Submitted By:Gagan Kumar Patra

Gaurav KocherPulkit GoelVijay Behra

Vikas Narwaria

Flow of Presentation

Introduction to Industry Research Objectives Market Scenario Research Methodology Analysis & Interpretation Findings and conclusions Limitations

Introduction to Industry

Very diverse and heterogeneous industry covers a wide variety of products

Indian Clothing industry is of US$ 29.024 billion The industry was growing at 3-4 % during the last

six decades, has now accelerated to an annual growth rate of 9-10 %.

The industry is targeted to grow at the rate of 16 % in value terms to reach the level of US$ 115 billion (exports US$ 55 billion; domestic market US$ 60 billion) by 2012.

Contd…

Major Reasons: Against the backdrop of an ageing world, India

possesses the advantage of having a largely young population. 35 % of India’s population is under 14 years of age and more than 60% of the population is estimated to constitute the working age group (15-60) till 2050.

Two-thirds of Indian population is under 35, with the median age of 23 years, as opposed to the world median age of 33. India is home to 20% of the global population under 25 years of age.

Contd...

Privatization is one of the reasons for increase in market players and thus in variety of products and prices.

Globalization is responsible for introduction of global trends into the market and hence affecting the consumer perception.

Economic growth has resulted in better living standards.

Research Objectives

To study the consumer behavior towards the retail garment industry and compare the higher and middle segments.

Analyzing & Forecasting the demand of the industry in the near future.

Research Methodology Sampling technique: Judgmental, Convenient

& Cluster Sampling. Sampling region: Delhi NCR Survey technique: Questionnaire Method

Data Collection: Primary Data: Consumer and retailer survey

done through filling of questionnaires Secondary Data: Collected from various

sources like Official sites and various business sites.

Analysis & Interpretation

From Consumer Primary Data Primary Data was collected through a

questionnaire having both open and close ended questions.

The sample size was taken as 75. The area covered for the survey was

New Delhi(Sarojini Nagar, Connaught Place , Saket , South Extension, Safdarjung Enclave) . The target consumers were who bought garments or visited the outlets and also general consumers.

Preferred Brand Segment Vs Occupation

Advertisement

Discount Vs Occupation

Age Distribution : 15-25

Age Distribution : 25-35

Age Distribution : 35-45

Age Distribution: 45 & Above

Retailer Primary Data Primary data was collected through a

open ended questionnaire which was filled by the retailers.

Sample size was taken as 15. Stores targeted were in two segments:• Middle Segment

KoutonsCantabil

• Higher SegmentAllen SollyLouis PhilippeVan Heusen

Findings common to both segments

Festival seasons includes the Marriage season, Diwali, Eid Ul Fitr and New year.

Variety and small discounts are the main attractions offered by the stores during these festival seasons.

Winter season is considered best time due to sales of higher margin products.

Previous year sales is treated as the base year to set target sales for the next year.

Findings for higher segment Aug-Sep being the worst season is generally

loaded with high discounts. They also study current market trends

through market research firms and set targets accordingly.

Discounts are subject to the off season, previous year stock and non moving merchandise.

Store training, product display, micro marketing straegies also form study subjects.

Major Brands are:Peter England, Parx, Espirit, Louis Philippe, Van heusen, Allen Solly.

Findings for middle segment Heavy discounts is the leading

technique used to attract all income level customers.

Attaching a brand name to low cost merchandise is the main idea behind this segment.

Retailers demand more advertising from the company.

Major brands are: Koutons, TQS, Priknit, Cantabil, Allen Cooper.

Secondary Data Source

The other secondary data were collected from the various websites.

www.fibre2fashion.comwww.cmlinks.com

http://www.maduragarments.com/www.retailindustry/about.com

Calculation of Price Elasticity

Determination of Price elasticity is required to find the demand behavior of the consumer.

Louis Phillippe:During Festive seasons discount offered

is 20% and consequently demand rises by 30% according to the retailers.

So Elasticity of Demand (Ep) = (P/Q)*(ΔQ/ ΔP) = (30%)/(-20%)

=-1.5So it is found out that the demand is elastic.

Elasticities During Festive Season

Brand Discount(%) % increase in sales Elasticity

Louis Philippe -20 30 -1.50

Van Heusen -40 30 -0.75

Allen Solly -30 20 -0.67

Need For Demand Forecasting

Sales for 2008-09 is of Rs.1046.68 Cr, what about next

year???

Demand Forecasting

Micro forecasting techniques were used in the project such as :• Time series data analysis• Standard deviation

Forecasted time period -2009-2010.Future demand can be forecasted by the following formulaCurrent Company Demand = Current Market Demand x Current Market Share

Contd… Koutons(Sales Figure in Crore INR):

The Standard Deviation = 409.74So the forecasted Sales for 2010 is =1046.68+409.74= 1456.68

Allen Solly(Sales Figure in Crore INR):

The Standard Deviation = 176.51So the forecasted Sales for 2010 is =517+176.51= 693.51

2003 2004 2005 2006 2007 2008 2009

21.25 31.37 57.85 158.34 402.7 783.46 1046.68

2005 2006 2007 2008 2009

111 140 224 411 517

Demand Forecast for KoutonsTime Series Analysis

Standard Deviation Method

Demand forecast for Allen SollyTime Series Analysis

Standard Deviation Method

SuggestionsThese are some suggestions from the

retailers which needs to be implemented.

Evaluate the product mix and pricing strategies in the context of changes in consumer demand.

Use retail sales promotional techniques (bundling of products, membership card, Price discount, quantity discount, etc.) to increase store traffic.

Contd…

Use appropriate Promotion mix to communicate with the customers.

Plan more frequently and aggressively based on most recent results and forecasts.

Understand the spending behaviour of target market and develop your planning.

Optimize the risk with respect to sales plans and profit.

SWOT ANALYSIS

Limitation

Could only surveyed few areas in New Delhi in the short span of time, so demand may vary in other places.

Retailers were unable to tell technical methods used for demand forecasting.

Data given by the consumers were considered to be perfect.

Any quantitative data was not provided by retailers.

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