across all income groups but number 22 in the ₹20,000 – ₹40,000 group and 13 in the under ₹20,000 group among respondents.
A total of 90 people belong to the household income group below ₹20,000 and 89 each fall into the income bands of ₹20,000 – ₹40,000 and more than ₹80,000. Our results show that many survey takers had modest incomes with little representation in the top level of earners. The results show that our participants include people from various educational and income backgrounds.
Table No: 3- Descriptive Statistics
Occupation | |||||||||
Administrative/Clerical | Sales/Marketing | Other | Manager | Professional (e.g., engineer, doctor, lawyer) | Student | Business Owner/Entrepreneur | Total | ||
Current Employment Status | Student | 15 | 14 | 6 | 8 | 10 | 12 | 9 | 74 |
Self-employed | 9 | 6 | 16 | 14 | 10 | 6 | 6 | 67 | |
Employed full-time | 12 | 13 | 13 | 7 | 7 | 12 | 5 | 69 | |
Employed part-time | 8 | 12 | 14 | 11 | 9 | 9 | 3 | 66 | |
Unemployed | 3 | 12 | 13 | 7 | 18 | 9 | 7 | 69 | |
Retired | 10 | 11 | 6 | 7 | 7 | 9 | 5 | 55 | |
Total | 57 | 68 | 68 | 54 | 61 | 57 | 35 | 400 |
The data shows what types of jobs and employment situations people currently have. Students take on the most jobs in Administrative/Clerical positions with 15 people followed by 14 students in Sales/Marketing for a total of 74 students. A majority of self-employed people belong to Different fields with 67 people working in these occupations. Both Administrative/Clerical and Sales/Marketing roles have 12 workers in their respective full-time employment category.
A sizeable majority of unemployed participants are Professional (18) and Sales/Marketing (12) workers alongside 10 Administrative/Clerical and 11 Sales/Marketing retirees. The information presents many different job types that work with various employment patterns to show our diverse sampling group features both working and jobless people. The sample includes more students and workers than professionals who hold full-time jobs and anyone who is unemployed. Forty percent of the respondents started their own businesses.
Table No: 4- Descriptive Statistics
Urban | Yes | No | Rural | Suburban | |
Place of Residence | 133 | 0 | 0 | 140 | 127 |
Owns Smartphone | 0 | 218 | 182 | 0 | 0 |
Has Access to Internet | 0 | 194 | 206 | 0 | 0 |
The data indicates how many respondents live in different areas and possess smartphones plus internet access. The data shows urban residents have the most numbers at 133 followed by suburban residents at 140 and rural residents at 127. Most participants use smartphones since 218 confirmed ownerships while 182 reported no access. The results show that most participants own and use smartphones.
The sample includes 194 respondents who have internet access and 206 people who do not. This distribution shows access to the internet is relatively normal but few still have no internet connexion. Analytics show people with smartphones mostly connect to the internet in urban and suburban locations. Rural areas face limits in smartphone and internet access because this phenomenon separates digital access from certain parts of the population.
Table No: 5 – Descriptive Statistics On Shopping Frequency And Influencing Factors For Online And Traditional Retail
How often do you shop online (e-commerce)? | How often do you shop at physical retail stores (traditional retail)? | What factors influence your decision to shop online? (Select all that apply) | What factors influence your decision to shop at physical retail stores? (Select all that apply) | |
Mean | 2.99 | 3.01 | 3.58 | 3.53 |
Std. Deviation | 1.41 | 1.35 | 1.69 | 1.73 |
Minimum | 1 | 1 | 1 | 1 |
Maximum | 5 | 5 | 6 | 6 |
The results indicate that customers use online shopping apps and brick-and-mortar stores the same number of times in a typical week. Scatter exists in how often survey takers shop according to standard deviation measurements.
Product variety gives online shopping a strong pull (mean 3.58 | SD 1.69) yet in-store shopping depends mainly on product inspection and instant buying (mean 3.53 | SD 1.73). Responses about shopping methods demonstrate wide adaptability since customers show many different choices.
Table No: 6 – Consumer Preferences For Online Shopping Versus Traditional Retail For Product Categories
n | Mean | Median | Standard deviation | |||
Do you prefer online shopping or traditional retail for buying the following types of products? (Electronics) | 400 | 1.94 | 2 | 0.8 | ||
Do you prefer online shopping or traditional retail for buying the following types of products? (Clothing) | 400 | 1.94 | 2 | 0.81 | ||
Do you prefer online shopping or traditional retail for buying the following types of products? (Groceries) | 400 | 1.98 | 2 | 0.84 | ||
Chi 2 | df | p | ||||
0.32 | 2 | .852 |
People display a small preference for traditional retail while shopping for all three product categories including electronics (mean 1.94), clothing (mean 1.94), and groceries (mean 1.98). Our results show that clients support online or physical shopping equally across each product group. Their choices vary only slightly between these groups.
The Chi-Square analysis produced a test value of 0.32 with two degrees of freedom and a p-value above the standard level of 0.05. Research data shows consumers have no clear preference between shopping online or in brick-and-mortar stores for electronics and clothing as well as food purchases. Thus, we fail to reject the null hypothesis.
Table No: 7 – Impact of E-Commerce on Traditional Retail Shopping Habits and Challenges
n | Mean | Std. Deviation | Std. Error Mean | |
How has the rise of e-commerce affected your shopping habits in traditional retail stores? | 400 | 2.51 | 1.11 | 0.06 |
What challenges do traditional retail stores face due to the rise of e-commerce? | 400 | 3.01 | 1.4 | 0.07 |
Test | F | df1 | df2 | p |
Levene’s Test (Mean) | 16.21 | 1 | 798 | <.001 |
Brown-Forsythe-Test (Median) | 13.16 | 1 | 798 | <.001 |
The findings show that customers view shopping habit transformation due to e-commerce’s growth at a mild level (Mean = 2.51, Standard Deviation = 1.11). Consumers see major difficulties for offline stores that encounter e-commerce growth according to a 3.01 rating scale (Standard Deviation 1.4).
The differences between group variances are highly distinct due to an F-value of 16.21 and a strict p-value below 0.001. The Brown-Forsythe Test of variance centred on median data demonstrates a strong difference between groups at F=13.16 with p<0.001. Our results show that participants view e-commerce differently from how they shop now and see distinct difficulties hitting traditional stores from online shopping.
Table No: 8 – Regression Analysis on Consumer Opinions Regarding Traditional Retail Strategies to Compete
With E-Commerce
Unstandardized Coefficients |
Standardized Coefficients |
95% confidence interval for B | |||||||
Model | B | Beta | Standard error | t | p | lower bound | upper bound | ||
Constant | 2.67 | 0.13 | 20.07 | <.001 | 2.41 | 2.94 | |||
What do you think traditional retail stores can do to compete with e-commerce? | -0.05 | -0.06 | 0.04 | -1.27 | .204 | -0.13 | 0.03 | ||
Model | df | F | p | ||||||
Regression | 1 | 1.62 | .204 |
The regression analysis shows that the baseline estimate of 2.67 is significant due to a p-value below 0.001. The coefficient for the factor “What do you think traditional retail stores can do to compete with e-commerce?” This factor shows no connection to the outcome because its test score (0.204) exceeds our 0.05 significance threshold.
The regression analysis shows that the independent variable cannot predict dependent variable changes because the F-statistic stands at 1.62 with a p-value of 0.204. The 95% confidence interval shows between -0.13 and 0.03 which crosses zero demonstrating statistically insignificant results for this factor. According to the model, consumer feedback does not show a strong link to what happens between physical stores and digital shopping in this situation.
Table No: 9 – Descriptive Statistics and Anova Results for Consumer Demographics and Shopping Preferences
n | Mean | Std. Deviation | |
What is your age group? | 400 | 3.56 | 1.74 |
What is your monthly household income? | 400 | 2.84 | 1.4 |
How do you feel about shopping online for high-ticket items? | 400 | 2.53 | 1.1 |
Type III Sum of Squares | df | Mean Square | F | p | η2 | |
Treatment | 224.28 | 2 | 112.14 | 54.66 | <.001 | 0.12 |
Error | 1637.05 | 798 | 2.05 |
The study shows the participants mainly fall between 3.56 years old and 5.30 years old (SD = 1.74) with a median age of around 15. The data shows most respondents earn between ₹20,000 – ₹40,000 each month. On a scale from 1 to 5, participants report neither favoring nor rejecting the idea of purchasing expensive items online (mean=2.53, standard deviation=1.1).
The treatment impact on shopping preferences and demographics produces a strong result with both a 54.66 F-value and <0.001 p-values. The treatment produced ansible 12% effect on consumer behaviour patterns between different age groups and buying habits online. The leftover variation amounts to 1637.05 distributed across 789 observations with an average of 2.05.
Table No: 10 – Correlation Matrix for Consumer Shopping Preferences and Education Level
Does your education level affect the way you shop online versus traditional retail? | How satisfied are you with the online shopping experience? | How satisfied are you with the in-store shopping experience? | |
Does your education level affect the way you shop online versus traditional retail? | 1 | -0.08 | 0.01 |
How satisfied are you with the online shopping experience? | -0.08 | 1 | -0.08 |
How satisfied are you with the in-store shopping experience? | 0.01 | -0.08 | 1 |
The matrix shows how education affects consumer shopping experiences. The study shows education level bears no meaningful connection to online shopping satisfaction. How content customers feel about shopping online has no major impact on their satisfaction with shopping in stores.
Research shows that education level barely affects customer shopping habits between physical stores and online. Consumer satisfaction levels in one store type do not clearly predict satisfaction in the other.
The study indicates that the modern shopper is buying on online more and more, with the key drivers being the ease of purchasing, discounts, and variety. Brick-and-mortar stores remain despite the proliferation of online shopping because customers like to touch products and shop on the spot and receive personal support. The findings reveal how online retailers are capturing ever more market share but that retailers must integrate digital innovation with their in-store operations to stay viable in the new world of retail. The decisions shoppers make while shopping depend on how much hassle the store or site is to navigate and also on the cost, the product range and the quality, and companies need to balance both styles of stores to be successful.
In other to note the actual habits of today’s shoppers, the combination of online and bricks and mortar considerations are necessary to build into their strategy. Companies that combine these shopping channels deliver superior service and outperform rivals in terms of revenue. Our research demonstrates that companies need to pair technology tools with better customer service and product representation to provide an excellent buying experience. Once both traditional shops and online stores know their customer’s desires and needs, both can co-exist offering customers shopping options that are just what they want.