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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
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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
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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.
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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.
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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 Woot.com 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
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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
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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. Fab.com, 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
Gilt.com, 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
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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 Amazon.com
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.”
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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.
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“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.”
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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.
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• 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.
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• 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.
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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.
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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.
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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.
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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 Alibaba.com, Amazon.com, 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).
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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
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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. 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 Makemytrip.com, Yatra.com and the IRCTC website
for railway bookings. Non-travel related online commerce comprises 25-30 percent of the B2C
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 6.2.16.2.1 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 6.2.16.4 (2) (f) and 6.2.16.5(1) (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. 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. 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. 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. 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. 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. 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. 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. 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. 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.
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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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
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. 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. 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.
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. 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. Page | 59
o Average
o Good
o Very Good
o Excellent
o Not Applicable
