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Flash sales report

  1. 1. Page | 1 Chapter I Introduction
  2. 2. Page | 2 1. INTRODUCTION Modern day marketers have a tremendous opportunity to connect to women in a better way with the products they buy and the media technologies they use to make a positive impact in their lives. After a strong and immense growth in 2010, internet retailing just came shining ahead of all other retailing channels and emerged as a strong winner even after recession, driven by shifting consumer attitudes and mindsets. Remarkable transformation in economic independence, better access to education, better and improved career opportunities and higher pay scales in both developed and emerging economies have been some of the major factors responsible for the transformation of women into smart and intelligent consumers. Online flash sales sites are the latest buzz in India that have come up in response to rising investor interest in private sale portals across the globe such as the Gilt Group and Rue LaLa in USA and Ventee-Privee.Com in Europe. Today, the flash-sale shopping sites have their own loyal following, and the range of products offered varies from fashion to electronic gadgets to apparels to loads of other categories. The fact that shopping behavior varies not only between men and women, but is quite different between the women of different countries, religions and even age groups intrigued the researchers to get a deeper insight about the young female consumers' psyche and attitude regarding the online flash sales hype in India. Consumers are sophisticated - more so than retailers, it turns out. Consultants at PricewaterhouseCoopers (PwC) interviewed 1,000 shoppers in seven major countries and the results were mostly consistent. As retailers embrace both new approaches (flash sales, online outlets, daily deals and more) and new channels (mobile, social and multichannel), customers are quick to take advantage. Online retail has long been driven by product availability, shopping convenience, price and selection. Now multi-channel is also part of the equation. The rise of multi-channel PwC identifies three main types of multichannel retail. • Making a purchase from a choice of up to five different available channels. Channels are chosen depending on the type of item or circumstances. Eighty-six percent of those surveyed by PwC are already using at least two channels. A quarter said they use four or five. • Using a mix of channels for a single purchase. This means using different platforms but with the same retailer. Three quarters of online customers have already done this. • Using a mix of channels across retailers to make a single purchase. This can mean doing research online before buying in-store. More than 80 percent of those PwC surveyed said they
  3. 3. Page | 3 have researched online before buying in-store for items such as electronics, books, music and films. It can also mean the reverse – for example, seeing a TV in-store and then buying the TV online from an online retailer. Multi-channel approach there is increasing pressure to get the multichannel approach right. The experience should be seamless for the consumer even if it requires some complex backend systems integration. Consumer decision journey Consumers have also fundamentally changed the way they buy. While marketers used to think in terms of a buying funnel, a linear and relatively simple concept still relevant across much of B2B, a few years ago experts at McKinsey identified the Consumer Decision Journey.7 Most notable of the four phases of the Consumer Decision Journey is the ‘Loyalty Loop’ because of factors such as e-loyalty programs and social media. Buying decisions are now circular rather than linear for many products, especially for apparel. With the backdrop of higher levels of e- commerce and consumer shopping sophistication, retailers must broaden their offerings rapidly and securely at scale. THE RISE OF THE FLASH SALE Flash sales are very much associated with apparel, fashion and luxury goods. Online businesses such as MyHabit and BuyVIP have made names for themselves in the flash sales space in the past few years. The flash sales category is expected to continue to grow globally.8 The Business Insider analyst explains: “It’s easy to see why this is a win-win for all involved. The limited supply of high-end apparel at deep price markdowns creates the illusion of scarcity that protects a designer’s brand image, despite the fact that they’ve just thrown their doors open to the plebeian masses. Consumers get huge discounts on desirable brands while being made to feel Figure 1: Consumer Decision Journey
  4. 4. Page | 4 like they were just hushed into a back room for an exclusive deal. The flash sale operators meanwhile — and this bears repeating — have created a billion dollar industry in a few short years on the ashes of a record supply overhang.” Flash sales aren’t limited to online startups. Established names in retail such as Amazon have been very active in the flash sales space. Consumers have become accustomed to flash sales across apparel, jewelry, and luxury categories and flash sales are more popular than ever. Mobile commerce and social media also impact flash sales. Mobile commerce allows consumers to make purchases quickly and in many cases right when a flash sale goes live. Social media – in line with the McKinsey model – provides a virtuous circle of consumers talking about upcoming sales or providing feedback on goods they bought or missed out on. Most retailers in this space are enthusiastic about the opportunities and challenges both mobile and social present. ONLINE OUTLETS Just as consumers have become accustomed to flash sales, they have also come to expect online outlet sites similar to out-of-town brick and mortar outlet malls from major retailers. They accept that outlets – offline and online – provide a fundamentally different shopping experience. While they expect big reductions, they are also aware that aspects such as shipping options, returns policies and the general shopping experience might be different. For retailers, outlets are a way to tap into the consumer appetite for a different shopping experience while protecting non-sale margins on their main sites. Running frequent sales on a core website just isn’t the same. It is also something that consumers are increasingly comfortable with. Just as outlet shopping centers provide out-of-town experiences, outlet sites provide online shoppers with different destinations for their favorite brands. Flash sales are a relatively new concept in India, with Flipkart being the beginner in this regard, with sales of Xaomi Mi3 phones. Other e commerce majors such as amazon and snap deal were quick to catch on, with their own versions of the concept to entice the tech savvy youth to their respective portals. Deal-of-the-day (also called flash sales or one deal a day) is an ecommerce business model in which a website offers a single product for sale for a period of 24 to 36 hours. Potential customers register as members of the deal-a-day websites and receive online offers and invitations by email or social networks.
  5. 5. Page | 5 Flash sales develop a large targeted potential buyer’s database, test these potential buyers to see which the right product mix is and then buy unsold inventory and resell it at a large discount. Sometimes – they don’t even do that. They just attract potential customers to several discount offers which become active when a certain number of buyers is reached. They ensure this way that they are able to purchase the merchandise without reporting losses. The logistics in this business is a little tricky if you are dealing with “volatile” STOCKS and can sometimes turn to frustration from customers as orders sometime take weeks to arrive. However, when purchases are made, flash sales sites customers are more likely to buy again, according to this study. Customer lifetime value increases 385% for flash sales sites, whereas traditional online retail shows an increase of “only” 94%. So – business is a-booming. Buyers flock around flash sales sites, they buy more than on traditional online stores and the business model seems to be more stable. Overall, the introduction of flash sales in India has made online shopping a more attractive entity for the consumers.
  6. 6. Page | 6 Chapter II Design of Study
  7. 7. Page | 7 2.1 STATEMENT OF PROBLEM: Flash sales in India is a new broader and consumer oriented concept of sales especially online. It is not yet a very common practice and it is important to analyze the pros and cons of such an approach and use it most optimally for benefit of the e commerce industry as well as consumers. This study aims to study the process of flash sales, its practice strategies and its impact on the industry and is consumers. 2.2 REVIEW OF LITERATURE: History of the Flash Sale The flash sale was pioneered by online retailer in July 2004 in a deal of a day format. In addition to browsing the company’s online store, you had a 24 hour window each day to take a special deal or ignore it. The following day, a new item appeared with the same 24 hour sale deadline. The types of items that appeared in the daily special could hail from anywhere in the Woot inventory—from everyday, mundane computer supplies to quality consumer goods. Since then, flash sale-centric websites exploded across the Internet, seemingly multiple ones for every type of consumer industry. Perhaps the biggest flash sale success story is that of Groupon. Right up around Q4 2010, the company turned down a $6 billion buyout from Google, inspired over 500 types of copycat services, and garnered over $850 million in sales in the United States. Six months later, Groupon launched its IPO with an organizational value priced around $13 billion. Around this time period, franchise tech companies such as Google, Facebook, and Amazon began to flirt with the daily deal phenomenon. Why Flash Sales Worked One of the major reasons why flash sales were so effective was that during their heyday, the American economy was still feeling the effects of the market crash. People needed to save up on money as they lost their jobs and struggled to make ends meet. With the flash sale, you have something extremely cheap for a limited time that could provide you with quality entertainment. Instead of splurging money on high tech gadgets and various beauty parlor visits, you instead could treat yourself to a cheap salon day pass or highly discounted consumer
  8. 8. Page | 8 goodies. In response to a depleted economy, flash sales made everything fun and interesting again and disrupted the typical brick and mortar or online retailer business plan. Additionally, because of the sometimes-needed participant quotient for a deal to activate, deals became popular shares across social media. Users would encourage their friends to join in on something for a chance to bond. Factor in a time requirement element for deals, and all of a sudden you have large social media presence. How Flash Sales Faltered After a year in the public market arena, Groupon lost about 80% of its stock value. Sales were falling alongside the number of local establishment partnerships that the company had carved out. For the rest of the flash sale market, a large number of the small copycat ones got swept away, though the more established ones continued to carry on, albeit at a more downscaled level. Several different factors can be pinned to the fall of flash sale sites. Perhaps the biggest one is the shift in consumer behavior. One term that came from this entire craze is flash sale fatigue. As people used flash sale services, they were signed up to the ecommerce site’s email listserv. If you participate in a flash sale on a dozen of different sites, you would receive daily/weekly emails from each of them. Things got pretty crazy for the average email box. Marketing messages started to blend in with each other. Consumers began to tune out when viewing subject headers. Opt-out rates began to climb. People got burnt out from feeling the need to purchase at a discount price all the time. As a result, the number one direct advertisement channel lost its edge. You can look at the economy’s recovery as another reason for the fall. As people began to go back to work, expendable income once again was on the rise, and along it was retail shopping. The tried-and-true business model received a second breath of fresh air. As a result, there was less fire sale surplus to go around for flash sales. People also began to be more patient with their money and used technology to research products thoroughly before purchasing them. This allowed them to find pricing for items that was on par with flash sales’, without feeling rushed by the daily deal window. Additionally, a number of flash sale ecommerce stores offered less
  9. 9. Page | 9 than favorable shipping rates and return policies. These two elements are key in building a loyal customer base and generating favorable word of mouth. Lastly, the flash sale business model proved unsustainable for those who offered goods services at a highly discounted rate. The reason why many local establishments partnered up with Groupon was that they saw Groupon as a chance to build their customer base. Theoretically, a Groupon customer would be exposed to your services because of the discounted rate, be pleased, and become a regular returning customer, resulting in a long term net gain. The reality was completely different. Many stores lost money because Groupon users would only put down money for the original deal and not return, some businesses had to dip into their own funds to honor the sheer explosion of discounted sales, and customers who did not have their Groupons honored trashed businesses’ Yelp pages to harm their brand. Groupon’s negative effects on local businesses have been well documented on the Internet, and the company began to gain notoriety as a poor business partner. Shift to the Norm Flash sale business models have by in large dissipated now. Sites such as Rue La La and Totsy have experienced major downsizing. Others have reverted to more standard business models. For instance, after Groupon’s CEO Andrew Mason was fired, the site shifted to an online coupon model that offers discounts valid for longer periods and also a marketplace for discounted wares., which acted as a social media network before offering flash sales, is evolving again, this time into a standard online retailer outfit. Some sites, such as, are even going back to basics with a brick and mortar storefront. It’s true to say that flash sales generated a lot of revenue, but for the key metric of profitability, it’s a whole other story. Already, some industry analysis are comparing Zulily’s rise to Groupon’s, and we all know how the latter has turned out. In fact, Zulily just turned profitable earlier this year, despite showing high levels of sales and active customers the year before. Can the company somehow beat the flash sale fatigue, or will it just be another footnote in the big book unsustainable business models? It is important to differentiate between deal-of-the-day companies such as Groupon and LivingSocial, and the retailers relying on a flash sale model. The main difference is that daily
  10. 10. Page | 10 deal sites tend to primarily offer virtual vouchers for trips or services, as opposed to physical products that can be sent to a consumer’s home. Since there is no clearance of physical goods, purchase activity isn’t as important as the marketing of the web site itself. However, as big as many daily deal companies are, there are still doubts as to how they can grow and beyond their present model. “One of the challenges for this model has been that it is heavy on the sales force side,” Baird said. “They’re actively reaching out to retailers and working with them to try to make a deal that meets Groupon’s criteria, but also achieves a goal for the retailer. The reps I’ve talked to have learned that this model is ‘try, and then hopefully the customer comes back.’ Which means, ‘I’m willing to be confident there’s enough margin in my business that I can make an investment to get you to come in the door.’ From there, it’s on the retailer to try and turn that into a relationship.” Overall, Groupon and LivingSocial are the two frontrunners in the daily deals space, and are the two most recognizable sites in terms of brand name. Although Groupon, a publicly traded company, has higher revenue results than LivingSocial, both companies have had their fair share of misfortune over the past year. Groupon suffered a combined $95.3 million in net losses between Q4 2012 and Q3 2013, and incurred a whopping $81.1 million in loss during Q4 2012 alone. LivingSocial posted a net loss of $183 million in 2013, as disclosed by an regulatory filing. (Amazon owns approximately 30% of the company.) As a result of these lackluster results, LivingSocial is branching away from its daily deal roots, and instead is rebranding itself as a marketing solution for merchants. “We work now with merchants in a lot of interesting was beyond the daily deal model,” said Jake Maas, Sr. VP of Product and Operations at LivingSocial. “That’s still a part of our offering, but we engage consumers across the board, whether that’s through deals, coupons, or even content and other strategies, as well.”
  11. 11. Page | 11 Customer Backlash Via Social Daily deal and flash sale sites do pose a series of benefits, however, many customers have had negative experiences, according to a report from logistics and fulfillment services provider Dotcom Distribution. Of the 2,776 comments posted across 11 of the top U.S. flash site Facebook pages, 44% were negative. Out of the remaining commenters, only 29% posted positive comments, while 27% were neutral. Almost half (49%) of the negative comments were related to shipping issues, with the overarching theme being that most consumers had to wait four to six weeks to receive their packages. Compare that to the average e-Commerce experience, where customers can receive purchased items in 10 days or less. Fab And The Inventory Problem Contemporary home décor eTailer Fab was one of the first major flash sale success stories, but moved away from the flash sale business model in July 2013 to a more traditional online business strategy. The switch coincided with a series of layoffs in July, October and November, which nearly cut the company’s workforce in half. Within this time, Co-Founder and Chief Design Officer Bradford Shellhammer departed from the company. (Shellhammer still serves as a non-executive advisor to the company). Fab Co-Founder and CEO Jason Goldberg explained the business shift in a July 2013 post in his personal blog, Betashop Quarterly: “Over the past couple of years we realized that in order to exceed the expectations of our customers… that we would need to shift our business model to an inventory planning model,” Goldberg said. “We are building a scalable model that allows us to sell the same products simultaneously everywhere around the globe while giving our customers complete confidence in their purchases. That was hard to do with flash sales as products would come and go from Fab daily; the nature of flash sales dictates that products are not kept in inventory and are thus very difficult to ship fast or for free.” Although the appeal of discounted luxury products is undeniable, placement of these products on flash sale sites doesn’t guarantee retail success. This “inventory problem” poses a threat to flash sales companies due to increasing costs incurred whenever products go unsold.
  12. 12. Page | 12 “If I’m a brand and I have an inventory problem, I’m looking for alternative channels to relieve me of that inventory,” said Mona Bijoor, CEO of JOOR, an online wholesale fashion marketplace. “Flash sale sites initially seem to be a great alternative to the traditional channels where they’re liquidating your inventory at very low prices. These sites are photographing the items, marketing them and putting on SEO tags, but the reality is there’s a reason why the inventory didn’t sell in the first place. Some of it gets sold, but some of it stays, and there’s a holding cost to keep that inventory around. If you’re selling furniture or clothes in a flash sales model, the longer those things stay in a warehouse, the less valuable they become.” Flash Sales: Not Just Suited For E-Commerce Generally, flash sales sites have products listed for a few days, then have another set of products in line to replace them once the sale period runs out. This rotation keeps the online shopping experience fresh and heavily appeals to consumers who are looking for diverse selections. However, major players such as Gilt, Rue La La and Zulily are now also selling their own exclusive private-label merchandise, which could be taken as an indicator that the business model on its own isn’t bringing in the desired profit. “It’s getting harder for flash sale companies to select inventory that’s going to sell through that channel,” Bijoor said in an interview with Retail TouchPoints. “They’re trying to understand what products are selling so they can privately label them before putting them on the market. That allows them to make more margins, but that’s not really flash sales. That’s just becoming a brand and selling more items at full price. Ultimately, that’s becoming a product service company.” This tactic is similar to what some retailers have used to handle customer demands, in which they design lower-cost products exclusively for their outlet stores. “If we hit that point [in flash sales], that will demonstrate where the natural market has tapped out,” Baird said. “Now the brands and retailers that are running that model are actually having to create the supply to meet the demands that exist in that model. I’m pretty sure that the demand for that model will exceed the supply and inventory available the way that the model is structured to be.”
  13. 13. Page | 13 Embracing the Niche Market With much of the initial novelty wearing off over the past two years, flash sale and daily deal retailers are merging into a very pronounced niche market. While Zulily and Gilt are notable leaders in the flash sale space, the market might not be large enough to handle any more ‘front- runners.’ For the most part, opportunities to employ the business model would be best suited in small doses to prevent overspending on products to be sold. Newer companies looking to take advantage may have to take one of two actions: focus on building partnerships with major retailers for the sake of exposure, or differentiate their business by emphasizing one specific product category that appeals to a single demographic. MAJOR TRENDS IN E-COMMERCE BUSINESS • Retail consumer e-commerce continues to grow at double-digit rates. • The online demographics of shoppers continues to broaden. • Online sites continue to strengthen profitability by refining their business models and leveraging the capabilities of the Internet. • The first wave of e-commerce transformed the business world of books, music, and air travel. In the second wave, eight new industries are facing a similar transformation: telephones, movies, television, jewelry, real estate, hotels, bill payments, and software. • The breadth of e-commerce offerings grows, especially in travel, information clearinghouses, entertainment, retail apparel, appliances, and home furnishings. • Small businesses and entrepreneurs continue to flood into the e-commerce marketplace, often riding on the infrastructures created by industry giants such as Amazon, eBay, and Overture. • Brand extension through the Internet grows as large firms such as Sears, J.C.Penney, L.L. Bean, and Wal-Mart pursue integrated, multi-channel bricks-and-clicks strategies.
  14. 14. Page | 14 • B2B supply chain transactions and collaborative commerce continue to strengthen and grow beyond the $1.5 trillion mark. TECHNOLOGY • Wireless Internet connections (Wi-Fi, Wi-Max, and 3G telephone) grow rapidly. • Podcasting takes off as a new media format for distribution of radio and user-generated commentary. • The Internet broadband foundation becomes stronger in households and businesses. Bandwidth prices fall as telecommunications companies re-capitalize their debts. • RSS (Really Simple Syndication) grows to become a major new form of user-controlled information distribution that rivals e-mail in some applications. • Computing and networking component prices continue to fall dramatically. • New Internet-based models of computing such as .NET and Web services expand B2B opportunities. SOCIETY • Self-publishing (user-generated content) and syndication in the form of blogs, wikis and social networks grow to form an entirely new self-publishing forum. • Newspapers and other traditional media adopt online, interactive models. • Conflicts over copyright management and control grow in significance. • Over half the Internet user population (about 80 million adults) join a social group on the Internet. • Taxation of Internet sales becomes more widespread and accepted by large online merchants. • Controversy over content regulation and controls increases. • Surveillance of Internet communications grows in significance. • Concerns over commercial and governmental privacy invasion grow.
  15. 15. Page | 15 • Internet fraud and abuse occurrences increase. • First Amendment rights of free speech and association on the Internet are challenged. • Spam grows despite new laws and promised technology fixes. • Invasion of personal privacy on the Web expands as marketers find new ways to track users 2.3 SCOPE OF THE STUDY:  The study is based on the views of people chosen randomly in mathikere and Bangalore urban areas.  The study attempts to understand and analyze the various views on flash sales and is effectiveness.  Study also attempts to evaluate impact of such strategies on e commerce industry. 2.4 RESEARCH OBJECTIVE: 1. To study how flash sales is used as a revenue mechanism. 2. To evaluate the impact of such strategies on the consumers. 2.5 HYPOTHESES: H0: Flash sales does not have any impact on consumers. H1: There is meaningful relationship between flash sales and consumers’ willingness to buy. 2.6 RESEARCH METHODOLOGY: 1. METHODOLOGY :  Data in the form of primary data collected through questionnaire and secondary data through various surveys conducted.  The statistical tools that can be used for analyzing the data are frequency tables, graph charts, correlation.
  16. 16. Page | 16 2.7 SAMPLING PLAN: Non Random Convenience sampling is the method employed to obtain a sample. The sample size under consideration is 100. The sample members will be respondents – either full time or contractual, without any limitations with respect to gender, position and education qualifications. 2.8 TOOLS FOR COLLECTION OF DATA: Questionnaire is used to collect primary data from customers with regard to get data for consumption patterns. Secondary data is collected from various surveys conducted and information available in newspaper articles, journals and internet. 2.9 PLAN OF ANALYSIS: The research will be carried out in 4 stages. The stages can be described as follows:-  Secondary data collection to understand the how the practices have been used and what were the implications.  Primary data collection to get firsthand information of presently existing strategies and also how the respondents have reacted to it.  Analysis of data collected using statistical tools.  Draw conclusions from the data collected. 2.10 SCOPE OF STUDY:  This study is limited to consumers in Bangalore urban areas only.  The study considers all persons above age of 18.  The study extends to consumers of all types.  This study only spoke to consumers about their views with respect to flash sales strategies, while not considering other contributing factors to online sales generation.
  17. 17. Page | 17 2.11 LIMITATIONS:  The choice of respondents was limited to those available at the time.  Consumers were not freely willing to participate and had to be coaxed. 2.12 CHAPTER SCHEME:  CHAPTER 1- Introduction about flash sales. o The chapter aims to introduce the concept of flash sales and its evolution.  CHAPTER 2- Review of Literature, Purpose and Scope of Study, Statement of Problem. o In this chapter, we learn about the history and research that has gone into flash sales from various authors and researchers. o The chapter also talks about the current study, its purpose, scope and what the study seeks to achieve.  CHAPTER 3- Industry analysis. o This chapter contains information about the e commerce industry on a global scale and national scale, with current trends and growth prospects being discussed as well.  CHAPTER 4- Analysis of Data. o This chapter contains the analysis of the collected data which is presented in form of graphs and charts, with appropriate analysis and inferences.  CHAPTER 5- Summary, Findings and Conclusions of the Study. o This chapter draws conclusions to the study based on summary of findings. o It also suggests a few recommendations and speaks about scope for further research.
  18. 18. Page | 18 Chapter III Industry Analysis
  19. 19. Page | 19 E-commerce in recent times has been growing rapidly across the world. According to Report of Digital– Commerce, IAMAI-IMRB (2013), e-commerce industry in India has witnessed a growth of US$ 3.8 billion in the year 2009 to US$ 9.5 billion in 2012. By 2013, the market is expected to reach US$12.6 billion, showing year to year growth of 34%. Industry sources indicate that this growth can be sustained over a longer period of time as e-commerce will continue to reach new geographies and encompass new markets. E-commerce means sale or purchase of goods and services conducted over network of computers or TV channels by methods specifically designed for the purpose. Even though goods and services are ordered electronically, payments or delivery of goods and services need not be conducted online. E- commerce transaction can be between businesses, households, individuals, governments and other public or private organizations. There are numerous types of e-commerce transactions that occur online ranging from sale of clothes, shoes, books etc. to services such as airline tickets or making hotel bookings etc. The bookings done through electronic communication could be Business to Business (B2B) or Business to Consumer (B2C). Business to Business i.e. B2B is e-commerce between businesses such as between a manufacturer and a wholesaler or between a wholesaler and a retailer. As per the WTO report WT/COMTD/W/193, global B2B transactions comprise 90% of all e- commerce. According to research conducted by USA based International Data Corporation, it is estimated that global B2B commerce, especially among wholesalers and distributors amounted to US$12.4 trillion at the end of 2012. The bookings done electronically between Business to Consumer for purchase or sale of goods and services is known as B2C e-commerce. Although B2C e-commerce receives a lot of attention, B2B transactions far exceed B2C transactions. According to IDC, global B2C transactions are estimated to have reached US$ 1.2 trillion at the end of 2012, ten times less than B2B transactions. B2C e-Commerce entails business selling to general public/ e- catalogues that make use of shopping place. There are several variants in B2C model that operate in e-commerce arena.
  20. 20. Page | 20 From the point of view of business, there are two models of e-commerce. First model is known as „Market Place‟ model, which works like exchange for buyers and sellers. The „Market Place‟ provides a platform for business transactions between buyers and sellers to take place and in return for the services provided, earns commission from sellers of goods/services. Ownership of the inventory in this model vests with the number of enterprises which advertise their products on the website and are ultimate sellers of goods or services. The „Market Place‟, thus, works as a facilitator of e-commerce. Different from the „Market Place‟ model is the second category of business known as „Inventory Based‟ model. In this model, ownership of goods and services and market place vests with the same entity. This model does not work as a facilitator of e-commerce, being delineated therefrom, but is engaged in e-commerce directly. Status of the global e-commerce industry: According to a report by the Interactive Media in Retail Group (IMRG), a U.K. online retail trade organization, Global business-to-consumer e-commerce sales will pass the US$ 1,250 billion mark by 2013, and the total number of Internet users will increase to approximately 3.5 billion. Around 90% of the global e-commerce transactions are in the nature of B2B, leaving meager 10% as B2C e-commerce. The biggest e-commerce markets are U.S.A. followed by U.K. and Japan. In Asia, China, India and Indonesia are the fastest growing e-commerce markets. Major global e-Commerce companies are,, Walmart, Apple, Dell, e-bay, Mercadolibre Inc., Rakuten Inc., Crate & Barrel, Symantec, Autozone, Microsoft, Gap, Nike, Disney stores, HP, ASOS PLC, Blue Nile Inc. etc. E-commerce in emerging economies: Middle class in many of the developing countries, including India, is rapidly embracing online shopping. However, India falls behind not only US, China and Australia in terms of Internet density, but also countries like Sri Lanka and Pakistan. Sri Lanka has an internet penetration of 15 percent. Better internet connectivity and the presence of an internet-savvy customer segment have led to growth of e-commerce in Sri Lanka with an existing market size of USD 2 billion. Pakistan, with an internet penetration of 15 percent has an existing market size of consumer e-commerce of USD 4 billion. Incidentally FDI in inventory-based consumer ecommerce is allowed in both these countries. (IAMAI-KPMG report, September 2013).
  21. 21. Page | 21 A.T. Kearney's 2012 E-Commerce Index examined the top 30 countries in the 2012 Global Retail Development Index™ (GRDI). Using 18 infrastructure, regulatory, and retail-specific variables, the Index ranks the top 10 countries by their e-commerce potential. The 2012 E-Commerce Index of emerging economies is given as under: Following are some other major findings of the Index: i) China occupies first place in the Index. The G8 countries (Japan, United States, United Kingdom, Germany, France, Canada, Russia, and Italy) all fall within the Top 15. ii) Developing countries feature prominently in the Index. Developing countries hold 10 of the 30 spots, including first-placed China. These markets have been able to shortcut the traditional online retail maturity curve as online retail grows at the same time that physical
  22. 22. Page | 22 retail becomes more organized. Consumers in these markets are fast adopting behaviors similar to those in more developed countries. iii) Several "small gems" are making an impact. The rankings include 10 countries with populations of less than 10 million, including Singapore, Hong Kong, Slovakia, New Zealand, Finland, United Arab Emirates, Norway, Ireland, Denmark, and Switzerland. These countries have active online consumers and sufficient infrastructure to support online retail. iv) India is not ranked. India, the world’s second most populous country at 1.2 billion, does not make the Top 30, because of low internet penetration (11 percent) and poor financial and logistical infrastructure compared to other countries. 3.4 It is seen that countries making in the top list of the table of e-commerce have required technologies coupled with higher internet density, high class infrastructure and suitable regulatory framework. India needs to work on these areas to realize true potential of e- commerce business in the country. Status of e-commerce sector in India: As already mentioned above, growth of e-commerce industry has been phenomenally high. However, its growth is dependent on a number of factors and most important of them is internet connectivity. As per Forrester McKinsey report of 2013, India has 137 million internet users with penetration of 11%. Total percentage of online buyers to internet users is 18%. Compared to India, China, Brazil, Sri Lanka and Pakistan have internet population of 538 (40%), 79 (40%), 3.2 (15%) and 29 (15%) millions respectively. Therefore, lower internet density continues to remain a challenge for e-commerce. According to Report of Digital–Commerce, IAMAI-IMRB (2013), e-commerce is growing at the CAGR of 34% and is expected to touch US$ 13 billion by end of 2013. However, travel segment constitutes nearly 71% of the transactions of consumer e-commerce industry, meaning thereby that e-tailing has not taken of in India in any meaningful way. Share of e-tail has grown at the rate of 10% in 2011 to 16% in 2012. Industry surveys suggest that e-commerce industry is expected to contribute around 4 percent to the GDP by 2020. In comparison, according to a NASSCOM report, by 2020, the IT-BPO industry is expected to account for 10% of India’s GDP, while the share of telecommunication
  23. 23. Page | 23 services in India’s GDP is expected to increase to 15 percent by 2015. With enabling support, the e-commerce industry too can contribute much more to the GDP. Around 90% of the global e-commerce transactions are stated to be in the nature of B2B, leaving meagre 10% as B2C e-commerce. Case of India is no different where most of such transactions are in the nature of B2B. Moreover Indian e-commerce industry is characterized by „Market Place‟ model. It allows large number of manufacturers/traders especially MSMEs to advertise their products on the „Market Place‟ and benefit from increased turnover. The growing e-commerce industry can have a positive spillover effect on associated industries such as logistics, online advertising, media and IT/ITES. Currently e-commerce accounts for 15-20 percent of the total revenues for some of the big logistics companies. The revenue for logistics industry from inventory based consumer e-commerce alone may grow by 70 times to USD 2.6 Billion (INR 14,300 crores) by 2020. Currently, the inventory based consumer e- commerce model alone provides direct employment to approximately 40,000 people and is estimated to create 1 million direct and another 0.5 million indirect jobs by 2020. Low entry barriers have attracted many young and enterprising individuals to try their hand at entrepreneurship. A significant 63% of e-commerce ventures have been started by first time entrepreneurs. Indian e-commerce industry is in nascent stage and is nowhere in the league of big global players. Major domestic e-commerce companies are Flipkart, Snapdeal, Fashionandyou, Myntrainkfruit, Dealsandyou, Homeshop18 etc. Although many factors support the growth of e-commerce in India, the fledgling industry is faced with significant hurdles with respect to infrastructure, governance and regulation. Low internet penetration of 11 percent impedes the growth of e-commerce by limiting the internet access to a broader segment of the population. Poor last mile connectivity due to missing links in supply chain infrastructure is limiting the access to far flung areas where a significant portion of the population resides. High dropout rates of 25-30 percent on payment gateways, consumer trust deficit and slow adoption of online payments are compelling e-commerce companies to rely on costlier payment methods such as Cash on Delivery (COD). As stated earlier, over 70% of all consumer e-commerce transactions in India are travel related, comprising mainly of online booking of airline tickets, railway tickets and hotel bookings. The biggest players in the travel category are, and the IRCTC website for railway bookings. Non-travel related online commerce comprises 25-30 percent of the B2C
  24. 24. Page | 24 e-Commerce market. The unfettered growth of online travel category has been possible because the regulatory and infrastructure issues do not impede its growth. Also, it does not face the infrastructure challenges since the goods need not be transferred physically. Existing regulations on e-commerce in the country: As per extant FDI policy, FDI, up to 100%, under the automatic route is permitted in B2B „e- commerce activities‟. The relevant paragraph of „Circular 1 of 2013-Consolidated FDI Policy‟, effective from 05 April, 2013, is given below: “E-commerce activities refer to the activity of buying and selling by a company through the e- commerce platform. Such companies would engage only in Business to Business (B2B) e- commerce and not in retail trading, inter-alia implying that existing restrictions on FDI in domestic trading would be applicable to e-commerce as well.” Paragraphs (2) (f) and (ix) further provide that “ Retail trading, in any form, by means of e-commerce, would not be permissible, for companies with FDI, engaged in the activity of single brand retail trading or multi-brand retail trading.” As such, extant FDI policy does not permit FDI in B2C e-commerce. Information Technology Act, 2000 provides legal recognition for transactions carried out by means of electronic data interchange and other means of electronic communication, commonly referred to as "electronic commerce", which involve the use of alternatives to paper-based methods of communication and storage of information, to facilitate electronic filing of documents with the Government agencies. India has the Consumer Protection Act 1986. However, nothing in the Act refers explicitly to e-commerce consumers. It provides for regulation of trade practices, creation of national and state level Consumer Protection Councils, consumer disputes redressal forums at the National, State and District level to redress disputes, class actions and for recognized consumer associations to act on behalf of the consumers. The Act provides a detailed list of unfair trade practices, but it is not exhaustive. The legal requirements for undertaking e-commerce in India also involve compliance with other laws like Contract Law, Indian Penal Code, etc. Further, online shopping in India also involves compliance with the banking and financial norms applicable in India. For instance,
  25. 25. Page | 25 take the example of PayPal in this regard. If PayPal has to allow online payments receipt and disbursements for its existing or proposed e-commerce activities, it has to take a license from Reserve Bank of India (RBI) in this regard. Further, cyber due diligence for Paypal and other online payment transferors in India is also required to be observed. Evolution of e-commerce in India The rapid growth of e-commerce in India Over the last two decades, rising internet and mobile phone penetration has changed the way we communicate and do business. E-commerce is relatively a novel concept. It is, at present, heavily leaning on the internet and mobile phone revolution to fundamentally alter the way businesses reach their customers. While in countries such as the US and China, e-commerce has taken significant strides to achieve sales of over 150 billion USD in revenue, the industry in India is, still at its infancy. However over the past few years, the sector has grown by almost 35% CAGR from 3.8 billion USD in 2009 to an estimated 12.6 billion USD in 20131. Industry studies by IAMA2 I indicate that online travel dominates the e-commerce industry with an estimated 70% of the market share. However, e- retail in both its forms; online retail and market place, has become the fastest-growing segment, increasing its share from 10% in 2009 to an estimated 18% in 20133. Calculations based on industry benchmarks estimate that the number of parcel check-outs in e-commerce portals exceeded 100 million in 2013. However, this share represents a miniscule proportion (less than 1%) of India’s total retail market, but is poised for continued growth in the coming years. If this robust growth continues over the next few years, the size of the e-retail industry is poised to be 10 to 20 billion USD by 2017-2020. This growth is expected to be led by increased consumer-led purchases in durables and electronics, apparels and accessories, besides traditional products such as books and audio-visuals. E-commerce logistics models: A radical shift from regular logistics the strong emergence of e-commerce will place an enormous pressure on the supporting logistics functions. The proposition of e-commerce to the customer is in offering an almost infinite variety of choices spread over an enormous geographical area. Firms cannot compete solely based on sheer volumes in today’s ever-evolving, information symmetric and globalized world of e-commerce. Instead, the realm of competition has shifted to delivering to ever-shortening delivery timeliness, both consistently and predictably. Negligible or zero delivery prices, doorstep delivery, traceability solutions and convenient reverse logistics have become the most important elements of differentiation for providers. While the current logistics challenges relating to manufacturing and distribution of consumer
  26. 26. Page | 26 products and organized retail are well-known, the demands of e-commerce raise the associated complexities to a different level. E-commerce retailers are well aware of these challenges and are cognizant of the need to invest in capital and operational assets. Reaching the customer: Going beyond the traditional definition the essence of e-retailing is in its ability to transcend physical boundaries and reach customers in a manner different from the traditional brick-and- mortar stores, to their very doorstep. However, the base of the e-retailing model is technology and logistical solutions that facilitates the customer acquisition and the final ‘reach’ process. E-commerce further brings to the table vagaries in customer orders accompanied with difficult scenarios such as free delivery, order rescheduling, cancellation, returns and cash-on-delivery. Additionally, an expected minimized turn-around-time (TAT) which will potentially lead to word-of-mouth publicity, feedback and customer retention to the e-portal or website. An information network which shares updated information with respect to inventory status, demand schedules and forecasts, shipment schedules and promotion plans among all the stakeholders of the supply chain will form the backbone of an e-retailer. Need for different management of physical infrastructure The business model of the conventional retailers and e-commerce providers differ significantly. The conventional infrastructure model relies on increasing depth and breadth of coverage through several inventory nodes, warehouses and stocking points connected by based on various other factors ranging from production cycles, nature and variety of the SKUs to even local taxation laws. The conventional order point occurs at retail stores and static customer fronts located at the end of the chain, and inventory requirements are predicted empirically based on several months or years of past data. In fact, competing sales channels may also duplicate infrastructure, an indication of the typical sub-ordination of the logistics function within the overall sales and distribution process. On the other hand, e-commerce providers operating either through inventory-led or marketplace models, are entering an entirely different paradigm of operations, where management of the supply chain is core to the business of creating more business. With real- time demand and tight delivery expectations, the supply chain needs to be built from the customer-end, with the fundamental difference being the proliferation of delivery points and the need to move large number of orders of small parcels (one or two goods) across the length and breadth of the country at an affordable cost. In India, foreign direct investment (FDI) within
  27. 27. Page | 27 the business-to-consumer (B2C) e-commerce segment is not allowed where as foreign investment in the business-to-business (B2B) e-commerce segment is allowed. This means that inventory led e-retailing model cannot attract FDI whereas market-place based e-retailing model can still attract FDI. Most e-retailers have started practicing the market-place business model with suppliers storing on their behalf and delivering as per the requirement and thus falling under the B2B category. The need to build infrastructure for increased agility the key to success in e-commerce is an efficient last-mile network to ensure time bound delivery while maintaining agility in the logistics chain. The fundamental SKU at the delivery point is a ‘parcel’, of varying shapes and sizes, while the pin-codes of the operation become the determinant of the last-mile network model. The up-stream infrastructure will then need to be built as a layer over this last-mile network with strategic location choices of fulfillment centers proximal to delivery modes. The operations will need to be tightly controlled in such a way that the inventory stocks are converted to parcels and pushed down the chain efficiently, as well as that the fulfillment centers are replenished. The balance between inventory and supply chain costs is therefore a dynamic decision to be taken, considering both cost and service level considerations. While the conventional logistics models have evolved in a way to expand reach for businesses at the lowest cost in a ‘push’ model, e-commerce businesses will feel the need for greater agility in their supply chain that will be more responsive to customer demands that are variable and less predictable. The sheer variety of the product and destination choices and fulfillment modes will mean that the provider cannot afford to stock the entire supply chain with sufficient inventory to fulfill customer needs. The customer order point will need to be pushed further upstream, from where ‘pull’ from the customer is recognized, tracked and met through rapid fulfillment methods. The implications of product choices on infrastructure networks the network design and the agility of the supply chain will also be influenced by the products carried. E-retailers have been able to attract significant customers to online buying but these are still limited to very exclusive categories such as consumer electronics, apparels and lifestyle, books, music and video. In the future, other categories such as food and beverages, departmental store, home furnishings, auto parts, healthcare and office equipment will also see increased e-commerce activity. It is important to note that each product category will have its own customized logistics requirements which can alter the balance between inventory and supply chain costs. Within the apparel and lifestyle category, for example, localized suppliers or warehouses can be used to
  28. 28. Page | 28 good effect in tune with the buying patterns and ensuring seasonal inventory replenishment. For books, music and video, a large centralized inventory for a large region may be better suited. For consumer electronics and durables, which have lesser SKU proliferation, higher product value and higher security and handling needs, a JIT and direct fulfillment model may need to be put in place. For hot and cold merchandising, localized sourcing and continuous availability of temperature controlled infrastructure throughout the supply chain becomes the critical need. The challenge is to ensure that the supply chain needs of the specific product segments are married with customer propositions that offer better customer value than traditional retail models. Logistics infrastructure to be the weakest link in the Indian e- commerce story Logistics in developing economies such as India may act as the biggest barrier to the growth of the e-commerce industry. Till date, logistics models developed in India target the metropolitan and the Tier-1 cities where there is a mix of affluent and middle classes and the internet penetration is adequate. In India, about 90% of the goods being ordered online are moved by air, which increases the delivery costs for the e-retailers. Most e-retailers were initially dependent on third party delivery firms. However as the market evolves and customer expectations increase, city or geography centric service levels are becoming the need of the hour. Moreover, issues specific to e-retailing such as the problems associated with fake addresses, cash-on-delivery and higher expected return rates have made e-retailers consider setting up their captive capital intensive logistic businesses. For instance, Flipkart has set up several regional warehouses and is constantly increasing the supplier base across the country to achieve low transportation cost by ensuring delivery from the nearest supplier or regional warehouse. Flipkart is growing its logistics arm E-Kart whereas Amazon India is building capacities with its logistic arm Amazon Logistics. While establishing the captive logistics infrastructure was a consequence of need for better service delivery by actively controlling the logistics chain, it has pushed up the delivery costs. According to industry benchmarks, the delivery cost in the captive logistics models are 10 to 20% expensive than the 3PLs whose expertise lies in quick delivery at an affordable cost. Further, the logistics set-up and requirements in developing countries are also dependent on the purchasing behavior of the customers These factors will call for strengthening the logistics infrastructure and increased number of failing which the e-retailers will have to start up or strengthening their own logistics counterparts. Higher delivery costs can result in withdrawal of free delivery by e-retailers on
  29. 29. Page | 29 the back of high delivery costs and complex business models threatening already wafer-thin business margins. Infrastructure will demand a large proportion of investment in e-commerce Active management of logistics, infrastructure and service levels is core to the e-commerce business in any market. E-retailers need to have a hybrid model of their own captive logistics arm which takes care of their specific business model needs and strictly monitored service level agreements with 3PLs to rationalize the delivery costs. The future competitors and winners in the e-retailing space will be the ones which will use both bricks and clicks and not bricks or clicks alone. This is evident from the evolving logistics and storage strategy of Amazon in the US. Amazon has changed its logistics network from the ‘sell all, carry few’, model to the ‘sell all, carry more’ model and increased the number of warehouses across the US. This eventually proved beneficial for Amazon as the increased number of warehouses led to both better reach and range for the suppliers and customers which eventually resulted in faster service delivery and increased customer retention. Amazon is further investing 14 billion USD in increasing its warehouses’ base by 50 in the US. Strictly monitored service level agreements with 3PLs which have developed the expertise and skills to handle the vagaries of the customers in the e- commerce space has proven beneficial for e-retailers as they are able to outsource the skills best suited to the 3PLs. A successful example in terms of usage of SLAs with 3PLs is of eBay which has partnered with couriers and allied service providers for the logistics with closely controlled SLAs. The above requirement will only increase in magnitude when operating in India. The exponential growth in e-retailing will also attract 3PL majors like DHL, FedEx, UPS and Gati to play a crucial role in the last-mile delivery. DTDC has already started offering customized services to e-retailers under the name Dotzot. To cater to this potential explosive growth in the absence of a ready-built industry structure, significant investments will need to flow into creating back bone logistics infrastructure from e-commerce providers or 3PLs. Industry interactions indicate that market place operators typically invest 10 to 20% of their revenue to build self-owned infrastructure. Investments in infrastructure and operating models of the future The growth in e-retailing will spawn several investments in logistics infrastructure including large fulfillment centers and warehouses, downstream parcel and sortation centers, focus will be on equipping these nodes with state-of-the-art technology and modern warehousing practices promoting visibility across the logistics chain. The kind of infrastructure will not only be bare bone shells but will focus on specific handling requirements of the
  30. 30. Page | 30 commodities transacted. As times becomes the essence of delivery, quicker modes of transportation and reduced transit times will increasingly become the key demands. Currently, India operates at a very low level of air cargo penetration characterized by only a few airports equipped to handle large volumes of express delivery parcels. As the race to the market moves to the Tier 2 and Tier 3 cities a day may not be far off when there is an increasing demand of expanding air cargo connectivity to smaller towns through various merry-go round aircrafts using charter airplanes and general aviation. Airport operators including the Airport Authority of India (AAI) needs to carefully evaluate this particular category of air cargo on par with other categories of airport infrastructure development Similarly, for certain product categories, railways movement can also be explored. The Indian railways is exploring various schemes like parcel trains and increasing the competitiveness of parcel loads in passenger trains. For certain commodities on the short haul routes, railway can become a predictable and low-cost transport choice. Therefore the whole transportation paradigm of the future may evolve around a judicious mix of rail, road and air transport modes. Economic potential due to the rise of e-commerce logistics the rising growth and complexity of e-commerce categories and delivery networks is expected to have a large spill-over to infrastructure and logistics investments which will include more warehouses, sortation and delivery centers and employment. Based on current productivity trends and growth estimates, it can be estimated that over the next three to four years, there will be an addition of 7.5 to15 million sq. ft4 in the form of additional central fulfillment centers alone with an average size of 80,000 to 1, 50,000 sq. ft. each. This, by itself represents an additional 6 to 12% of all the space available in the form of organized warehousing in India and almost 25 to 50% of all incremental addition of consumption-driven warehousing space5 in the same period. To enhance the reach further to match the growth in warehousing, additional sortation and delivery centers will also be critical. Such additional centers with each measuring around 10,000 to 20,000 sq. ft. will be added. Industry estimates6 reveal that the total spend on warehousing and sortation centers could be as high as 3 to 6% of top-line revenues, which represents an cumulative spend of over 450 to 900 million USD of spend in warehousing till 2017-2020. The industry is expected to spend an additional 500 to 1000 million USD in the same period on logistics functions, leading to a cumulative spend of 950 to 1900 million USD till 2017-2020. It is also estimated that currently over 25,000 people7 are employed in e-retailing warehousing and logistics. Even with efficiency improvements in individual performance and productivity
  31. 31. Page | 31 (IPPs) in the delivery networks, it is estimated that there will be an additional employment of close to 75,000 people in these two functions alone8 by 2017-2020, representing an increase in employment by almost three times. Trends to watch out for • Evolution of logistics landscape in the country will be a very important factor in determining the course for the e-retailing industry. Logistics evolution will be necessary to realize the potential robust growth. • Despite a huge potential, long term profitability of the e-retailing industry in the country is still under question. After so many years of operations, all the major e-retailers are yet to start making profits. In the wake of wafer-thin margins and sub-optimal infrastructure resulting in higher delivery cost, the long-term profitability still seems a distant possibility. • FDI in the inventory-led retail will also be an important factor in shaping up the future of the industry. In the current scenario, global e-retailing giants like Rakuten and Alibaba are eyeing an entry into Indian e-retail market. Amazon has recently announced a 2 billion USD investment operating on marketplace model. FDI allowance could be a vital factor in attracting significant investments resulting in better infrastructure and robust supply chains. • Evolution of taxation policies in the country will in a large way effect the way industries practice warehousing. With uniformity in taxation laws across the country, e-retailers are expected to move closer to consumption centers with an aim to address the duplicities in the logistics chain by removing the overlaps in form of delivery and sortation centers which are traditionally closer to the consumption centers. It will also result in uninterrupted access to the e-retailing market. In a recent case, a south Indian state had sent a tax notice to e-retailers resulting in all e-retailers withdrawing services in the particular state because of differing tax policies. • The evolution of the existing logistics providers and more players entering the 3PL domain will result in realization of the huge potential of the e-retailing industry. Major 3PL players (such as FedEx, DHL, UPS, Gati, etc.) will have to gear up to the increasing demands of the e- retailing industry thereby helping in rationalization of delivery costs and provide much needed balance between using captive logistics network and 3PLs. To take the opportunity and help the e-retailing industry to overcome infrastructural bottlenecks, resurrection of the Indian
  32. 32. Page | 32 Postal Service can be a game changer. Collaborating the strong last-mile capability with technological up gradation will ease the dependence on the other modes of transportation. After taking a holistic view of the industry trends, e-commerce is poised for an exciting period of exploding growth in a period of three to five years. This is expected to lead to substantial investments in supporting infrastructure and innovative and game changing business models. SWOT Analysis: Strengths:  Attraction to the firm  Builds brand recognition & loyalty  Drawing attention for new firms  Attracting new demographics to old firms - Saks Fifth  Selling surplus  Grow revenue  Increasing store traffic  Perception of scarcity Weakness:  May feel forced to slash prices too dramatically in order to keep up with the competition  If not involved, can easily loose out sales to competitors Opportunities:  Flash sales as division of company E-bay, Neiman Marcus & Saks – already have own flash sale components to sell unsold merchandise Haute look sold to Nordstrom earlier this year for $270 million. The Gilt Group nearing a $1 billion evaluation  Mobile applications  Deals based on GPS location on mobile device
  33. 33. Page | 33 Also on personal info on device (searches, texts, etc.)  More/better aggregate platforms like Yipit Threats:  Backlash on social media can lead to bad publicity  Minimal margins no good for business growth in terms of revenue  Customers get used to discounts and start demanding them.
  34. 34. Page | 34 Chapter IV Data Analysis
  35. 35. Page | 35 DATA ANALYSIS The data after collection has to be processed and analyzed in accordance with the outline laid down for the purpose at time of developing the research plan. This is essential for scientific study and ensuring that we have all relevant data for many contemplated comparisons and analysis. Technically processing implies editing, coding, classification and tabulation of collected data so that they are amenable for analysis. The term analysis refers to the computation of certain measures along with searching for patters of relationship that exists among data groups. Thus, “in this process of analysis, relationships or differences supporting or conflicting with original or new hypothesis should be subjected to statistical tests of significance to determine with what validity data can be said to indicate any conclusions. Analysis of data in a general way involves a number of closely related operations that are performed with the purpose of summarizing the collected data and organizing these in such a manner so they answer the research questions. In the following analysis, we are going to use the collected data and test them to either accept or reject our null hypothesis and therefore come to a conclusion about the impact of participative management strategies and job satisfaction.
  36. 36. Page | 36 Table 2: Gender of respondents Gender Frequency Male 63 Female 44 Total 107 Analysis: The percentage of male respondents is 59% and female respondents are 41%. Chart 1: Gender Respondents Inference: Most respondents are Male by gender. While the gender by itself does not play a major role in this study, the preference of genders towards categories of products is linked to the gender. Male 59% Female 41% Gender
  37. 37. Page | 37 2. Income Category: Table 3: Income category of Respondents Category Frequency NA 69 0-2 lakhs p.a. 8 2-4 lakhs p.a. 12 4-6 lakhs p.a. 13 Above 6 lakhs p.a. 5 Total 107 Analysis: It is seen that 65% of respondents are in the non-earning category, 7% are 0-2 lakhs p.a., 11% are 2-4 lakhs p.a., 12% are 4-6 lakhs p.a. and 5% are above 6 lakhs p.a. Chart 2: Income Category of Respondents Inference: Most respondents are in the non-earning and are at the dependency of limited incomes and this has an impact on buying behavior and willingness to make the most of discount opportunities by way of flash sales. 65%7% 11% 12% 5% Income Category NA 0-2 lakhs p.a. 2-4 lakhs p.a. 4-6 lakhs p.a Above 6 lakhs p.a.
  38. 38. Page | 38 3. Age of respondents: Table 4: Age of respondents Category Frequency 18-20 3 21-25 89 26-30 12 31-35 2 Above 35 1 Total 107 Analysis: It is seen that 83% of respondents are of age 21-25, 11% are 26-30, 2% are 31-35,3% are above 35 and 1% are 18-20 Chart 3: Age of respondents Inference: A majority of the respondents were young adults, who have generally good grasp of technology are favorable to using those means. This means a good number of them would not be hindered by not knowing how to access flash sales and participate 3% 83% 11% 2% 1% Age 18-20 21-25 26-30 31-35 Above 35
  39. 39. Page | 39 4. Occupation Table 5: Occupation of respondents Category Frequency Student 81 Employed - private business 19 Employed - Own business 5 Government Employee 1 Others 1 Total 107 Analysis: It is seen that 76% respondents are students, 18% are Employed-private business, 4% are employed –Own business and 1% are Government employee and others Chart 4: Occupation of respondents Inference: The fact that over 3 quarters of respondents were students would imply a dependency on income available for spending, which is an influence on buying behavior as well as the inclination to be updated as far as latest trends in clothing or electronics is concerned 76% 18% 4% 1% 1% Occupation Student Employed - private business Employed - Own business Government Employee Others
  40. 40. Page | 40 5. I am aware of the concept of flash sales Table 6: Awareness of flash sales Category Frequency Nil 16 Somewhat aware 32 Moderately aware 28 Well aware 25 Fully aware 6 Total 107 Analysis: It is seen that 30% respondents are somewhat aware of flash sales, 26% respondents are moderately aware of flash sales, 23% respondents are well aware of flash sales, 15% respondents are not aware of flash sales and 6% respondents are fully aware of flash sales
  41. 41. Page | 41 Chart 5: Awareness of flash sales Inference: A review of the statistics suggests a rather dim awareness of flash sales. This could be attributed to the concept being very rarely used in India and in fact, is just finding relevance in India’s e commerce story. 6. I have participated in flash sales events: Table 7: Frequency of use Category Frequency Never 1 Rarely 19 Sometimes 60 Mostly 18 Always 9 Total 107 Analysis: It is seen that 56% use flash sales sometimes, 18% use flash sales rarely, 17% use flash sales mostly, 8% use flash sales always, 1% never use flash sales for making purchases online 15% 30% 26% 23% 6% Awareness of Flash Sales Nil Some what aware Moderately aware Well aware Fully aware
  42. 42. Page | 42 Chart 6: Frequency of use Inference: A review of the statistics shows a moderate use of flash sales as a means to buy online. While this shows that it may not be the preferred choice for many consumers, it does leave a lot of potential for the right kind of marketing. 7. I have participated in flash sales events Table 8: Participation in Flash Sales Category Frequency Never 42 0-2 times 50 3-5 times 11 5-7 times 2 Above 7 times 2 Total 107 Analysis: It is seen that 47% respondents participate 0-2 times, 39% respondents never participate, 10% respondents participate 3-5 times, 2%of respondents participate 5-7 times or more than that. 1% 18% 56% 17% 8% Frequency of Use Never Rarely Sometimes Mostly Always
  43. 43. Page | 43 Chart 7: Participation in flash sales Inference: A high percentage of respondents have not participated in flash sales too many times. This could be attributed to the concept being rather new and the awareness being quite moderate about the concept. 8. I like buying products in online because: Table 9: Reason for shopping online Category Frequency Convenience 69 Pricing 43 Varied choice of products 44 Better Quality of products 2 Total 158 Analysis: It is seen that convenience is a deciding factor for 63 respondents, 43 of them preferred shopping online due to prices being favorable, varied choice of products brings 43 respondents towards online shopping and only 2 felt they shopped online for better quality of products (the number of choices exceeds respondents due to multiple choices being available). 39% 47% 10% 2% 2% Participation in Flash Sales Never 0-2 times 3-5 times 5-7 times Above 7 times
  44. 44. Page | 44 Chart 8: Reason for shopping online Inference: Convenience of shopping from anywhere is a major factor deciding the success of online sales along with pricing and choice of products as other important factors. These factors along with the quality of service decide the preference of platform for shopping. 9. I like buying products during flash sales because Table 10: Reasons for preference of flash sales Category Frequency Prices are competitive 80 Sense of achievement 24 Varied choice of products 35 Better Quality of products 8 Customer Service 6 Delivery Time 9 Other: 1 Total 163 Analysis: It is seen that competitive prices are competitive factor for 80 respondents, 24 of them preferred shopping online due to a Sense of achievement on buying the product, varied choice of products brings 35 respondents towards flash sales while 8 felt they liked flash Convenience Pricing Varied choice of products Better Quality of products Series1 69 43 44 2 0 10 20 30 40 50 60 70 80 Percentage Reason for Shopping online
  45. 45. Page | 45 sales for better quality of products. Added services such as customer service, delivery time and others was the preferred factor by 6, 9 and 1 respondents respectively. (The number of choices exceeds respondents due to multiple choices being available). Chart 9: Reasons for preference of flash sale Inference: It is quite clear that competitive prices are the major reason for flash sales being preferred, closely followed by varied choice of products and sense of achievement. 10. Type of products frequently purchased Table 11: Type of products frequently purchased Category Frequency Electronics 69 Apparel 52 Utilities 26 Other: 1 Total 148 Analysis: It is seen that electronics is a preferred category of shopping for 69 respondents, 52 of them preferred shopping online for apparel, choice of utilities brings 26 respondents towards online shopping and only 1 felt they shopped online for other products (the number of choices exceeds respondents due to multiple choices being available). 0 20 40 60 80 100 Reasons for preference of flash sale
  46. 46. Page | 46 Chart 10: Types of products frequently purchased Inference: Electronics and apparel were the preferred choice of products amongst the respondents with utilities being the next shopped option. 11. Reasons for dislike of flash sales Table 12: Reasons for dislike of flash sales Category Frequency Possibility of forgery 11 Not getting the product because of competition 59 Too much clutter 39 Security issue (Online payment risks) 13 Physical examination not possible before purchase 22 Other: 2 Total 135 Analysis: It is seen that Possibility of forgery is a repelling factor for 11 respondents, 59 of them did not like flash sales for the fear of disappointment on not getting the product because of competition, varied choice of products also bring clutter which was unattractive to 39 Electronics Apparel Utilities Other: Series1 69 52 26 1 0 10 20 30 40 50 60 70 80 Percentage Type of products frequently purchased
  47. 47. Page | 47 respondents, the issue of online security and data privacy during online money transfer was a put off for 13 respondents towards online shopping and 22 felt the lack of physical examination of products made flash sales unfavorable. (The number of choices exceeds respondents due to multiple choices being available). Chart 11: Reasons for dislike of flash sales Inference: The disappointment of losing out on a preferred product is a major thumbs down towards flash sales according to the respondents who also felt physical examination of products and security of data among other things like too much clutter of products on view worked against them using flash sales 12. Overall satisfaction of participation in flash sales: Table 13: Overall satisfaction of participation Category Frequency Poor 0 Average 35 Good 49 Very Good 14 Excellent 6 Not Applicable 3 Total 107 0 20 40 60 80 Reasons for Dislike of Flash sales
  48. 48. Page | 48 Analysis: It is seen that 46% respondents say its good, 33% respondents say its average, 5% say its poor, 3% not applicable Chart 12: Overall Satisfaction Inference: The overall satisfaction of respondents towards online and flash sales is mostly positive. While there is definitely room for improvement in terms of attracting users and potential buyers, the start is definitely encouraging considering the infancy of flash sales in India. 0% 33% 46% 13% 5% 3% Overall Satisfaction Poor Average Good Very Good Excellent Not Applicable
  49. 49. Page | 49 Chart 13: Correlation Analysis: Analysis: There is very high correlation between income and occupation. There is also a high correlation between frequency of use and satisfaction experienced overall, as with awareness of flash sales. A moderate correlation is seen with age and participation in flash sales as well as occupation and participation in flash sales. Inference: These correlations show an influence of multiple factors on whether buyers shop online, whether they use flash sales and the factors also decide, to a good extent the kind of products that would generally be chosen on these platforms 0 10 20 30 40 50 60 70 80 90 100 Never Rarely Sometimes Mostly Always
  50. 50. Page | 50 Table 14: Correlation Analysis Hypotheses testing: Our understanding from this study is that there is moderate influence of the use of flash sales as a mechanism to attract consumers to online shopping and flash sales plays a moderate role in influencing buying behavior. This suggests a limited use of the concept, but as illustrated earlier, this also represents a lot of potential as awareness is low. income age occupation awareness frequency participation satisfaction Never 69 3 81 16 1 42 0 Rarely 8 89 19 32 19 50 35 Sometimes 12 12 5 28 60 11 49 Mostly 13 2 1 25 18 2 14 Always 5 1 1 6 9 2 6 income age occupation awareness frequency participation satisfaction income 1.0000 Age - 0.2932 1.0000 occupation 0.9646 - 0.0564 1.0000 awareness - 0.2136 0.6289 -0.1508 1.0000 frequency - 0.4379 0.0488 -0.4889 0.5450 1.0000 Participation 0.4785 0.6947 0.6776 0.3681 -0.2793 1.0000 satisfaction - 0.5191 0.4825 -0.4611 0.7596 0.8983 0.0548 1.0000
  51. 51. Page | 51 Chapter V Discussion
  52. 52. Page | 52 Summary of Findings: 1. The majority of respondents were students and non-income earning category. This meant that complete buying decision was not likely to have been theirs, given the dependency for decision making and income on the parental discretion. 2. Most of them were young adults, which meant an affinity for trying new things as well as comfort with technology. 3. The awareness to flash sales was moderate though almost all were aware of online shopping and were using it regularly. 4. The most preferred categories of products were electronics and apparels. 5. The concept of online shopping had both pros and cons in terms of convenience and low prices against security issues and competition among buyers. 6. The overall satisfaction is good, which is a decent start but there is much desired to fully realize the potential of market. 7. Frequency of use and awareness bring about a greater understanding of the concept and thus increase satisfaction, leading to continual business.
  53. 53. Page | 53 Recommendations: 1. The awareness of the concept must be increased in order to realize full value of potential. 2. The loopholes in terms security and defective products must be taken care of and thus bring credibility. 3. Value adds such as delivery times and customer service can be a differentiating factor. 4. The right kinds of products must be showcased to avoid clutter 5. Encash on growing internet reach to attract more users to online shopping and thus flash sales can be used as an attraction. 6. Create a hype with social media marketing to have a rollover publicity effect and thus bring about awareness of the concept to increase sales.
  54. 54. Page | 54 Conclusion: As we have seen in this study, the whole concept of online shopping is just finding its feet in India. Additionally, the relative unawareness of flash sales concept is something that can be rectified by effective marketing as well as awareness campaigns which could increase sales by attracting customers or potential buyers. Flash sales does have its cons as we have seen in terms of emotional disappointment, clutter and heavy competition, which is why there must be credibility on part of the seller during the execution of these campaigns. Further scope for research exists in terms of evaluating the relevance of the concept once it has become a relatively common concept with its effect on buying behavior then – will it still hold its charm or become a nonexistent factor in the eyes of the consumer.
  55. 55. Page | 55 References: passing-fad sales-and-private-sales Flash-Sales-and-Daily-Deals-Be-for-Travel-#.VOyHMnyUeX8 _sales_sites.pdf df lashSales.pdf https://images-na.ssl-images-
  56. 56. Page | 56 Appendix Questionnaire Flash sales and its impact on customers’ buying behavior * Required 1. Name *
  57. 57. Page | 57 2. Gender * o Male o Female 3. Income Category * o NA o 0-2 lakhs p.a. o 2-4 lakhs p.a. o 4-6 lakhs p.a o Above 6 lakhs p.a. 4. Age * o 18-20 o 21-25 o 26-30 o 31-35 o Above 35 5. Occupation * o Student o Employed - private business o Employed - Own business o Government Employee o Other: 6. I am aware of the concept of flash sales * o Nil o Some what aware o Moderately aware o Well aware o Fully aware 7. I shop online for my utilities and other purchases * o Never o Rarely o Sometimes o Mostly
  58. 58. Page | 58 o Always 8. I like shopping online because (please tick applicable choices) * o Convenience o Pricing o Varied choice of products o Better Quality of products 9. I have participated in flash sales events * o Never o 0-2 times o 3-5 times o 5-7 times o Above 7 times 10. I like buying products during flash sales because (please tick applicable choices) * o Prices are competitive o Sense of achievement o Varied choice of products o Better Quality of products o Customer Service o Delivery Time o Other: 11. Type of products frequently purchased in flash sales (please tick applicable choices) * o Electronics o Apparel o Utilities o Other: 12. Reasons for dislike of flash sales (please tick applicable choices) * o Possibility of forgery o Not getting the product because of competition o Too much clutter o Security issue (Online payment risks) o Physical examination not possible before purchase o Other: 13. Overall satisfaction of participation in flash sales * o Poor
  59. 59. Page | 59 o Average o Good o Very Good o Excellent o Not Applicable