SEASONext: NTADBM Group 6
Transcript of SEASONext: NTADBM Group 6
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New Technology Applications
Design & Business Models(NTADBM)
IIM NID joint courseJuly to September 2011
Group 6Madhumanti Ghosh
Chayan DebNitin Kumar
Abhilash Gajula
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Table of Contents:
Introduction..2
Current scenario...3
Proposed structure...4
About the app...5
Target customer segment.9
Value proposition.9
Channels.10
Revenue stream..10
Key resources needed.11
Cost Estimation for developing the app ........................................................................................11
Pricing the App ..............................................................................................................11
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Introduction:
Among the fastest growing industries in the world today is the fashion industry. Change is something
that has remained constant in the fashion industry since time immemorial. The fashion industry in
India currently is considered dynamic. Over the last few decades the fashion industry in India has
experiencing a boom due to the ever increasing fashion consciousness among Indians. Be it the
middle aged home maker, the sporty college kid or the working professionals, everyone seems to have
developed a fashion sense which is distinct and classy.
Apparels are a major part of fashion throughout the world. Indians really believe in the famous
saying "Clothes maketh a man". A person more often than not is judged by the way he/she is dressed.
Apparels define the personality of a human being. It talks a lot about his/her education, personality
and way of thinking. It is said that it is the massive Indian fashion consuming class that will set the
global fashion industry in the next few years.
The boom in the Indian apparel industry is mainly due to factors like, rising incomes levels of Indians,
liberal trade policies adopted by the government, and flexible investment policies on the apparel
industry. Today most of the international brands have found their way into some of the best malls in
the country. Brands like Mango, Armani and Diesel were unheard off in India till a few years back but
today these brands are found in almost all Indian cities.
It is said that in the last ten years the fashion industry in India has moved from a very nascent stage to
a full fledged booming industry. The value of the apparel market in India is estimated at
around Rs 20, 000 crore. The branded apparel market's size is Rs 5, 000 crore which is a quarter of
the total share. The apparel market in India is categorized into branded and non branded. The Top
Apparel Brands in India are Madura Garments, Arvind Mills, Provogue Zodiac Clothing, and
Raymonds. Apart from these brands India over the years has given birth to some of the finest
designers who have become famous brands not only in the country but in the world. The introduction
of a number of designers in the fashion industry has given a further boost to the Indian fashion
industry. According to recent research conducted by the (FDCI) Fashion Design Council of India
apparels created by designers in India is going to play a major role in the growth of the apparel
industry in the next few years. Currently the Indian fashion designer industry stands at Rs 180 crore
and is expected to grow to Rs 1, 000 crore within the next decade. (mapsofindia, 2011)
Let us consider the retail scenario of the clothing industry in India. From a high level, it is somehow
like this:
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The cycle in clothing retail is six month long; they are referred to as season: spring-summer and
autumn-winter. The designer takes inputs from the trend forecast for the upcoming season and designs
accordingly. The marketing & sales people, considering many factors, decide on the amount of
production. The products reach the stores, from where the consumer buys them.
Current scenario
The above diagram exhibits the product flow in the current environment. Product design starts from
the designer and the sales and marketing department is responsible for promotions and demand
estimation. The designs are then sent into production from where they got to the retail stores. The
final purchase is made by the customer and the subsequent records revenue generated is collected and
analysed by the marketing department for further insights into buying patterns. However, there is no
direct interaction between the designers (who actually design the apparels) and end customers(who
ultimately use the product). There is no way of anticipating the customer preferences and designingapparels to suit their tastes. This leads to a disconnect between the customers and the designers.
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Design insights are limited only to a few marketing and preference surveys conducted occasionally by
the marketing people. A direct form of communication between the customers and designers would
help in meeting the consumer expectations and maximising profits for the company.
Proposed structure:
An application which would enable the customers to directly give their feedback to the designers
would go a long way in meeting the demand-supply mismatch. This would help the designers to
prospectively assess the consumer tastes across a variety of customers and design apparels
accordingly. The app would be mutually beneficial as the customers now have a say in the designing
of apparels they want to wear.
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About the app:
SEASONext is an application which can plug in this gap. It is a smart phone application which will
essentially collect preferences from consumers and help the producer verify the forecasted trend
beforehand and thereby correctly estimate demand for the upcoming season.
SEASONext will have 2 interfaces One for the consumer and the other for the producer. In the
consumer interface, SEASONext will offer its user a finite set of option selected by the designer. The
various options can be of styles, fabrics, colours, and accessories. The user can play around with them
and select a desired garment, and know its approximate price as well. All the inputs from consumer
feed into a database. For the purpose of maintaining quality of incoming data, SEASONext can be
only for the loyalty card holders. Respondents will be rewarded with points on their loyalty card.
From the point of view of a consumer, an emotional incentive will be the freedom to exercise his/her
choice. Moreover, he/she can know the price of upcoming garments beforehand.
Leveraging on the already existing social CRM structure- using the database of the loyalty customers
along with the data from consumers, SEASONext can offer the producer a data view according to
his/her needs. For example, if someone from the producer side, say the marketing people, wants to see
which combination of style, fabric and accessory was most popular in the eastern region amongst
female consumers aged between 25 and 30, SEASONext will provide the information in a
comprehensive manner. Access to such information, can help to validate on forecasts-thereby
minimize the risk of demand-supply mismatch.
Lets look at the business plan from the point of view of the software application vendor. The vendor
will sell the application to the retailer at a fixed price and with inputs from their designer, configure it
for them for every season. The data that the retailer gets from the consumers is an important asset to
them. Since SEASONext provide the retailer with this data, the vendor could levy a variable charge
according to the amount of data it gets.
Another parallel line of business for the application vendor can be for smaller design houses,
boutiques and tailors. Here it can be used to offer the customers an immediate showcase of how a
garment will look with different fabric, or in a different colour. Here the application need not be
customized every season, and moreover there wont be a need for data storage at backend, the
application can be offered at a very low price.
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Customers view 1:
The app user can browse through the product offerings of all the branded retail chains the app has
partnered with. She can select any apparel according to her choice and customize it too.
The screen would also display a few advertisements put up by other retail apparel stores. This would
help the user compare between the offerings across a large number of stores. Suppose, the app has a
contract with four retail stores. This would imply that the product range of the four stores would be
displayed by the app. By browsing through the entire range, the consumer becomes aware of almost
all kinds for products which are to be launched by the stores. She is thus, in a better position to make
an informed choice of the apparel she wants to be wearing the next season.
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Customer view 2:
User can then simulate and recreate the original proposed design by adding in the desired colour
schemes.
Customer view 3:
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The above illustration indicates the final stage of design selection by the user. Once she has selected
the outfit of her choice, she can indicate whether she is satisfied by the look and design of the apparel
or not. An approximate price of the outfit will also be indicated along with the final design.
Manufacturers view:
The above figure illustrates the app interface from the manufacturers viewpoint. Based on the
response of the app users, the percentage indicates the number of people who opted for purchasing
that specific apparel once it comes into the market. Although indicating the preference does not mean
that the users will certainly be purchasing the product, but it gives the manufactures an insight into the
consumer preferences nevertheless. One of the key advantages would be the scalability of the
population. For example, if 1000 known customers are using the app, then the responses (and
subsequently the production) of the user base would be scaled up by 100 times, if the total target
population is 100000.
Based on the estimates indicated by the app, manufacturers can now make a reasonable and accurate
estimate of the amount to be produced. This would not only reduce wastage, but also maintain
customer involvement which is essential for brand loyalty.
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Target Customer Segment:
The primary objective of the app is to provide an opportunity for the customers to voice their opinion
regarding the upcoming fashion trends. Thus the target segment comprises of loyal customers of the
top five fashion brands. The app requires genuine feedback from serious shoppers. Thus, loyalty card
holders at major garment houses will be the key target segment.
It has been observed that a concise estimate can be arrived by targeting the fashion conscious people
belonging to the upper and upper middle class people. The segment will consist of both males and
females belonging to the 18-45 years of age group. This group also includes of working women who
dont get enough time to shop for themselves. Also, it comprises of regular smartphone users and easy
access to the internet. Existing channels would be utilized in communicating with the target segment.
Value proposition
For end customers: The app would provide an elaborate range of popular fashion trends. Users
would be able to simulate and modify the color and indicate their preferences. It would lead to a case
of customer empowerment wherein the customers can now voice and suggest their preferences. When
a customer sees an apparel design he/she had suggested in a store, it would result in high emotional
connect between the customer and the brand. It would provide loyal customers with brands discount
offers based on the number of clothes they offered to design and also the appropriateness of the
design.
For Cloth Houses: Managing inventory is one of the major concerns for large apparel stores. Owing
to the highly variable demand, stores bear the risk of both excess inventory and frequent stockouts.
This app would make the demand estimation easier. Inventory losses would be minimized. Regular
feedback would ensure better understanding of consumer preferences. As the customer uses the appfeaturing only a handful of apparel chains, it would also promote brand loyalty.
Channels:
The apparel stores with whom the app would be collaborating will have to put up banners and
catalogues providing the details and the benefits associated with the app. Loyalty card holders would
be provided with more information and even a sample trial so as to get them interested. As the app
would be more useful for loyalty card holders (as only they can indicate their preferences), regular
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customers will now have an incentive to migrate towards the loyalty program.Thus even the stores
would be willing to provide generous advertisement space for the app. Apart from the point of
purchase promotions, advertisements would be displayed on popular free app websites. As the app
would be free to download by all, having a good visibility is important. Thus, the video of the app
would also be launched on popular social networking sites like youtube, twitter, facebook etc.
Revenue Model:
A large sample size would be essential to make this app a success. Thus, it would available for
downloading free of cost. A user can browse through the fashion trends and simulate a dress of his/her
choice for free. The idea is, not to burden the users with any hidden or extra cost which may hamper
her from using the app regularly. However, the apparel stores would be charged each time a user
indicates her preference. The data regarding the user preferences would be very valuable to thecompanies as it would help in forecasting the demand of each line of clothing. A variable pricing
structure, comprising a fixed and a variable component would be implemented. Revenue will also be
generated from in app advertisements. Other retail stores, who are not in collaboration in the app
would like to get their new offerings featured once the popularity of the app picks up.
The Indian women apparel market has undergone a transformational phase in the past few years.
Growing number of working women, changing fashion trends, rising level of information and media
exposure, entry of a large number of foreign brands have given a new dimension to the industry. As a
result, many speciality apparel stores for men have started diversifying into women wear to exploit
the highly lucrative market which was estimated to be around 37,000 crores in 2007. (RNCOS, 2008)
The market, in the past five years has been posting growth at a rate of 17%. Few of the key features
are:
Increasing at a CAGR of 17%, the womens apparel market has grown to Rs 61,000 crores in2010.
Branded women apparel is growing at 25% and is worth Rs 18,000 crores in 2010.
Premium segment apparel is growing at 20% Western wear, along with lingerie is the fastest growing segment. Organized players are expected to account for around 40% of the premium market.
(RNCOS, 2008)
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Market size estimation:
The domestic market can be segmented into mens wear (RMG for males aged above 15 years),womens wear (RMG for females aged above 15 years) and kids wear (RMG for children aged up to
15 years). The size of each of these segments is estimated to be around Rs 527 billion, Rs 466 billion
and Rs 132 billion, respectively. (2010) (RMG : Ready made garment)
Women's wear segment
The women wear market which is the primary target segment for our app is further classified as
follows
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The market size for branded women apparel = Rs 18000 Crore. Assuming 20% of the clothes
produced are not sold and going waste, potential savings which can be done by perfect trend
forecasting = (18000*0.2)/0.8 = Rs 4500 Crores
The above findings indicate the immense potential is the apparel industry, especially in the premium
segment.
Key Resources needed:
Initial resources needed would be minimal. Collaboration with the several fashion houses for
providing options for the users would be of primary importance. The Platform on which the app
would be launched on would be Android since we require high volumes in sample size. The
promotion and advertising expenses would be borne by the companies themselves.
Key activities after the launch of the app would include regular updates of designs brought by partner
apparel stores. As the entire stock would ideally be revamped every six months, the entire range of
products would have to be replaced by new stock during this time.
Cost Estimation for Developing the app
For the iPhone industry, based on the survey done from 96 developers the average cost of developing
a mobile application was $6,453(Some of the developers omitted development costs).Cost is also
dependent on the size of the development team. For a contracted team, the cost could go up to five to
10 times. The development costs are platform independent (typical rates for developers being $50 per
hour to $100 per hour). (Ahlund, 2010) Factoring in the complexities of integrating the app with
systems like the CRM system, Facebook and Twitter for each cloth retail house and assuming the
development team is of moderate size, the cost for developing a robust mobile app could go up to
$30000(Rs 1,373,400). (Damico, 2010)
Pricing the App
Assuming the app is sold to three different retail chains (Shopper Stop, Pantaloons and Lifestyle), one
third of the fixed cost ofRs 1,373,400 could be transferred to each retail house. Hence cost incurred
per Retail house = Rs 457800
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As on April 2009, retail house Shoppers Stops loyalty program First Citizen had 1.4 million
customers. (Brahma, 2009) Assuming a year on year customer growth rate of 7%, the present number
of loyalty card holders could be 1.602 million customers.
Assuming 50% of these loyalty card holders have Smart phones and use our free application,
Sample size = 1.602*0.5 = 0.801 million.
Assuming each user, on an average indicates 10 preferences in a month using our mobile app, the total
number of preferences indicated = 8.01 million
The revenue for the app developer is predominantly from the back end operations. The retail house
can also generate revenue by featuring in-app advertisements. Since the revenue model is one of fixed
and variable combination with a variable amount charged for preference indicated, by charging Rs 0.2
for every preference indicated, revenue generated in one month = 8.01 million * 0.2 = Rs 1.602
million.
Hence even if we do not charge the retail house with a fixed fee, the app has the potential to break
even with the revenue generated from variable component of the revenue model. By charging a fixed
fee for the app, we are essentially sharing the risk with the retail house. Based on the cost incurred per
retail house, we wish to make 50% of the cost incurred as the upfront fee for the retail houses which
comes out to be 0.5 *457800 = Rs 228900.
Hence we are going to charge the retail houses a fixed price of Rs 228900 and a variable price of Rs
0.2 for every preference indicated.
Hence profit made by the app developer per retail house in one month = 1,602,000 +228900 457800
= Rs 2,015,100
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Bibliography:
Ahlund, A. (2010, May 16). iPhone App Sales, Exposed. Retrieved from http://techcrunch.com:
http://techcrunch.com/2010/05/16/iphone-app-sales-exposed/
Brahma, P. D. (2009). Pantaloon Retail to launch integrated loyalty programme. Retrieved from
http://www.mydigitalfc.com: http://www.mydigitalfc.com/companies/pantaloon-retail-launch-
integrated-loyalty-programme-905
Damico, J. (2010). B2B Mobile Marketing theres an app for that. Retrieved from
http://jdamico.net: http://jdamico.net/2010/05/b2b-mobile-marketing-theres-an-app-for-that.html
Domestic readymade garments industry grew at around 6 per cent CAGR between 2005 and 2009.
(2010, December). Retrieved from https://www.crisilresearch.com:
https://www.crisilresearch.com/CuttingEdge/industry.jspx?enc==?UTF-
8?B?c2VydmljZUlkPTUwNSZ1c2VySWQ9MjEwODEmcmVzZWFyY2g9ZmFsc2U=?=&firstLogin=true
mapsofindia. (2011, June 20). Retrieved September 2, 2011, from mapsofindia:
http://business.mapsofindia.com/top-brands-india/top-apparel-brands-in-india.html
RNCOS. (2008, August). Report Buyer. Retrieved sepetember 2011, from Report Buyer:
http://www.reportbuyer.com/consumer_goods_retail/clothing/women/women_wear_market_fore
cast_2010.html