Research Report on Kazo by Sakshi Gupta

Pearl Academy, New Delhi Fashion Marketing and Retail Management (FMRM) (2014-2018)

Research Methods 2 “To study the effect of promotional strategies of Kazo on consumers”

Submitted toMrs. Vasundhra Gupta/ Mrs. Usha Aggarwal Faculty of Pearl Academy

Submitted ByNikita Singhal, Harshita Chutani and Sakshi Gupta Date of Submission- 5th may,2015

Table of Contents 1. Executive Summary 2. Background Study 2.1 Origin 2.2 Working of Kazo in India 2.3 Marketing Mix 2.3.1. Price 2.3.2 Place 2.3.3 Product 2.3.4 Promotions 2.4. SWOT analysis 2.4.1. Strengths 2.4.2 Weakness 2.4.3 Opportunities 2.4.4. Threats 2.5 Competitor Analysis 2.6 Primary Study 2.7 Problem Statement 2.7.1 Research problem 3. Literature Review 3.1 Understanding the term â&#x20AC;&#x2DC;brandâ&#x20AC;&#x2122; 3.2 Consumer Market 3.2.1 Consumer 3.2.2 Consumer Behaviour 3.2.3 Consumer Behaviour towards Apparel Brands 3.3 Marketing Strategies 3.3.1 Understanding your clients

3.3.2 Developing Finanical Goals 3.3.3 Strategic Planning 3. 4. Promotion Mix 3.4.1 Advertising 3.4.2 Sales Promotion 3.4.3 Personal Selling: 3.4.4 Public Relations 3.5 Techniques of Promotional Strategies 3.6 Advertising and its Effects 3.6.1 Advertising and Brand Awareness 3.6.2 Advertising and Consumer Behaviour 3.6.3 How does Advertising affect consumers? 3.7 Knowledge Gap 4. Research Methodology 4.1 Research Objective 4.2 Research Design 4.3 Data collection method 4.4 Data Collection Tool 4.5 Sample Design 4.5.1 Sampling Frame 4.5.2 Sampling Unit 4.5.3 Sample Size 4.5.4 Method of sampling 4.5.5 Sample 4.6 Data Analysis Tools 5. Data Analysis and Findings 6. Conclusion 7. Recommendation 8. Referencing 9. Bibliography

10. Annexure

Executive summary Kazo is a fashion retailer that came into being with a simple aim of amalgamating creative international trends and fashion at a value that would suit the requirements of todayâ&#x20AC;&#x2122;s youth. Due to the high wear-ability and high street fashion trends, Kazo has been able to make an enviable reputation for itself in a short span of time. The research report has been done keeping in mind the Indian operation of Kazo Ltd. This report provides an analysis of the brand perception of KAZO customers. It

suggests hosts of marketing strategies and promotional activities that help a brand to grow. The observation includes the analysis on Customer loyalty program, quantity and quality of collection, the display of designs and various other details. The report finds the prospects of the company in its current position are not positive. According to the primary and secondary study conducted, there are two major problems faced by Kazo. The first problem is that Kazo is not able to connect with its consumers. The second problem encountered was that Kazo has no promotion strategy. The major areas of weakness require further investigation and remedial action by management. Recommendations discussed include: â&#x20AC;˘

Frequent addition of new designs and information about it through sales staff, online blogs or SMSs should motivate customers to come back to stores more frequently.

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KAZO needs to invest on several ATL for branding & BTL activities to target its potential customers.

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A few of the customers specially mentioned the need for frequent change of design on mannequin as that gives an idea of the collection inside.

Chapter 2: Background Study

2.1 Origin Giving every woman a chance to live their life confidently and to feel great about them, Kazo launched its first store On July 7 th, 2007. Kazo is an in-house brand of B.L. International. It came into being with a simple aim of amalgamating creative international trends and fashion at a value that would suit the requirements of todayâ&#x20AC;&#x2122;s youth. Due to the high wear-ability and high street fashion trends, Kazo has been able to make an enviable reputation for itself in a short span of time.

Kazo has huge design studios in Milan, Spain, Paris and London and New Delhi. The designers of Kazo follow the fashion trends of the runway of Milan, Paris and London which are the genesis of fashion hub.

2.2 Working of Kazo in India KAZO is committed to deliver your order with good quality packaging within given time frame. We ship throughout the week, except weekends and Public holidays. To ensure that your order reaches you in good condition, in the shortest span of time, we ship through reputed courier agencies only. At this time there are few locations where our logistic partners don’t have reach and therefore, we may not be able to service your order. •

How are the delivery charges calculated?

They charge a flat shipping charge of Rs 100 for all orders below Rs 2,000. Orders above Rs 2,000 are shipped free of cost. •

How long does it take for an order to arrive?

Orders received till 9:00am will be dispatched on the same day. Orders received after 9.00am or on non-working days will be dispatched on the next working day. Most orders are delivered within 3 to 7 working days depending on the location of delivery. Delivery will be done only at the address as mentioned by you at the time of placing the order. •

What if the product received is in damaged condition?

If a person thinks, they have received the product in a bad condition or if the packaging is tampered with or damaged before delivery, they should refuse to accept the package and return the package to the delivery person. The customer should call the customer care number or email them mentioning the Order ID. The responsible authorities will personally ensure that the issue is satisfactorily resolved. He conceptualized sales and marketing plans to redefine trends in fashion. Motivated by this vision coupled with his zeal for work, Mr. Aggarwal through the KAZO has rendered high quality service, resulting in brand loyalty. His determination inspires the team to position his businesses as the pioneer in high fashion industry. By combining skillful management, innovative and modern technology, Mr. Aggarwal inspires the team to achieve new milestones and improve performance graphs. Mr. Aggarwal’s belief in professionalism has led him to build a core team of experts from in all aspects of brand retail. The team has been carefully selected to carry forward his ambitious vision. With the growing popularity of the brand and its aggressive expansion, Mr. Aggarwal continually motivates his team to set new performance benchmarks and be proactively involved in all activities pertaining to the

growth of the company. His leadership and management skills are iconic and will continue.

2.3 Marketing Mix(Price, Product, Promotion & Place) 2.3.1 PriceKazo is a young international brand that has made its way into the centre of the fashion industry within a short span of time. The idea of Kazo came into being with the aim of amalgamating international trends and fashion at a value that is affordable for the women of today. The main asset of the collections is that it is highly affordable which enables customers an access to the latest designer wear, giving a chance to every women to feel great in her skin, right to her soul. The prices it offers for its fine quality product are neither too high nor too low and are pretty well accepted by the customers. The price range for Kazo’s product range is given belowProduct Range

Price Range

Kazo Trendy

Rs. 1000-Rs.3000

Kazo Evening

Rs.2500-Rs. 5000

Kazo Limited

Rs.4000-Rs. 6000

Kazo Basic

Rs.600-Rs.2700

Kazo Men

Rs.1000-Rs. 4000

2.3.2 RETAIL PRESENCE – Place EBOs  Delhi/NCR – 6 showrooms •

Westgate Mall, Raja Garden

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Select City Walk Mall, Saket

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Ambiance Mall, Gurgaon

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Great India Place, Noida

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Greater Kailash – I

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DT Mall, Gurgaon

 Mumbai – 4 showrooms •

Juhu Tara Road,

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Juhu Mega Mall,

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Inorbit Mall, Vashi

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Oberoi Mall

 Punjab – 2 showrooms •

Ludhiana

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Amritsar

 Bangalore – 1 showroom  Hyderabad – 1 showroom

SISs  Ritu Wears •

Rohini

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Lajpat Ngr

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Jallandhar

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Amritsar

 Forum Bangalore  Central Bangalore 

India Bulls - Pune

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Ebony •

Amritsar

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Chandigarh

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Faridabad

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Ludhiana

2.3.3 Product Range-

KAZO Trendy, KAZO Evening, KAZO Basic, KAZO Men and KAZO Limited are the ranges of KAZO that are from chic and youthful to glamorous and glitzy to please not only naughty teens, professionals and the coveted diva but also men. •

KAZO TRENDY

The name speaks for itself- this range is chic, youthful with a dash of vulnerability. Specially designed to ring out sheer fun element in the lives of young girls between 15- 25. Attires under this collection are a toast to vivacity of a woman who constantly alters her wardrobe and thrives on variety.

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KAZO EVENING

For that special evening, with glitz and glamour, KAZO has its designer evening wardrobe that will give you a complete look of the diva. Those entire women between 15 and 35, finds it one stop for that impeccable fit and ethereal design. Whether it’s a party, an evening with friends or a date with your beloved, KAZO’s designer wear will prepare you to walk the face of the earth with poise.

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KAZO LIMITED

Very limited, specially designed, oodles of attitude, charm, poise and style that’ll take the breath away are the bona fide characteristics of a KAZO limited collection. From 20-35, the collections under KAZO accommodate one and all enabling every woman to mesmerize the world. If parties are your haunt and distinctiveness your covet then KAZO is your ultimate stop.

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KAZO BASIC

Office wear was never so trendy before the launch of KAZO that has created a unique collection of the women of today who aims at leaving a mark wherever she goes. Office wardrobes from KAZO is a must have if style and profession goes hand in hand for you.

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KAZO MAN

The Autumn/Winter collection of 2009 saw another addition to the existing range of KAZO. It was the time when KAZO entered the men’s collection. Trendy, stylish, casual and colorful are some of the attributes in the collection. Though it’s only available at select stores right now, KAZO plans to increase the man’s collection to its entire store.

2.3.4 Promotions Kazo Fashion maintains a huge potential exists in social networking websites and that the company has taken to it very seriously. Kazo hosts a lot of campaigns online to attract customers, and has a presence on Twitter and Facebook by conducting on ground activities with the help of social media. Given the huge interest on social media, the company is looking to launch Kazo stores in Italy, France and England soon. The company, which is concentrating on social media and digital marketing to achieve growth, regularly updates its promotions and marketing features on its Facebook page.

2.4 SWOT analysis 2.4.1 Strength •

Lesser price as compared to competitors

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Stores at main locations in the mall

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Very high degree of customer loyalty

2.4.2 Weakness •

Low level of brand awareness

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Non availability of sizes

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Limited variants in color

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No incentive for repeat purchase

2.4.3 Opportunities •

Increase in demand of brands in middle east

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Increase in disposable income of people

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People are becoming brand conscious

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Growing domestic market

2.4.4 Threats •

Predominance of unorganized sector

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Increased competition

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Cheaper imports

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Change in government policy of FD

2.5 Competitors Mango, Zara, Sisley is the major competitors. Kazo use to supply to these brands before opening up its retail store. The price range is a weakness for Mango in the Indian market when compared with its competitors like Kazo, Promod, Zara. The French fashion brand Promod has cut costs but Zara and Kazo are comparatively lower priced than Mango.

ZARA

KAZO

MANGO

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It provides apparels at/with minimum starting range of Rs. 1000

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It provides apparels at/with minimum starting range of Rs. 1200

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It provides apparels with a minimum starting range of Rs. 1500

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Zara’s average sales are around Rs. 50,000

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Kazo’s average sales are about Rs.

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It brings in new products every fortnight

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It brings in new products

Mango’s average sales are around Rs. 40,000.

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Good range of designs and styles

It brings in new products

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Wide range

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Has good awareness of the brand

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Much wider range of styles Generates more footfalls Has good awareness of the brand

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Generates lower footfall

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Has lower awareness of the brand

2.6. Primary Study

A brand visit was also conducted where in the promotional strategies of the brand were studied. The field study was conducted in Pacific mall and Selectcity walk, New Delhi. It was noticed that Kazo had very few retail promotions. We also used observation method. It was noticed that most of the customers came just to have a

look at Kazoâ&#x20AC;&#x2122;s products. The primary Study was also conducted with the help of Unstructured and structured data collection tools i.e. Interviews and Questionnaires respectively.

2.7 Problem Statement According to the primary and secondary study conducted, there are two major problems faced by Kazo. The first problem is that Kazo is not able to connect with its consumers. The second problem encountered was that Kazo has no promotion strategy. 2.7.1. Research Problem The main problem being encountered by Kazo is that it is not able to connect with its customers as it has unsatisfactory promotion strategy.

Chapter 3: Literature Review

Consumers are evolving entities. Their aspirations and expectations are continuously changing. Today’s shoppers are more intelligent, discerning and tuned to their individual preference. They are increasingly brand and fashion conscious and select labels which define who they are or who they want to be. The biggest challenge for all the brands is to create loyal customers who love them. With rapid growth in disposable incomes Indian consumer markets are changing fast. And therefore Apparel and fashion industry in India is in its growth stage. In such a scenario, it is very essential to study how consumers make their choices in Apparel & Fashion category where there are several brands in the consideration set of a consumer. Brands build customer loyalty by delivering excellent value which includes styling, durability, quality fabrics, and consistent fit. To the consumer, a brand name represents familiarity, consistency, and confidence in performance.

3.1 Understanding the term ‘Brand’ A brand is a product, service, or concept that is publicly distinguished from other products, services, or concepts so that it can be easily communicated and usually marketed. A brand name is the name of the distinctive product, service, or concept. Branding is the process of creating and disseminating the brand name. Branding can be applied to the entire corporate identity as well as to individual product and service names. A company's brands and the public's awareness of them is often used as a factor in evaluating a company. A brand connects the four crucial elements of an enterprise- customers, employees, management and shareholders. Brand is nothing but an assortment of memories in customers mind. Brand represents values, ideas and even personality. It is a set of functional, emotional and rational associations and benefits which have occupied target market’s mind. Some examples of well known brands are Mc Donald’s’, Mercedes-Benz, Sony, Coca Cola, Kingfisher, etc. (Lee, 2015). Fashion must have value and purpose and should truly resonate in the industry. Strong brands with consistent powerful messages can create loyalty and a sense of worth that transcends the burden of choice. It also nourishes industries with high research requirements due to its present characteristics: •

Fast mutation of its specificities

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Obsolescence of the product

The understanding of consumerâ&#x20AC;&#x2122;s desires, behaviour, and of purchase process of fashion products is extremely important to design products collections as well as to placement of these products in market.

3.2 Consumer Market 3.2.1 about the Consumer Consumer is an individual who buys products or services for personal use and not for manufacture or resale. A consumer is someone who can make the decision whether or not to purchase an item at the store, and someone who can be influenced by marketing and advertisements. Any time someone goes to a store and purchases a toy, shirt, beverage, or anything else, they are making that decision as a consumer. (Mawen, 2001) Consumers play a vital role in the economic system of a nation. Without consumer demand, producers would lack one of the key motivations to produce: to sell to consumers. The consumer also forms part of the chain of distribution. For example: Atul might purchase a cap for his son or Sonam might buy a skirt for herself. In the above examples, both Atul and Sonam are consumers. (Naureman, 2006) 3.2.2 Consumer behaviour Consumer behaviour is the study of how individual customers, groups or organizations select, buy, use, and dispose ideas, goods, and services to satisfy their needs and wants. It refers to the actions of the consumers in the marketplace and the underlying motives for those actions. Marketers expect that by understanding what causes the consumers to buy particular goods and services, they will be able to determineâ&#x20AC;&#x201D;which products are needed in the marketplace, which are obsolete, and how best to present the goods to the consumers. (Ehrenberg, 2005) The study of consumer behaviour assumes that the consumers are actors in the marketplace. The perspective of role theory assumes that consumers play various roles in the marketplace. Starting from the information provider, from the user to the payer and to the disposer, consumers play these roles in the decision process. The roles also vary in different consumption situations; for example, a mother plays the role of an influence in a childâ&#x20AC;&#x2122;s purchase process, whereas she plays the role of a disposer for the products consumed by the family.( Naureman, 2015) 3.2.3 Consumer behaviour towards Apparel Brands The Indian customer has undergone a remarkable transformation. Just a decade or two ago, the Indian customer saved most of his income, purchased the bare

necessities and rarely indulged himself. Today, armed with a higher income, credit cards, exposure to the shopping culture of the west and a desire to improve his standard of living, the Indian consumer is spending like never before. Organized retail with its variety of products and multitude of malls and supermarkets is fuelling their addiction. Most customers’ preferences change according to the change in fashion.(Sundarraj, 2015). A key challenge for apparel retailer in India is to induce customer to purchase quickly, which means sales promotion tactics are important, including end of season sales, festival promotion and special events. There is an increasing shift from price consideration to design and quality, as there is a greater focus on looking and feeling good (apparel as well as fitness). At the same time, the new Indian consumer is not beguiled by retailed products which are high on price but commensurately low on value or functionality. There is an easier acceptance of luxury and an increased willingness to experiment with mainstream fashion. This results in an increased tendency towards disposability and casting out -from apparel to cars to mobile phones to consumer durables. The self-employed segment of the population has replaced the employed salaried segment as the mainstream market. 40% of primary wage earners in the top 2-3 social classes in towns with a population of 1 million or more are self employed professionals and businessmen. This has driven growth in consumption of productivity goods, especially mobile phones and two and four-wheelers. Finally, credit friendliness, drop in interest rates and easy availability of finance have changed mindsets. Capital expenditure (jewellery, homes, cars) has shifted to becoming redefined as consumer revenue expenditure, in addition to consumer durables and loan credit purchases. Some of the interpretations of what a consumer preference is, are given below Elling (1984) explained consumer preference as that ―character of a consumer which, when the product preferred by him was not available with one dealer, made him to walk to other dealer for the same product‖. The way consumer is fulfilled or unhappy about a product after his purchase is called as customer’s preference. Once the customer likes the product there are more chances of purchasing it again. Domestic brands have also stepped into the market with different variety of products according to the region and culture. Brands are expanding their presence from urban market to rural market to reach the consumers. In the past consumers were not provided with comprehensive list of products and so there were no special preferences. In today‘s context, there is wide range of variety and brands for the consumer to choose and hence the preferences of consumer have a wider importance. It was seller’s market during 1990s and now its buyer’s market. (Oliver, 1999).

3.3 Marketing Strategies Promotional and marketing strategies are often first brainstormed and written as part of an organization's marketing plan. If your small business doesn't have a marketing plan, you should seriously consider developing one. Most marketing plans include the current or expected strategies you have for your products, the price points of those products, how you intend to distribute the products, and your advertising and marketing tools. A marketing plan is also important for developing a promotional strategy as it helps your business identify its target markets and to set measurable goals. It is vital to the success of the organization that you implement a marketing plan that aims for growth and positive change in the bottom line. 3.3.1 Understanding your clientsPromotional and marketing strategies can also assist your business in understanding and connecting with clients and customers. If your marketing plan is loosely structured, you might not have much success at targeting products to the "right" demographics. Having a solid and well-thought-out marketing plan can help you identify gaps in the marketplace and provide feasible solutions for your clients. If you operate an ice cream business in a neighbourhood where no other ice cream shops exist, it might be easier to attract clients than in a town where there are other ice cream options. In this case, understanding that your clients want sprinkles and waffle cones might help you sell more ice cream and keep your customers coming back for more. 3.3.2 Developing financial goalsPromotional and marketing strategies are also important for guiding your business into the development of financial goals. Financial goals are two-fold: They are related to your sales targets and also to your expenses budget. Sales targets are initially set as part of the marketing plan but might change over time according to changing market conditions, increases in product price, or increases or decreases in consumer demand. Monitoring expenses is also part of financial goal development. If your business tends to spend more than it brings in, you'll have a serious problem maintaining long-term business viability. However, if the business is able to closely monitor its outflows, only spending what it absolutely needs to, you'll be better equipped to increase the profit margins. 3.3.3 Strategic planningAnother important aspect of promotional and marketing strategies involves strategic planning. Strategic planning is a concept that encompasses marketing, promotion, sales, and financial goals and is essentially about developing goals for your business. Having a strategic plan for your business means that there is are plans in place to deal with both expected and unexpected situations. If you know that your mortgage will balloon by 5 percent next year, a strategic plan will outline how you'll

increase sales or decrease expenses to meet this additional outflow. A strategic plan might also include solutions to "what-if" scenarios. This means having a plan B for months when profits are down or expenses are unusually high. Sales and promotional strategies are important here because they allow you to ramp up marketing and to increase the bottom line without sacrificing efficiencies or service. (Naureman,2015)

3.4 Promotion Mix:

It refers to all the decisions related to promotion of sales of products and services. The important decisions of promotion mix are selecting advertising media, selecting promotional techniques, using publicity measures and public relations etc.(Kotler, 2003) There are various tools and elements available for promotion. These are adopted by firms to carry on its promotional activities. The marketer generally chooses a combination of these promotional tools. Following are the tools or elements of promotion. They are also called elements of promotion mix: 3.4.1 Advertising: Advertisement can be defined as the â&#x20AC;&#x153;paid form of non-personal presentation and promotion of idea, goods or services by an identified sponsorâ&#x20AC;?. It is an impersonal presentation where a standard or common message regarding the merits, price and availability of product or service is given by the producer or marketer. The advertisement builds pull effect as advertising tries to pull the product by directly appealing to customer to buy it. 3.4.2 Sales Promotion: Sales promotion refers to short term use of incentives or other promotional activities that stimulate the customer to buy the product. Sales promotion techniques are very useful because they bring: (a) Short and immediate effect on sale. (b) Stock clearance is possible with sales promotion. (c) Sales promotion techniques induce customers as well as distribution channels. (d) Sales promotion techniques help to win over the competitor. 3.4.3 Personal Selling:

Personal selling means selling personally. This involves face to face interaction between seller and buyer for the purpose of sale. The personal selling does not mean getting the prospects to desire what seller wants but the concept of personal selling is also based on customer satisfaction. 3.4.4 Public Relations: Apart from four major elements of marketing mix, another important tool of marketing is maintaining Public Relations. In simple words, public relations means maintaining public relations with public. By maintaining public relations, companies create goodwill. Public relations evaluate public attitudes; identify the policies and procedures of an organisation with the public interest to earn public understanding and acceptance. Public does not mean only customers, but it includes shareholders, suppliers, intermediaries, customers etc. The firmâ&#x20AC;&#x2122;s success and achievement depends upon the support of these parties for example, firm needs active support of middle men to survive in market, it must have good relations with existing shareholders who provide capital. The consumersâ&#x20AC;&#x2122; group is the most important part of public as success of business depends upon the support and demand of customers only.

3.5 Techniques of Promotional Strategies

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Independent and small retail stores go through periods when daily sales receipts are down. To increase sales, attract new customers, and retain current customers, many retail stores implement various sales promotion techniques. While most business owners would love to sell products at full price all of the time, sales promotions have proven effective at increasing the overall bottom line in many retail stores.

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An effective technique to increasing sales is to offer certain products at a steep discount, which are called loss leaders. The importance of loss leaders is the ability to draw new customers into your store. Most customers not only buy products that are steeply discounted, but also other products that are selling for regular price. Loss leaders are effective for selling overstocked items, increasing traffic into your store and building brand awareness.

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Another sales promotion technique is to offer point-of-purchase items. These items are placed on the counter near the cash register. Many retail stores place items, such as jewelry and makeup, near the register. Customers often buy point-of-purchase items on an impulse. Many retail owners believe that point-of-sale products result in an increase in revenue.

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Repeat customers are essential to the success of a retail business. One method to encourage customers to return is through reward programs made available to loyal customers. A more recent phenomenon is offering coupons to customers who ‘Like’ the store’s Facebook page. This not only leads to customers coming to your store to use the coupon, but also allows you to send messages to your customers through Facebook to keep them informed on new items & sales. Another option is to send a coupon or sale notification to all of its past customers that are on the store’s email list. The incentives work well to build loyalty and repeat sales because customers have a previous history of shopping at the store are likely shop there again.

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Offering free samples is a promotion method retail stores use to entice reluctant shoppers to make purchases. A free item offered in a promotion should be a low-cost, high-value item. A sample of a new perfume may be a good product to give away for some retail stores. It is important to strategically plan a free sample promotion. Some customers will purchase other items, while others will take the free sample and leave. If not executed in the proper manner, a free sample promotion campaign can cause your store to lose money.(Lange, 2005)

3.6 Advertising and its effect

3.6.1 Advertising and Brand Awareness Now it is very well known that since Brands are coming in by dozens, all one needs is the confidence to deliver, to just make it happen- by none other than advertising which forms a vast superstructure with an autonomous existence and an immense influence. Today there is general agreement that advertising objectives can be set around four broad themes:•

The behavioral constructs generating trial purchases and store visit.

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Change in attitude and its measurement

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Positioning of the product and brand building.

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Creating awareness of new products and brands.

Advertising is one of the most important cultural sign systems that reflect and mould our lives. It is an inevitable part of anyone’s life. Even if one does not read the newspaper or watches television it is impossible to escape the advertising images that pervade our surroundings, via hoardings, wall paintings, pop material or even the radio, cutting across all media but limited to none. It is true that Brand Awareness is one of the prime objectives of Advertising in the modern world. Advertising is the communication link between the seller and the buyer. It does not simply provide information about the products and services but is an active attempt to influencing people to action byan over appeal to reason or emotion. In other words, advertising does not end with the flow of information from the seller to the buyer; it goes further to influence and persuades people to action or belief. Advertising, being an integral part of promotion mix, is a part of the total marketing mix and it influences the sale of the products as do the other variables of the mix. Together with the product or brand, price, channel or distribution outlet and personal selling it attempts to achieve the marketing objectives. (Til, 2005) 3.6.2 Advertising and Consumer Behaviour:Relationship consumer behaviour is influenced by various factors, ranging from personal motivation, needs attitude and values, personality characteristics, socioeconomic and cultural background, age, sex, professional status to social influence of various kinds exerted by family, friend’s colleagues and society as a whole. Each person has hi /her own standards of judgments and distinct behaviour in every aspects of his/her role as a consumer. But, at the same time, underlying the individual differences there are similarities which make it possible to explain behaviour of specific types or groups of people. A careful study of consumer behaviour provides the advertiser with deeper insight of his target segments, which in turn proves to be very valuable in strategic advertising decisions, especially in

defining the target markets and creating the advertising appeal and message. (Naureman, 2015) 3.6.3 How does Advertising affect consumers? Advertising, along with a number of other factors like price, distribution, sales force, packaging, product features, competitive actions and changing buyer needs and tasters influence sales isolating the effects of advertising is extremely difficult. Advertising might attract buyers who will be loyal customers for many years to come or might start the development of positive attitudes or brand equity that will culminate in purchase much later. Advertising influences consumer and his decision making in a number of ways. It not only educated him about his problems or needs, provides required information and assists him in comparing the various alternatives and arriving at final decision. As it is a cyclical process, it also has impact over the post purchase behavior of the consumer. Often, the consumers are either not aware of their needs or are confused about their problems. To them, advertising provides clues; therefore advertising provides the consumer motives to purchase the advertised product. (Lange, 2005) As in the present scenario the strategy is to keep on changing or improving the product. As in the present scenario the strategy is to keep on changing or improving the product or its features, it becomes imperative top inform the consumers about the minor innovations and the way it can solve their problems – the problems which the consumers feel and is at the surface or the problems which had not captured the attention of the consumers. Advertising also provides the necessary support after the consumer has made the purchase. If the consumers experience dissonance or discomforts Moving to their purchase decision, then advertisement reduce this feeling of discomfort by providing information on the products attributes. It is even more necessary to neutralize the impact of the advertisements of rival brands. Keeping the above facts in view an attempt has been made to find out whether advertising has an impact on brand awareness and preference on men’s garment in the study area of Navi Mumbai, has also experienced the sift in men’s shopping pattern and methodology used as the city wittiness significant economic, demographic, social cultural development. People of this city are customizing themselves to the fashion revolution and men are a major contributing factor and greatly affected by the same as well. New avenues are reshaping and redirecting the general marketing/shopping culture prevalent. Navi Mumbai is the world's largest planned city.

3.7 Knowledge Gap Promotion is a very important aspect to maintain a brand’s position in the marketing sector. It helps the brand to connect with people. Without business promotion companies will have no substantial growth and low visibility in the market. This is what lacks in Kazo. This affects their sales as it fails to connect with people.

4. Research Methodology 4.1 Research Objective To analyze the effect of promotional strategies of Kazo on the consumers.

4.2 Research Design The design of the research conducted is Causal in nature since the study includes cause and effect relationship between Consumer behaviour and promotion strategy of Kazo. Causal research Design finds the relationship between two variables. As the effect of promotion strategy on customers is being analyzed, the research objective itself shows that it is Causal Research design.

4.3 Data collection method The data has been collected with the help of Primary and Secondary Data to execute the result.

4.4 Data Collection Tool The data has been collected with the help of following data sources-

Primary Data Sources- Interviews, Questionnaires Secondary Data Sources- E-books, Websites, Journals 4.5 Sample Design 4.5.1 Sampling Frame The research is conducted on Fashion Conscious Women as the research is based on a fashion brand.

4.5.2 Sampling Unit The research is conducted on Fashion Conscious Women in Delhi as Delhi is the most accessible area.

4.5.3 Sample Size The data has been collected from 100 respondents.

4.5.4 Method of sampling

The research is conducted through judgmental non probability sample because respondents have been handpicked from the population based on their awareness about the brand Kazo.

4.5.5 Sample The research is conducted on Women in Delhi falling under the age group of 18 to 30 years of age.

4.6 Data Analysis Tools The data has been analyzed with the help of statistical tools like Annova and chi square. The data analysis has been performed with the help of the softwareStatistical Package for Social Sciences (SPSS).

5. Data Analysis and Findings 5.1 Gender of the respondents Vs the brand aspects:(Annova test applied) It was interpreted that1. Most of the females prefer the fabric of Kazo products more. 2. Most of the females prefer for the designs of Kazo more. 3. Most of the females prefer for the variety of Kazo products more. 4. Most of the females prefer for the display of Kazo products more. 5. Most of the females are satisfied with the prices that Kazo offers. 6. Most of the males prefer for the music played in Kazo stores. 7. Most of the females are satisfied with the staff etiquettes. 8. Most of the females are satisfied with the visual merchandising of the brand Kazo. Since the results for all the above observations were more than 0.05, the hypothesis is rejected. This might be because most of the respondents were not true while filling up the questionnaires.

5.2. Age of the respondents Vs the Brand aspects:It was interpreted that1. Most of the respondents falling in the age group of 18-21 years prefer the fabric of Kazo products more. 2. Most of the respondents falling in the age group of 26-29 years prefer the designs of Kazo products more. 3. Most of the respondents falling in the age group of 26-29 years prefer the variety of Kazo products more. 4. Most of the respondents falling in the age group of 22-25 years prefer the display of Kazo products more. 5. Most of the respondents falling in the age group of 26-29 years are satisfied with the prices that Kazo offers. 6. Most of the respondents falling in the age group of 18-21 years prefer the music played in Kazo stores. 7. Most of the respondents falling in the age group of 22-25 years are satisfied with the staff etiquettes in Kazo stores. 8. Most of the respondents falling in the age group of 26-29 years are satisfied with the visual merchandising of the brand. Since the results for all the above observations were more than 0.05, the hypothesis is rejected. This might be because most of the respondents were not true while filling up the questionnaires.

5.3. Marital status Vs the brand aspects:It was interpreted that1. Most of the respondents who are single prefer the fabric of Kazo products more. 2. Most of the respondents who are neither single nor married (hence others) prefer the designs of Kazo products more.

3. Most of the respondents who are married are satisfied with the variety that Kazo provides. 4. Most of the respondents who are single prefer the display of Kazo products. 5. Most of the respondents who are married prefer the prices offered by Kazo. 6. Most of the respondents who are single prefer the music played in Kazo stores. 7. Most of the respondents who are neither single nor married (hence others) prefer the staff etiquettes of Kazo. 8. Most of the respondents who are single prefer the visual merchandising of Kazo stores. Since the results for all the above observations were more than 0.05, the hypothesis is rejected. This might be because most of the respondents were not true while filling up the questionnaires.

5.4. Education level of the respondents Vs brand aspects:It was interpreted that1. Most of the respondents who are graduates prefer the fabric of the brand Kazo more. 2. Most of the respondents who are graduates prefer the designs of the brand Kazo more. 3. Most of the respondents who have â&#x20AC;&#x153;othersâ&#x20AC;? as their education level prefer the variety that Kazo provides more. 4. Most of the respondents who are graduates prefer the display of Kazo products more. Since the result for this observation was less than 0.05, it is accepted.

5. Most of the respondents who are graduates are satisfied with the prices offered by the brand Kazo. 6. Most of the respondents who are undergraduates prefer the music played in the stores of Kazo. 7. Most of the respondents who have “others” as their education level are satisfied with the staff etiquettes that Kazo provides. 8. Most of the respondents who have “others” as their education level are satisfied with the visual merchandising that Kazo has. Since the results for all the above observations were more than 0.05, the hypothesis is rejected.(except for No.4) This might be because most of the respondents were not true while filling up the questionnaires.

5.5. Occupation of the respondents Vs the Brand aspects:It was interpreted that1. Most of the respondents who fall in the category “others” prefer the fabric of Kazo products more. 2. Most of the respondents who fall in the category “others” prefer the designs of Kazo products more 3. Most of the respondents who were businessmen, designers and self employed prefer the variety that the brand provides. 4. Most of the respondents who fall in the category “others” prefer the display of Kazo products more. 5. Most of the respondents who fall in the category “others” prefer the price of Kazo products more. 6. Most of the respondents who fall in the category “others” prefer the music played in Kazo stores. 7. Most of the respondents who fall in the category “others” prefer the staff

Etiquettes in Kazo stores. 8. Most of the respondents who fall in the category â&#x20AC;&#x153;othersâ&#x20AC;? prefer the visual merchandising of Kazo stores. Since the results for all the above observations were more than 0.05, the hypothesis is rejected. This might be because most of the respondents were not true while filling up the questionnaires.

5.6. Income of the respondents Vs the brand aspects:It was interpreted that:1. Most of the respondents who have monthly disposable income of Rs.25000-35000 prefer the fabric of Kazp products more. 2. Most of the respondents who have monthly disposable income of Rs 5000 or below and who have a monthly disposable income of Rs.35000-45000 prefer the designs of Kazo products more. 3. Most of the respondents who have monthly disposable income of Rs.5000 or below prefer the variety that Kazo provides. 4. Most of the respondents who have monthly disposable income of Rs.35000-45000 prefer the display of Kazo products more. 5. Most of the respondents who have monthly disposable income of Rs.35000-45000 are satisfied with the prices that Kazo offers. 6. Most of the respondents who have monthly disposable income of Rs.35000-45000 prefer the music played in Kazo stores. 7. Most of the respondents who have monthly disposable income of Rs.5000 or below are satisfied with the staff etiquettes in Kazo stores. 8. Most of the respondents who have monthly disposable income of Rs.5000 or below are satisfied with the visual merchandising of Kazo stores. Since the results for all the above observations were more than 0.05, the hypothesis is rejected.

This might be because most of the respondents were not true while filling up the questionnaires CROSSTABS (Chi Square test applied) [Within the promotional activity Kazo should implement]

5.7. Gender of the respondents Vs Promotional activity Kazo should implement. It was interpreted that According to most of the male respondents, Point based Purchase-Discounts is a better promotional activity that Kazo should implement.  WHILE, according to most of the female respondents, Exclusive membershipFashion shows/Club nights/Kazo nights is a better promotional activity that Kazo should implement. The above analysis is rejected. This might be because most of the Respondents were not true while filling up the questionnaires.

5.8. Age of the respondents Vs Promotional activity Kazo should implement It was interpreted that According to most of the respondents who fall in the age group of 18-21 years, Exclusive membership-Fashion shows/Club nights/Kazo nights is a better promotional activity that Kazo should implement.  According to most of the respondents who fall in the age group of 22-25 years, Point based purchase-discounts is a better promotional activity that Kazo should implement.  According to most of the respondents who fall in the age group of 26-29 years, Exclusive membership-Fashion shows/Club nights/Kazo nights is a better promotional activity that Kazo should implement.  According to most of the respondents who fall in the age group 30 years and above, Newsletter- Fashion updates/store updates/fashion tips is a better promotional activity that Kazo should implement.

The above analysis is rejected. This might be because most of the respondents were not true while filling up the questionnaires.

5.9. Marital status of the respondents Vs Promotional activity Kazo should implement It was interpreted that According to most of the respondents who are single, Point based purchasediscounts is a better promotional activity that Kazo should implement.  According to most of the respondents who are married, Exclusive membershipFashion shows/Club nights/Kazo nights is a better promotional activity that Kazo should implement.  According to most of the respondents who have opt “others” as their marital status, Newsletter- Fashion updates/store updates/fashion tips is a better promotional activity that Kazo should implement The above analysis is rejected. This might be because most of the respondents were not true while filling up the questionnaires.

5.10. Education level of the respondents Vs Promotional activity that Kazo should implement It was interpreted that According to most of the respondents who are Undergraduates, Exclusive membership-Fashion shows/Club nights/Kazo nights is a better promotional activity that Kazo should implement.  According to most of the respondents who are Postgraduates, Newsletter- Fashion updates/store updates/fashion tips is a better promotional activity that Kazo should implement  According to most of the respondents who are Graduates, Newsletter- Fashion updates/store updates/fashion tips is a better promotional activity that Kazo should implement. The above analysis is rejected. This might be because most of the respondents were not true while filling up the questionnaires.

5.11. Profession of the respondents Vs Promotional activity that Kazo should implement It was interpreted that According to most of the respondents who are Businessmen, Newsletter- Fashion updates/store updates/fashion tips is a better promotional activity that Kazo should implement.  According to most of the respondents who are students, Point based purchasediscounts is a better promotional activity that Kazo should implement.

 According to most of the respondents who are Designers, Exclusive membershipFashion shows/Club nights/Kazo nights is a better promotional activity that Kazo should implement.  According to most of the respondents who are Self-Employed, Newsletter- Fashion updates/store updates/fashion tips is a better promotional activity that Kazo should implement.

 According to most of the respondents who have opt “others” as their profession, Point based purchase-discounts is a better promotional activity that Kazo should implement. The above analysis is rejected. This might be because most of the respondents were not true while filling up the questionnaires.

5.12. Monthly Disposable Income Vs Promotional activity that Kazo should implement It was interpreted that According to most of the respondents who have monthly disposable income of Rs5000 or below, Newsletter- Fashion updates/store  According to most of the respondents who have monthly disposable updates/fashion tips is a better promotional activity that Kazo should implement.  According to most of the respondents who have monthly disposable income of Rs5000-15000, Point based purchase-discounts is a better promotional activity that Kazo should implement.

 According to most of the respondents who have monthly disposable income of Rs15000-25000, Point based purchase-discounts is a better promotional activity that Kazo should implement .  According to most of the respondents who have monthly disposable income of Rs25000-35000, Newsletter- Fashion updates/store updates/fashion tips is a better promotional activity that Kazo should implement.  According to most of the respondents who have monthly disposable income of Rs35000-45000, Newsletter- Fashion updates/store updates/fashion tips is a better promotional activity that Kazo should implement.  According to most of the respondents whose monthly disposable income of Rs45000 or above, Exclusive membership-Fashion shows/Club nights/Kazo nights is a better promotional activity that Kazo should implement. The above analysis is rejected. This might be because most of the respondents were not true while filling up the questionnaires.

6. Conclusion •

Kazo needs to improve their display of products and focus more on visual merchandising.

•

The most preferred medium of promotion i.e magazine, newspaper and radio ads are missing.

•

Customers should be given a chance to become Exclusive member of the brand. Fashion shows and Kazo nights should be held in order to attract a large number of customers.

7. Recommendation •

KAZO needs to invest on several ATL for branding & BTL activities to target its potential customers. As the target market of Kazo is between the age group of 18 to 30 years of age, Kazo should implement its promotions in Coffee shops, Movie Theatres, Colleges, inside Malls.

•

Monthly visits make up the maximum part of footfalls to the store, which eventually needs to be converted to either fortnightly or weekly visit. Frequent addition of new designs and information about it through sales staff, online blogs or SMSs should motivate customers to come back to stores more frequently.

â&#x20AC;˘

Nearly 50% of the customers were okay with the display of window, but almost a quarter of customers felt the need for improvement. A few of the customers specially mentioned the need for frequent change of design on mannequin as that gives an idea of the collection inside.

â&#x20AC;˘

Loyalty Programs can be used as an effective tool to retain customers and make them purchase more often. As the majority of customers are young, a good amount of respondents were also interested in membership or invites for events like Fashion Shows and KAZO nights. Once in a while even this option can be used to increase brand loyalty.

8. Reference •

Ehrenberg, A. et al (2006)”When communication challenges brand associations: a framework for understanding consumer responses to brand image incongruity”, Journal of Consumer Behaviour, 5(1), 32-42.

•

Kotler, P. (2003). Marketing Management (11th ed.). New Jersey: Prentice Hall.

•

Lange, Fredrik, Sjödin, Henrik, and Törn, Fredrik (2005), “Effects of Ad-Brand Incongruency”, Journal of Current Issues and Research in Advertising, 27(2), 1-12.

•

Lee,T.S Leung C.S and Zhang Z.M Fashion Brand Image Marketing: Brand Image and Brand Personality[Online] Available from: file:///C:/Users/ILFS12/Downloads/paper.pdf [Assessed: February 17,2015]

•

Mowen, J. C., & Minor, M. (2001). Consumer behavior: A framework (2nd ed.). Upper Saddle River, New Jersey: Prentice-Hall.

•

Naureman,N Academia.edu.Consumer behaviour and marketing strategies[Online]9 Available from: https://www.academia.edu/6078770/CONSUMER_BEHAVIOR_and_MARKET ING_STRATEGY_CONSUMER_BEHAVIOR_and_MARKETING_STRATEGY [Assessed: February 18, 2015]

•

Oliver, Richard L. (1999). Whence Consumer Loyalty? Journal of Marketing, 63, 33-44.

•

Sundarraj,K. Baba.hb. An investigation on consumer behavior and preferences towards apparel, purchase by Indian consumers [Online] Available from: http://bada.hb.se/bitstream/2320/9248/1/2011.9.7.pdf [Assessed: February 18, 2015]

•

Till, Brian D. and Daniel W. Baack (2005),”Recall and Persuasion: Does Creative Advertising Matter?”, Journal of Advertising, Vol. 34 No. 3, 47-58.

9. Bibliography •

http://www.mydigitalfc.com/my-brand/kazo-add-oomph-apparel-market

•

http://www.vccircle.com/news/consumer/2014/05/28/women%E2%80%99sapparel-brand-kazo-eyes-17m-private-funding

•

http://www.kazo.com/aboutus/

•

http://www.thehindubusinessline.com/news/breaking-trends-indian-womennow-prefer-western-wear/article5966666.ece

•

http://www.vintage-obsession.com/diwali-shopping-kazo-bangalore/

•

http://www.fashionunited.in/news/fashion/kazo-has-eight-store-launches-inthe-pipeline-260320135168

•

http://bada.hb.se/bitstream/2320/9248/1/2011.9.7.pdf

•

https://www.academia.edu/6078770/CONSUMER_BEHAVIOR_and_MARKET ING_STRATEGY_CONSUMER_BEHAVIOR_and_MARKETING_STRATEGY

•

file:///C:/Users/ILFS12/Downloads/paper.pdf

Annexure Questionnaire We are students of pearl academy conducting a survey on the Brand Kazo to understand its customer profile.

Q.1 Gender •

Female

•

Male

Q2. Age

•

Graduate

Q5. Profession •

Business

•

Student

•

18-21 years

•

Designer

•

22-25 years

•

Self-Employed

•

26-29 years

•

Others

•

30 years and above

Q3. Marital status

Q6. Disposable Monthly Income •

Below Rs. 5,000

•

Single

•

RS. 5000-Rs 15,000

•

Married

•

Rs. 15,000-Rs. 25,000

•

Others

•

Rs. 25,000-Rs. 35,000

Q4. Education

•

Rs. 35,000- Rs. 45,000

•

Above Rs. 45,000

•

Modest

•

Fashionable

•

Undergraduate

•

Postgraduate

Q7. Choose 3 words that best define your lifestyle-

•

Independent

•

Trendy

•

Urban

•

Conservative

•

Zara

•

Traditional

•

Mango

•

Promod

Every week

Q10. Which are the other brands you are most likely to visit while shopping? (You can choose more than one option)

Q8. How did you come to know about KAZO? •

Magazine ad

•

Sisley

•

Newspaper ad

•

Espirit

•

Word of Mouth

•

Others_________________________

•

Radio

•

Browsing through the mall

•

Promotions

Q11.When you think of KAZO, first thing that comes to your mind is-

Q9. How many times do you visit KAZO? •

Every month

•

Twice in a month

•

Every 10 days

•

Evening Wear

•

Party Wear

•

Casual Wear

•

Accessories

•

Others_________________________ _______

Q12. How much would you rank the following aspects of Kazo? 5 Fabric Design Variety of designs Display of products Price Range Music Staff Etiquettes Visual Merchandising

Q13. Which Promotional Activity attracts you the most? •

Television Ads

•

Malls

•

Radio Ads

•

Magazines

•

Newspapers Ads

•

Theatres Ads

•

Others ____________________________

Television Ads

•

Malls

•

Radio Ads

Magazines

•

Newspapers Ads

•

Theatres Ads

•

Others ____________________________

Q15. Which of the following promotional activity do you want Kazo to implement?

Q14. Where all have you seen Kazo’s promotions? •

•

Point Based Purchase – Discounts

•

Newsletter- Fashion Updates/ Store Updates/ Style Tips

•

Exclusive Membership- Fashion Shows/ Club Invites/ KAZO Nights

•

Others_________________________ ___

THANK YOU FOR YOUR TIME AND FEEDBACK

GET FILE='C:\Users\HEWLETT PACKARD\Desktop\stats work.sav'. DATASET NAME DataSet1 WINDOW=FRONT. DATASET ACTIVATE DataSet1. SAVE OUTFILE='C:\Users\HEWLETT PACKARD\Desktop\stats work.sav' /COMPRESSED. SAVE OUTFILE='C:\Users\HEWLETT PACKARD\Desktop\stats work.sav' /COMPRESSED. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes V.Merchaniding BY gender /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Oneway

Notes

Output Created

09-APR-2015 10:04:28

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

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Weight

<none>

Split File

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N of Rows in Working Data File

100 User-defined missing values are

Definition of Missing

treated as missing. Statistics for each analysis are

Missing Value Handling

based on cases with no missing

Cases Used

data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY gender /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.05

Elapsed Time

00:00:00.06

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\stats work.sav

Descriptives N

Mean

Std. Deviation

Std. Error

95% Confidence Interval for Me Lower Bound

Fabric

Design

Variety Display

Upper Bou

male

3.8375

.97362

.10885

3.6208

female

3.7000

.65695

.14690

3.3925

Total

100

3.8100

.91778

.09178

3.6279

male

3.7250

.81092

.09066

3.5445

female

3.4500

.82558

.18460

3.0636

Total

100

3.6700

.81718

.08172

3.5079

male

3.3875

.90699

.10140

3.1857

female

3.3000

.86450

.19331

2.8954

Total

100

3.3700

.89505

.08950

3.1924

male

3.4500

.92641

.10358

3.2438

female

Price

Music

S.Ettiquetes

V.Merchaniding

3.0000

.85840

.19194

2.5983

Total

100

3.3600

.92682

.09268

3.1761

male

3.0750

.95168

.10640

2.8632

female

2.9500

.75915

.16975

2.5947

Total

100

3.0500

.91425

.09143

2.8686

male

2.7375

1.06431

.11899

2.5006

female

2.9000

.96791

.21643

2.4470

Total

100

2.7700

1.04306

.10431

2.5630

male

3.0375

1.04873

.11725

2.8041

female

3.0000

1.29777

.29019

2.3926

Total

100

3.0300

1.09595

.10960

2.8125

male

3.2000

.99873

.11166

2.9777

female

3.1000

1.07115

.23952

2.5987

100

3.1800

1.00885

.10088

2.9798

Total

ANOVA Sum of Squares Between Groups Fabric

Mean Square

.302

Within Groups

83.088

.848

Total

83.390

1.210

Within Groups

64.900

.662

Total

66.110

Between Groups Design

Sig. .357

.552

1.827

.180

Between Groups Variety

.123

Within Groups

79.188

.808

Total

79.310

3.240

Within Groups

81.800

.835

Total

85.040

.250

Within Groups

82.500

.842

Total

82.750

.423

Within Groups

107.288

1.095

Total

107.710

.023

Within Groups

118.887

1.213

Total

118.910

.160

Within Groups

100.600

1.027

Total

100.760

Between Groups Display

Between Groups Price

Between Groups Music

Between Groups S.Ettiquetes

Between Groups V.Merchaniding

ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes V.Merchaniding BY Age /STATISTICS DESCRIPTIVES /MISSING ANALYSIS

Oneway Notes Output Created

09-APR-2015 10:04:52

Comments Input

C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Active Dataset

DataSet1

.152

.698

3.882

.052

.297

.587

.386

.536

.019

.892

.156

.694

Filter

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Weight

<none>

Split File

<none>

N of Rows in Working Data File

100 User-defined missing values are

Definition of Missing

treated as missing. Statistics for each analysis are

Missing Value Handling

based on cases with no missing

Cases Used

data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY Age /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.03

Elapsed Time

00:00:00.05

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\stats work.sav

Descriptives N

Mean

Std. Deviation

Std. Error

95% Confidence Lower Bound

Fabric

18-21 years

3.9074

.73378

.09985

3.7071

22-25 years

3.7143

1.00712

.21977

3.2559

26-29 years

3.6875

1.13835

.28459

3.0809

3.6667

1.32288

.44096

2.6498

100

3.8100

.91778

.09178

3.6279

18-21 years

3.5370

.79415

.10807

3.3203

22-25 years

3.8095

.67964

.14831

3.5002

26-29 years

3.9375

.77190

.19298

3.5262

3.6667

1.22474

.40825

2.7252

100

3.6700

.81718

.08172

3.5079

18-21 years

3.2593

.87276

.11877

3.0210

22-25 years

3.4762

.67964

.14831

3.1668

26-29 years

3.6250

1.14746

.28687

3.0136

3.3333

1.00000

.33333

2.5647

100

3.3700

.89505

.08950

3.1924

3.1852

.91268

.12420

2.9361

30 years and above Total

Design

30 years and above Total

Variety

30 years and above Total Display

18-21 years

22-25 years

3.7619

.76842

.16768

3.4121

26-29 years

3.5625

.81394

.20349

3.1288

3.1111

1.26930

.42310

2.1354

100

3.3600

.92682

.09268

3.1761

18-21 years

3.0741

.84344

.11478

2.8439

22-25 years

3.0476

1.02353

.22335

2.5817

26-29 years

3.2500

.93095

.23274

2.7539

2.5556

1.01379

.33793

1.7763

100

3.0500

.91425

.09143

2.8686

18-21 years

2.9259

1.06136

.14443

2.6362

22-25 years

2.7143

1.05560

.23035

2.2338

26-29 years

2.6250

1.02470

.25617

2.0790

2.2222

.83333

.27778

1.5817

100

2.7700

1.04306

.10431

2.5630

18-21 years

2.9815

1.03688

.14110

2.6985

22-25 years

3.1905

1.16701

.25466

2.6593

26-29 years

2.9375

1.12361

.28090

2.3388

3.1111

1.36423

.45474

2.0625

100

3.0300

1.09595

.10960

2.8125

18-21 years

3.1667

1.00471

.13672

2.8924

22-25 years

3.3333

.91287

.19920

2.9178

26-29 years

3.3750

.88506

.22127

2.9034

2.5556

1.33333

.44444

1.5307

100

3.1800

1.00885

.10088

2.9798

30 years and above Total

Price

30 years and above Total

Music

30 years and above Total

S.Ettiquetes

30 years and above Total

V.Merchaniding

30 years and above Total

ANOVA Sum of Squares Between Groups Fabric

Design

Mean Square

1.130

.377

Within Groups

82.260

.857

Total

83.390

2.508

Between Groups

.836

Sig. .439

.725

1.262

.292

Within Groups

63.602

Total

66.110

1.952

.651

Within Groups

77.358

.806

Total

79.310

6.256

2.085

Within Groups

78.784

.821

Total

85.040

2.872

.957

Within Groups

79.878

.832

Total

82.750

4.415

1.472

Within Groups

103.295

1.076

Total

107.710

.864

.288

Within Groups

118.046

1.230

Total

118.910

4.621

1.540

96.139

1.001

100.760

Between Groups Variety

Between Groups Display

Between Groups Price

Between Groups Music

Between Groups S.Ettiquetes

Between Groups V.Merchaniding

Within Groups Total

.663

ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes V.Merchaniding BY Relationship /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Oneway Notes Output Created Comments

09-APR-2015 10:05:46

.807

.493

2.541

.061

1.150

.333

1.368

.257

.234

.872

1.538

.210

C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

100 User-defined missing values are

Definition of Missing

treated as missing. Statistics for each analysis are

Missing Value Handling

based on cases with no missing

Cases Used

data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY Relationship /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.02

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\stats work.sav

Descriptives N

Mean

Std. Deviation

Std. Error

95% Confidence Interval for Me Lower Bound

Fabric

Design

Variety

Upper Bou

single

3.8308

.83981

.10417

3.6227

Married

3.7368

1.28418

.29461

3.1179

others

3.8125

.75000

.18750

3.4129

Total

100

3.8100

.91778

.09178

3.6279

single

3.6308

.80174

.09944

3.4321

Married

3.6842

1.00292

.23009

3.2008

others

3.8125

.65511

.16378

3.4634

Total

100

3.6700

.81718

.08172

3.5079

single

3.3692

.83981

.10417

3.1611

Married

3.5263

1.12390

.25784

2.9846

others

3.1875

.83417

.20854

2.7430

Display

Price

Music

S.Ettiquetes

V.Merchaniding

Total

100

3.3700

.89505

.08950

3.1924

single

3.4154

.88198

.10940

3.1968

Married

3.2105

1.08418

.24873

2.6880

others

3.3125

.94648

.23662

2.8082

Total

100

3.3600

.92682

.09268

3.1761

single

3.0308

.84722

.10509

2.8208

Married

3.1579

1.11869

.25664

2.6187

others

3.0000

.96609

.24152

2.4852

Total

100

3.0500

.91425

.09143

2.8686

single

2.8615

1.07350

.13315

2.5955

Married

2.4737

1.07333

.24624

1.9564

others

2.7500

.85635

.21409

2.2937

Total

100

2.7700

1.04306

.10431

2.5630

single

2.9692

1.04537

.12966

2.7102

Married

3.1053

1.24252

.28505

2.5064

others

3.1875

1.16726

.29182

2.5655

Total

100

3.0300

1.09595

.10960

2.8125

single

3.2615

.95651

.11864

3.0245

Married

3.1053

1.28646

.29513

2.4852

others

2.9375

.85391

.21348

2.4825

100

3.1800

1.00885

.10088

2.9798

Total

ANOVA Sum of Squares Between Groups Fabric

.065

Within Groups

83.260

.858

Total

83.390

.429

.214

Within Groups

65.681

.677

Total

66.110

.997

.499

Within Groups

78.313

.807

Total

79.310

.660

.330

Within Groups

84.380

.870

Total

85.040

.285

.143

Within Groups

82.465

.850

Total

82.750

2.219

Between Groups Variety

Between Groups Display

Between Groups Price Music

Mean Square

.130

Between Groups Design

Between Groups

1.110

Sig. .076

.927

.317

.729

.618

.541

.379

.685

.168

.846

1.020

.364

Within Groups

105.491

Total

107.710

.745

.372

Within Groups

118.165

1.218

Total

118.910

1.479

.740

99.281

1.024

100.760

Between Groups S.Ettiquetes

Between Groups V.Merchaniding

Within Groups Total

1.088

ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes V.Merchaniding BY Education /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Oneway Notes Output Created

09-APR-2015 10:06:21

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each analysis are

Missing Value Handling Cases Used

based on cases with no missing data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY Education /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.05

.306

.737

.723

.488

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\stats work.sav

Descriptives N

Mean

Std. Deviation

Std. Error

95% Confidence Inter Lower Bound

Fabric

Design

Variety

Display

Price

Music

S.Ettiquetes

V.Merchaniding

Undergraduate

3.8824

.81602

.11427

3.6528

Postgraduate

3.6857

1.10537

.18684

3.3060

Graduate

3.9231

.75955

.21066

3.4641

4.00

3.0000

Total

100

3.8100

.91778

.09178

3.6279

Undergraduate

3.5294

.78366

.10973

3.3090

Postgraduate

3.8000

.90098

.15229

3.4905

Graduate

3.9231

.64051

.17765

3.5360

4.00

3.0000

Total

100

3.6700

.81718

.08172

3.5079

Undergraduate

3.2353

.88517

.12395

2.9863

Postgraduate

3.4857

.98134

.16588

3.1486

Graduate

3.5385

.66023

.18311

3.1395

4.00

4.0000

Total

100

3.3700

.89505

.08950

3.1924

Undergraduate

3.1961

.93850

.13142

2.9321

Postgraduate

3.5143

.88688

.14991

3.2096

Graduate

3.7692

.59914

.16617

3.4072

4.00

1.0000

Total

100

3.3600

.92682

.09268

3.1761

Undergraduate

3.1373

.87223

.12214

2.8919

Postgraduate

2.9143

.98134

.16588

2.5772

Graduate

3.1538

.89872

.24926

2.6108

4.00

2.0000

Total

100

3.0500

.91425

.09143

2.8686

Undergraduate

2.9412

1.04712

.14663

2.6467

Postgraduate

2.5429

1.06668

.18030

2.1764

Graduate

2.7692

.92681

.25705

2.2092

4.00

2.0000

Total

100

2.7700

1.04306

.10431

2.5630

Undergraduate

2.9608

1.05756

.14809

2.6633

Postgraduate

2.9143

1.12122

.18952

2.5291

Graduate

3.4615

1.05003

.29123

2.8270

4.00

5.0000

Total

100

3.0300

1.09595

.10960

2.8125

3.1569

1.00742

.14107

2.8735

Undergraduate

Postgraduate

3.0000

1.11144

.18787

2.6182

Graduate

3.6923

.48038

.13323

3.4020

4.00

4.0000

Total

100

3.1800

1.00885

.10088

2.9798

ANOVA Sum of Squares Between Groups Fabric

.543

Within Groups

81.760

.852

Total

83.390

2.881

.960

Within Groups

63.229

.659

Total

66.110

2.160

.720

Within Groups

77.150

.804

Total

79.310

9.950

3.317

Within Groups

75.090

.782

Total

85.040

2.276

.759

Within Groups

80.474

.838

Total

82.750

3.893

1.298

Within Groups

103.817

1.081

Total

107.710

7.015

2.338

Within Groups

111.895

1.166

Total

118.910

5.246

1.749

95.514

.995

100.760

Between Groups Variety

Between Groups Display

Between Groups Price

Between Groups Music

Between Groups S.Ettiquetes

Between Groups V.Merchaniding

Mean Square

1.630

Between Groups Design

Within Groups Total

ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes V.Merchaniding BY Profession /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Oneway

Sig. .638

.592

1.458

.231

.896

.446

4.240

.007

.905

.442

1.200

.314

2.006

.118

1.757

.161

Notes Output Created

09-APR-2015 10:06:41

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

100 User-defined missing values are

Definition of Missing

treated as missing. Statistics for each analysis are

Missing Value Handling

based on cases with no missing

Cases Used

data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY Profession /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.06

Elapsed Time

00:00:00.05

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\stats work.sav

Descriptives N

Mean

Std. Deviation

Std. Error

95% Confidence Interv Lower Bound

Business

Fabric

3.1250

1.45774

.51539

1.9063

Student

3.7969

.85782

.10723

3.5826

Designer

4.0000

.81650

.25820

3.4159

Self Employed

4.0000

.92582

.32733

3.2260

others

4.1111

.78174

.26058

3.5102

23.00

4.0000

100

3.8100

.91778

.09178

3.6279

3.5000

1.30931

.46291

2.4054

3.6250

.78680

.09835

3.4285

Total Design

Business Student

Designer

3.7000

.67495

.21344

3.2172

Self Employed

3.7500

.46291

.16366

3.3630

others

4.0000

1.00000

.33333

3.2313

23.00

4.0000

100

3.6700

.81718

.08172

3.5079

3.5000

1.19523

.42258

2.5008

Student

3.2969

.86703

.10838

3.0803

Designer

3.5000

.84984

.26874

2.8921

Self Employed

3.5000

1.06904

.37796

2.6063

others

3.4444

.88192

.29397

2.7665

23.00

4.0000

100

3.3700

.89505

.08950

3.1924

3.2500

1.28174

.45316

2.1784

Student

3.2969

.88515

.11064

3.0758

Designer

3.0000

1.05409

.33333

2.2459

Self Employed

3.7500

.70711

.25000

3.1588

others

4.0000

.70711

.23570

3.4565

23.00

3.0000

100

3.3600

.92682

.09268

3.1761

2.6250

1.30247

.46049

1.5361

Student

3.1094

.89296

.11162

2.8863

Designer

3.1000

.73786

.23333

2.5722

Self Employed

2.8750

.99103

.35038

2.0465

others

3.1111

.92796

.30932

2.3978

23.00

3.0000

100

3.0500

.91425

.09143

2.8686

2.7500

1.28174

.45316

1.6784

Student

2.8594

1.05209

.13151

2.5966

Designer

2.5000

.84984

.26874

1.8921

Self Employed

2.0000

.92582

.32733

1.2260

others

3.1111

.92796

.30932

2.3978

23.00

3.0000

100

2.7700

1.04306

.10431

2.5630

3.1250

1.45774

.51539

1.9063

Student

2.9688

.99153

.12394

2.7211

Designer

2.8000

1.31656

.41633

1.8582

Self Employed

3.1250

1.35620

.47949

1.9912

others

3.6667

1.00000

.33333

2.8980

23.00

2.0000

100

3.0300

1.09595

.10960

2.8125

3.1250

1.24642

.44068

2.0830

Student

3.2031

.96247

.12031

2.9627

Designer

3.5000

.97183

.30732

2.8048

Total Business

Variety

Total Business

Display

Total Business

Price

Total Business

Music

Total Business

S.Ettiquetes

Total V.Merchaniding

Business

Self Employed

2.3750

.91613

.32390

1.6091

others

3.5556

1.01379

.33793

2.7763

23.00

2.0000

100

3.1800

1.00885

.10088

2.9798

Total

ANOVA Sum of Squares Between Groups Fabric

1.053

Within Groups

78.123

.831

Total

83.390

1.510

.302

Within Groups

64.600

.687

Total

66.110

1.228

.246

Within Groups

78.082

.831

Total

79.310

6.681

1.336

Within Groups

78.359

.834

Total

85.040

1.977

.395

Within Groups

80.773

.859

Total

82.750

7.087

1.417

Within Groups

100.623

1.070

Total

107.710

5.622

1.124

Within Groups

113.288

1.205

Total

118.910

8.928

1.786

91.832

.977

100.760

Between Groups Variety

Between Groups Display

Between Groups Price

Between Groups Music

Between Groups S.Ettiquetes

Between Groups V.Merchaniding

Mean Square

5.267

Between Groups Design

Within Groups Total

ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes V.Merchaniding BY Income /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Oneway

Sig.

1.267

.285

.439

.820

.296

.914

1.603

.167

.460

.805

1.324

.261

.933

.463

1.828

.115

Notes Output Created

09-APR-2015 10:06:54

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

100 User-defined missing values are

Definition of Missing

treated as missing. Statistics for each analysis are

Missing Value Handling

based on cases with no missing

Cases Used

data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY Income /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.02

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\stats work.sav

Descriptives N

Mean

Std. Deviation

Std. Error

95% Confidenc Lower Bound

Below Rs. 5000

Fabric

4.1111

.60093

.20031

3.649

Rs 5000- Rs 15000

3.8636

.88884

.18950

3.469

Rs 15000- Rs 25000

3.4615

.76057

.14916

3.154

Rs 25000-Rs35000

4.2632

.56195

.12892

3.992

Rs 35000-Rs45000

3.7692

1.30089

.36080

2.983

Above 45000

3.5455

1.21356

.36590

2.730

100

3.8100

.91778

.09178

3.627

4.0000

.70711

.23570

3.456

Rs 5000- Rs 15000

3.5455

.91168

.19437

3.141

Rs 15000- Rs 25000

3.4615

.76057

.14916

3.154

Rs 25000-Rs35000

3.8947

.56713

.13011

3.621

Rs 35000-Rs45000

4.0000

.70711

.19612

3.572

Above 45000

3.3636

1.12006

.33771

2.611

100

3.6700

.81718

.08172

3.507

3.6667

.70711

.23570

3.123

Rs 5000- Rs 15000

3.3182

.77989

.16627

2.972

Rs 15000- Rs 25000

3.0769

.89098

.17474

2.717

Rs 25000-Rs35000

3.4211

.90159

.20684

2.986

Rs 35000-Rs45000

3.6154

1.04391

.28953

2.984

Above 45000

3.5455

1.03573

.31228

2.849

100

3.3700

.89505

.08950

3.192

3.1111

1.26930

.42310

2.135

Rs 5000- Rs 15000

3.2273

.75162

.16025

2.894

Rs 15000- Rs 25000

3.3462

.97744

.19169

2.951

Rs 25000-Rs35000

3.5789

.96124

.22052

3.115

Rs 35000-Rs45000

3.6154

.86972

.24122

3.089

Above 45000

3.1818

.87386

.26348

2.594

100

3.3600

.92682

.09268

3.176

2.7778

.66667

.22222

2.265

Rs 5000- Rs 15000

3.0455

.89853

.19157

2.647

Rs 15000- Rs 25000

2.9231

.84489

.16570

2.581

Rs 25000-Rs35000

3.0000

.94281

.21630

2.545

Rs 35000-Rs45000

3.6923

.94733

.26274

3.119

Above 45000

2.9091

1.04447

.31492

2.207

100

3.0500

.91425

.09143

2.868

2.6667

1.22474

.40825

1.725

Rs 5000- Rs 15000

2.8636

1.12527

.23991

2.364

Rs 15000- Rs 25000

2.7692

1.03180

.20235

2.352

Rs 25000-Rs35000

2.6316

1.06513

.24436

2.118

Rs 35000-Rs45000

2.9231

.95407

.26461

2.346

Above 45000

2.7273

1.00905

.30424

2.049

100

2.7700

1.04306

.10431

2.563

Total Below Rs. 5000

Design

Total Below Rs. 5000

Variety

Total Below Rs. 5000

Display

Total Below Rs. 5000

Price

Total Below Rs. 5000

Music

Total

Below Rs. 5000

S.Ettiquetes

3.4444

1.42400

.47467

2.349

Rs 5000- Rs 15000

2.7273

.98473

.20995

2.290

Rs 15000- Rs 25000

2.9615

1.03849

.20366

2.542

Rs 25000-Rs35000

3.0526

1.02598

.23538

2.558

Rs 35000-Rs45000

3.3077

1.31559

.36488

2.512

Above 45000

3.0909

1.04447

.31492

2.389

100

3.0300

1.09595

.10960

2.812

3.4444

.88192

.29397

2.766

Rs 5000- Rs 15000

3.1364

.94089

.20060

2.719

Rs 15000- Rs 25000

3.0385

1.07632

.21108

2.603

Rs 25000-Rs35000

3.2632

.87191

.20003

2.842

Rs 35000-Rs45000

3.2308

1.36344

.37815

2.406

Above 45000

3.1818

.98165

.29598

2.522

100

3.1800

1.00885

.10088

2.979

Total Below Rs. 5000

V.Merchaniding

Total

ANOVA Sum of Squares Between Groups Fabric

1.746

Within Groups

74.661

.794

Total

83.390

5.859

1.172

Within Groups

60.251

.641

Total

66.110

4.255

.851

Within Groups

75.055

.798

Total

79.310

3.058

.612

Within Groups

81.982

.872

Total

85.040

6.715

1.343

Within Groups

76.035

.809

Total

82.750

.978

.196

Within Groups

106.732

1.135

Total

107.710

4.737

.947

Within Groups

114.173

1.215

Total

118.910

1.357

Between Groups Variety

Between Groups Display

Between Groups Price

Between Groups Music

Between Groups S.Ettiquetes V.Merchaniding

Mean Square

8.729

Between Groups Design

Between Groups

.271

Sig.

2.198

.061

1.828

.115

1.066

.384

.701

.624

1.660

.152

.172

.972

.780

.567

.257

.935

Within Groups Total

99.403

100.760

1.057

Notes Output Created

09-APR-2015 10:07:06

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each analysis are

Missing Value Handling Cases Used

based on cases with no missing data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY Awareness /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.05

Elapsed Time

00:00:00.05

Notes Output Created

09-APR-2015 10:07:22

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each analysis are

Missing Value Handling Cases Used

based on cases with no missing data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY Visit /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.03

Elapsed Time

00:00:00.03

Notes Output Created

09-APR-2015 10:07:39

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each analysis are

Missing Value Handling Cases Used

based on cases with no missing data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY Competitors /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.02

Notes Output Created

09-APR-2015 10:07:55

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each analysis are

Missing Value Handling Cases Used

based on cases with no missing data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY Products /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.02

Notes Output Created

09-APR-2015 10:08:16

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each analysis are

Missing Value Handling Cases Used

based on cases with no missing data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY P.Activity /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.05

Elapsed Time

00:00:00.03

Notes Output Created

09-APR-2015 10:08:30

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each analysis are

Missing Value Handling Cases Used

based on cases with no missing data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes

Syntax

V.Merchaniding BY Promotions /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.05

Elapsed Time

00:00:00.03

Notes Output Created

09-APR-2015 10:08:42

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each analysis are

Missing Value Handling Cases Used

based on cases with no missing data for any variable in the analysis. ONEWAY Fabric Design Variety Display Price Music S.Ettiquetes V.Merchaniding BY

Syntax

Reccomendations /STATISTICS DESCRIPTIVES /MISSING ANALYSIS.

Resources

Processor Time

00:00:00.00

Elapsed Time

00:00:00.02

Notes Output Created

09-APR-2015 10:16:47

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each table are

Missing Value Handling Cases Used

based on all the cases with valid data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=Reccomendations BY gender

Syntax

/FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.02

Dimensions Requested Cells Available

2 174762

Notes Output Created

09-APR-2015 10:17:06

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each table are

Missing Value Handling Cases Used

based on all the cases with valid data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=Reccomendations BY Age

Syntax

/FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.03

Elapsed Time

00:00:00.03

Dimensions Requested Cells Available

2 174762

Notes Output Created

09-APR-2015 10:22:58

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each table are

Missing Value Handling Cases Used

based on all the cases with valid data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=Reccomendations BY Relationship

Syntax

/FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.02

Dimensions Requested Cells Available

2 174762

Notes Output Created

09-APR-2015 10:23:12

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each table are

Missing Value Handling Cases Used

based on all the cases with valid data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=Reccomendations BY Education

Syntax

/FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.03

Elapsed Time

00:00:00.03

Dimensions Requested Cells Available

2 174762

Notes Output Created

09-APR-2015 10:23:25

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each table are

Missing Value Handling Cases Used

based on all the cases with valid data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=Reccomendations BY Profession

Syntax

/FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.03

Elapsed Time

00:00:00.02

Dimensions Requested Cells Available

2 174762

Notes Output Created

09-APR-2015 10:24:32

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each table are

Missing Value Handling Cases Used

based on all the cases with valid data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=Reccomendations BY Income

Syntax

/FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.02

Dimensions Requested Cells Available

2 174762

Notes Output Created

09-APR-2015 10:47:57

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each table are

Missing Value Handling Cases Used

based on all the cases with valid data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=Competitors BY Age /FORMAT=AVALUE TABLES

Syntax

/STATISTICS=CHISQ /CELLS=COUNT /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.02

Dimensions Requested Cells Available

2 174762

Crosstabs Notes Output Created

10-APR-2015 12:07:13

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\Sem 2\Stats\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each table are

Missing Value Handling Cases Used

based on all the cases with valid data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=gender BY Reccomendations /FORMAT=AVALUE TABLES

Syntax

/STATISTICS=CHISQ /CELLS=COUNT ROW COLUMN TOTAL /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.03

Elapsed Time

00:00:00.06

Dimensions Requested Cells Available

2 174762

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\Sem 2\Stats\stats work.sav

Case Processing Summary Cases Valid N

Missing Percent

Total

Percent

gender of the respondent * Promotional Activity Kazo

100

100.0%

0.0%

100

100.0%

should Implement

gender of the respondent * Promotional Activity Kazo should Implement Crosstabulation

Promotional Activity Kazo should Imp Point based

Newsletter-

Exculu

Purchase-

Fashion

Discounts

Updates/Store

Membe

Fash

Updates/Style Tips

shows

Nights/K

nigh gender of the respondent

Count % within gender of the male

respondent % within Promotional Activity Kazo should Implement % of Total

female

Count % within gender of the respondent

38.8%

40.0%

88.6%

82.1%

31.0%

32.0%

20.0%

35.0%

% within Promotional Activity Kazo should Implement % of Total Count % within gender of the respondent

Total

% within Promotional Activity Kazo should Implement % of Total

11.4%

17.9%

4.0%

7.0%

35.0%

39.0%

100.0%

35.0%

39.0%

Chi-Square Tests Value

Asymp. Sig. (2sided)

7.960a

.047

Likelihood Ratio

7.152

.067

Linear-by-Linear Association

5.641

.018

Pearson Chi-Square

N of Valid Cases

100

a. 2 cells (25.0%) have expected count less than 5. The minimum expected count is .20.

CROSSTABS /TABLES=Age BY Reccomendations /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW COLUMN TOTAL /COUNT ROUND CELL.

Crosstabs

Notes Output Created Comments

10-APR-2015 12:08:42

C:\Users\HEWLETT Data

PACKARD\Desktop\Sem 2\Stats\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

100 User-defined missing values are

Definition of Missing

treated as missing. Statistics for each table are

Missing Value Handling

based on all the cases with valid

Cases Used

data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=Age BY Reccomendations /FORMAT=AVALUE TABLES

Syntax

/STATISTICS=CHISQ /CELLS=COUNT ROW COLUMN TOTAL /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.00

Elapsed Time

00:00:00.05

Dimensions Requested

Cells Available

174762

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\Sem 2\Stats\stats work.sav

Case Processing Summary Cases Valid N

Missing Percent

Total

Percent

Age of the respondent * Promotional Activity Kazo should Implement

100

100.0%

0.0%

100

100.0%

Age of the respondent * Promotional Activity Kazo should Implement Crosstabula

Promotional Activity Kazo Point based

Newsletter-

Purchase-

Fashion

Discounts

Updates/Store Updates/Style Tips

Count % within Age of the respondent 18-21 years

% within Promotional Activity Kazo should Implement % of Total Count % within Age of the respondent

22-25 years

% within Promotional Activity Kazo should Implement % of Total

Age of the respondent

Count % within Age of the respondent 26-29 years

% within Promotional Activity Kazo should Implement % of Total Count % within Age of the respondent

30 years and above

% within Promotional Activity Kazo should Implement % of Total Count % within Age of the respondent

Total

% within Promotional Activity Kazo should Implement % of Total

Chi-Square Tests Value

Asymp. Sig. (2sided)

35.2%

37.0%

54.3%

51.3%

19.0%

20.0%

47.6%

38.1%

28.6%

20.5%

10.0%

8.0%

31.2%

37.5%

14.3%

15.4%

5.0%

6.0%

11.1%

55.6%

2.9%

12.8%

1.0%

5.0%

35.0%

39.0%

100.0%

35.0%

39.0%

9.628a

.381

9.936

.356

Linear-by-Linear Association

.627

.428

N of Valid Cases

100

Pearson Chi-Square Likelihood Ratio

a. 8 cells (50.0%) have expected count less than 5. The minimum expected count is .09.

CROSSTABS /TABLES=Relationship BY Reccomendations /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW COLUMN TOTAL /COUNT ROUND CELL.

Crosstabs

Notes Output Created

10-APR-2015 12:09:02

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\Sem 2\Stats\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each table are

Missing Value Handling Cases Used

based on all the cases with valid data in the specified range(s) for all variables in each table.

CROSSTABS /TABLES=Relationship BY Reccomendations /FORMAT=AVALUE TABLES

Syntax

/STATISTICS=CHISQ /CELLS=COUNT ROW COLUMN TOTAL /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.08

Dimensions Requested

Cells Available

174762

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\Sem 2\Stats\stats work.sav

Case Processing Summary Cases Valid N

Missing Percent

Total

Percent

Marital status of the respondent * Promotional Activity Kazo

100

100.0%

0.0%

100

100.0%

should Implement

Marital status of the respondent * Promotional Activity Kazo should Implement Crosstabula

Promotional Activity Kazo should Im Point based

Newsletter-

Excu

Purchase-

Fashion

Memb

Discounts

Updates/Store Updates/Style Tips

Fas

show

Nights

nig Marital status of the respondent

single

Count

% within Marital status of the respondent % within Promotional Activity Kazo should Implement % of Total Count % within Marital status of the respondent

Married

% within Promotional Activity Kazo should Implement % of Total Count % within Marital status of the respondent

others

% within Promotional Activity Kazo should Implement % of Total Count % within Marital status of the respondent

Total

% within Promotional Activity Kazo should Implement % of Total

Chi-Square Tests Value

Asymp. Sig. (2sided)

.802

3.390

.759

Linear-by-Linear Association

.708

.400

N of Valid Cases

100

Pearson Chi-Square Likelihood Ratio

3.056

a. 5 cells (41.7%) have expected count less than 5. The minimum expected count is .16.

40.0%

35.4%

74.3%

59.0%

26.0%

23.0%

26.3%

42.1%

14.3%

20.5%

5.0%

8.0%

25.0%

50.0%

11.4%

20.5%

4.0%

8.0%

35.0%

39.0%

100.0%

35.0%

39.0%

CROSSTABS /TABLES=Education BY Reccomendations /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW COLUMN TOTAL /COUNT ROUND CELL.

Crosstabs

Notes Output Created

10-APR-2015 12:09:41

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\Sem 2\Stats\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

100

User-defined missing values are

Definition of Missing

treated as missing. Statistics for each table are

Missing Value Handling

based on all the cases with valid

Cases Used

data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=Education BY Reccomendations /FORMAT=AVALUE TABLES

Syntax

/STATISTICS=CHISQ /CELLS=COUNT ROW COLUMN TOTAL /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.05

Elapsed Time

00:00:00.03

Dimensions Requested

Cells Available

174762

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\Sem 2\Stats\stats work.sav

Case Processing Summary Cases Valid N

Missing Percent

Total

Percent

Education level of the respondent * Promotional

100

100.0%

0.0%

100

100.0%

Activity Kazo should Implement

Education level of the respondent * Promotional Activity Kazo should Implement Crosst Promotional Activity Kazo

Point based

Newsletter-

Purchase-

Fashion

Discounts

Updates/Store Updates/Style Tips

Count % within Education level of the Undergraduate

respondent % within Promotional Activity Kazo should Implement % of Total Count % within Education level of the

Postgraduate

respondent % within Promotional Activity Kazo should Implement

Education level of the

% of Total

respondent

Count % within Education level of the Graduate

respondent % within Promotional Activity Kazo should Implement % of Total Count % within Education level of the

4.00

respondent % within Promotional Activity Kazo should Implement % of Total Count % within Education level of the respondent

Total

% within Promotional Activity Kazo should Implement % of Total

Chi-Square Tests

37.3%

35.3%

54.3%

46.2%

19.0%

18.0%

31.4%

42.9%

31.4%

38.5%

11.0%

15.0%

38.5%

46.2%

14.3%

15.4%

5.0%

6.0%

0.0%

35.0%

39.0%

100.0%

35.0%

39.0%

Value

Asymp. Sig. (2sided)

.208

9.825

.365

Linear-by-Linear Association

.128

.721

N of Valid Cases

100

Pearson Chi-Square Likelihood Ratio

12.100

a. 9 cells (56.3%) have expected count less than 5. The minimum expected count is .01.

CROSSTABS /TABLES=Profession BY Reccomendations /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW COLUMN TOTAL /COUNT ROUND CELL.

Crosstabs Notes Output Created Comments

10-APR-2015 12:10:01

C:\Users\HEWLETT Data

PACKARD\Desktop\Sem 2\Stats\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

100 User-defined missing values are

Definition of Missing

treated as missing. Statistics for each table are

Missing Value Handling

based on all the cases with valid

Cases Used

data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=Profession BY Reccomendations /FORMAT=AVALUE TABLES

Syntax

/STATISTICS=CHISQ /CELLS=COUNT ROW COLUMN TOTAL /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.02

Dimensions Requested

Cells Available

174762

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\Sem 2\Stats\stats work.sav

Case Processing Summary Cases Valid N

Missing Percent

Total

Percent

Profession of the respondent * Promotional Activity Kazo should Implement

100

100.0%

0.0%

100

100.0%

Profession of the respondent * Promotional Activity Kazo should Implement Crosstab

Promotional Activity Kazo s Point based

Newsletter-

Purchase-

Fashion

Discounts

Updates/Store Updates/Style Tips

Profession of the respondent

Count % within Profession of the Business

respondent % within Promotional Activity Kazo should Implement % of Total Count % within Profession of the

Student

respondent % within Promotional Activity Kazo should Implement % of Total Count % within Profession of the

Designer

respondent % within Promotional Activity Kazo should Implement % of Total Count % within Profession of the

Self Employed

respondent % within Promotional Activity Kazo should Implement % of Total Count % within Profession of the

others

respondent % within Promotional Activity Kazo should Implement % of Total

23.00

Count

37.5%

50.0%

8.6%

10.3%

3.0%

4.0%

40.6%

34.4%

74.3%

56.4%

26.0%

22.0%

20.0%

40.0%

5.7%

10.3%

2.0%

4.0%

0.0%

75.0%

0.0%

15.4%

0.0%

6.0%

44.4%

33.3%

11.4%

7.7%

4.0%

3.0%

% within Profession of the respondent % within Promotional Activity Kazo should Implement % of Total Count % within Profession of the respondent

Total

% within Promotional Activity Kazo should Implement % of Total

Chi-Square Tests Value

Asymp. Sig. (2sided)

Pearson Chi-Square Likelihood Ratio Linear-by-Linear Association N of Valid Cases

.164

17.992

.263

2.535

.111

20.217

100

a. 21 cells (87.5%) have expected count less than 5. The minimum expected count is .01.

CROSSTABS /TABLES=Income BY Reccomendations /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW COLUMN TOTAL /COUNT ROUND CELL.

Crosstabs

0.0%

35.0%

39.0%

100.0%

35.0%

39.0%

Notes Output Created

10-APR-2015 12:10:11

Comments C:\Users\HEWLETT Data

PACKARD\Desktop\Sem 2\Stats\stats work.sav

Input

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File Definition of Missing

100 User-defined missing values are treated as missing. Statistics for each table are

Missing Value Handling

based on all the cases with valid

Cases Used

data in the specified range(s) for all variables in each table. CROSSTABS /TABLES=Income BY Reccomendations /FORMAT=AVALUE TABLES

Syntax

/STATISTICS=CHISQ /CELLS=COUNT ROW COLUMN TOTAL /COUNT ROUND CELL.

Resources

Processor Time

00:00:00.03

Elapsed Time

00:00:00.03

Dimensions Requested

Cells Available

174762

[DataSet1] C:\Users\HEWLETT PACKARD\Desktop\Sem 2\Stats\stats work.sav

Case Processing Summary Cases Valid N

Missing Percent

Percent

Total N

Percent

Disposable monthly income * Promotional Activity Kazo

100

100.0%

0.0%

100

100.0%

should Implement

Disposable monthly income * Promotional Activity Kazo should Implement Cross

Promotional Activity Point based

Newslette

Purchase-

Fashion

Discounts

Updates/St

Updates/Style

Count % within Disposable monthly Below Rs. 5000

income % within Promotional Activity Kazo should Implement % of Total Count % within Disposable monthly

Rs 5000- Rs 15000

income % within Promotional Activity Kazo should Implement % of Total

Disposable monthly income

Count % within Disposable monthly Rs 15000- Rs 25000

income % within Promotional Activity Kazo should Implement % of Total Count % within Disposable monthly

Rs 25000-Rs35000

income % within Promotional Activity Kazo should Implement % of Total

Rs 35000-Rs45000

Count

3 33.3%

8.6%

3.0% 12 54.5%

34.3%

12.0% 9 34.6%

25.7%

9.0%

8 42.1%

22.9%

8.0%

% within Disposable monthly income % within Promotional Activity Kazo should Implement % of Total

income % within Promotional Activity Kazo should Implement % of Total

Chi-Square Tests Asymp. Sig. (2sided) Pearson Chi-Square Likelihood Ratio Linear-by-Linear Association N of Valid Cases

.050

23.821

.068

4.587

.032

25.021

100

a. 15 cells (62.5%) have expected count less than 5. The minimum expected count is .09.

18.2%

5.7%

% within Disposable monthly

2.0%

Count

Value

2.9%

% within Disposable monthly

Total

1.0%

Count

Above 45000

7.7%

35.0%

100.0%

35.0%