Management Dynamics Management Dynamics

Consumer behaviour study is an effort to comprehend the buying pattern of the final consumer. Consumer’s frequency of purchase and buying habits depict how sellers and marketers are promoting their product and luring customers time and again through their attractive sales promotion deals. Brain finds pleasure in the pursuit of inexpensive, and by tapping on the same idea, sellers are introducing repeat sales and low price deals along with added benefits to make their customers loyal towards them, thereby making the competition between physical and online retail store fierce day by day. This study examines the impact of influential determinants of consumer’s buying decision for clothes during sales with respect to various demographic variables. The comprehensive study analyzed factors that affect the purchase of apparels from physical and/or online retail store. The result also provides deeper insight into different forms of sales customers prefer while searching for the best deal. It helps in understanding consumer’s buying habits and making consumer’s experience economical and memorable. It is ideal for marketers and sellers to take into consideration the fact that demographic variables are the underlying determinants to cater to customers’ needs and wants, and in order to meticulously understand the habits of customers, it should be carefully administered to be able to let customers’ repeat their purchase of apparels from physical and/or online retail store.


INTRODUCTION
Ancient days account for men wearing leaves to cover themselves.The advent of clothes to cover up made way for the revolution in the garment industry.The existence of physical markets introduced words like 'bazaar', 'markets', shopping malls', etc.The brick and mortar industry has been the sole reason for the joy of shopping till now.With a quick shift into the living, buying and consumption standards of garments came the "shop from home" option.One can easily order garments while sitting at home, try them on being delivered, and then keep, return or exchange them.Behavioural differences, when known can help clothing retailers improve customer experiences when shopping between in-store purchases or online.Understanding the overall consumer consumption goals can help sellers-physical as well as online to effectively target promotional plans, design loyalty schemes and introduce new products that can cater to different consumption goals of various customers.
With the use of mobile and internet facility, more and more consumers engage in "showrooming" i.e. they look out for the clothes in a traditional brick and mortar store, but then search and purchase online for a lower price instead.Even though online cannot entirely replicate the experiences offered by the innate store purchase, online is constantly trying to come up with ways that make it easier for customers to engage in decision making.Overall, it is essential for firms to measure the incremental sales happening over the ones happened without any advertisement or sales promotion.While both retailers and e-tail firms are highly competing with their industry competitors, the competition among these two is no less.Both try to provide better deals and purchase experience, which can lure customers to initiate purchase.
Consumers often experience continuous pursuit of new clothes, which leads to an insatiable desire to want more clothes.Hence, they operate on a hedonic treadmill.Low costs also mean people can buy clothes they don't need without much deliberation.With such hedonic pleasure offered by fancy deals, price causes little competing pain.Such fancy deals are often tempting and highly irresistible.Retail stores are offering incredibly cheap clothes to consumers, making it easier to buy for them.Moreover there are frequent new deliveries to the stores, meaning customers have a variety to choose from.Famously known Zara stores have new deliveries every two weeks, whereas brands like H&M and Forever21 get clothes daily.They often price their products lower than the market, making it appear to the customer as an ideal bargain.
Shopping as a source of relaxation: Online purchase helps customer envision how clothes would look on them, use videos to customize and mix and match, and are eagerly responding to flash sales, discounts and coupon offers whereas physical retailers offer off season sales at the store, expert advice on fabric, attire complementing the personality, mix and match, etc.Such competition is giving the customer enough space to make the right choice for himself, and pick the deal that suits his pocket.It is eliminating shopping blues of the customer, and enhancing his overall purchase experience.Recently, shopping has become a source to find solution to problems, a tool to fill the void.Clothes that one searches for, compares and buys helps one imagine oneself as powerful, strong, beautiful and confident.The personality gets a high-kick when one is psychologically satisfied to have bought a popular and expensive brand's cloth at a great discount.

Men vs Women:
It is expected that a woman's buying patterns are contradictory to that of men's.Women may step in the store, and closely observe, while men may hunt for their particular aisle.Their habits define their age old practices of women being gatherers and men being hunters.Women look for more interaction, best deals, good experience when they shop, while men often focus on essential organized retail penetration at 19 per cent as of 2014.
Selling is prominently about service.The average Indian consumer who shops online chooses to because of "increasing time-poverty, changing lifestyle, convenience, flexibility of shopping and option of free home delivery," according to the Technopak paper.Retailers often use data collected to understand the effect of promotions on their total sales over a period of time.Top Indian online retailers are currently competing to increment and hold their clients, notwithstanding the customary reliability programs.Except from the standard reliability programs, fabulous client administration, uncommon rebates, focused on promoting and bulletins, free delivery, scheduled delivery and membership based administrations, these portals are hauling out all stops to make exceptionally imaginative advertising techniques to draw in with clients at a non-value-based level -to motivate them to spend increasingly and spend frequently.Experienced e-trade mammoths like Flipkart-Myntra and Jabong are combating it out for mind share of the upper-middle class section while Snapdeal and Limeroad focus on a tasteful niche market.Amazon is shaking things up by furthermore scaling up their style offerings, subsequently making it an intriguing space to keep an eye out for.Blackwell and Hiliker (1978) conducted to find out the processes and variables involved in purchasing of clothes by women.The data was found out by observing discussions across various focus group interviews.A decision process approach was used to analyze ten focused group interviews conducted in varied geographic and demographic populations.An essential objective of the study involved understanding conceptions of fashion and the necessity of relationship between such conceptions and clothing purchases to predict the future trends that may occur in fashion conceptions and clothing purchases.Analysts of the focus group interview used Engel-Kollat-Blackwell model to come up with various variables that are essential in purchase decisions for different clothes.Vyas(2007) quotes that Indian organized retail industry is poised for growth.The Indian economy, in alignment with the globalized markets, hold great opportunity for the apparel sector.With a massive use of sales promotions, that are constantly luring the customers, it becomes essential for managers to understand opportunities and threats.The study delves into sales promotion programs of six apparel stores in Ahmedabad market.It provides major findings and insights on consumer's behavior.Lifestyle, for instance, has a loyalty program called `The Inner Circle', Pantaloons offers a `Green Card' Rewards program and Westside has `Club West' to woo the customers.Based on the study by the author, sales promotion has a direct impact on the consumer's action process whereas too frequent and all time available sales promotion may make the consumer question about the brand, and gradually make them indifferent.Also a proper coordination of selling effort is required.

LITERATURE REVIEW
Vikkraman and Sumathi (2012) studied the behavior of the consumer towards international and local brand in the apparel industry by studying self-concept, need for uniqueness, clothing interest, perceived quality, emotional value and purchase intention.Based on their findings, the researchers concluded that emotional value and clothing interest play a significant role in purchase intentions of the customer whereas the high price of global brands and patriotism towards the country are some factors that play an anti-purchase role.Makers should focus on uniqueness to boost sales.Agarwal(2012) endeavors to break down the components identified with the shopping conduct of online customers.Shopper's shopping conduct in appreciation of web shopping was considered utilizing distinctive financial variables.The aftereffects of study uncover that internet shopping in India is fundamentally influenced by different demographic elements like age, sexual orientation, instruction and salary.Further it additionally helps retailers to comprehend the drivers of buyer's demeanor and objective to shop on the web and purchaser's observations with respect to convenience and handiness.The results of the study propose that evaluation of customer's shopping conduct can add to a superior comprehension of buyer shopping conduct in admiration of web shopping.Sharma (2013) quotes that her objectives were to study the changing buying patterns, growth of online shopping and e-commerce, factors that define the success of online shopping, and how to improve the website appeal to attract customers.The conclusion of the study stated that there were major purchase decisions undertaken by people aged between 21 and 30, the online websites are mostly visited by females, clothes and accessories are most frequently purchased online, and customers prefer cash-ondelivery over other payment options.Nagadevara(2011) states that a key and major feature of online sites is the personal interface and ease in purchase and navigation.A standout amongst the most encouraging potential advantages of such personalization is that it permits forthcoming purchasers to screen expansive arrangements of items productively and adequately (Alba et al. 1997). Haubl et al. (2004) talked about experiences identifying with various types of personalization, especially instruments that create item proposals in light of customer inclinations and apparatuses that encourage one next to the other correlations of items.They have utilized information gathered from around 2000 study members from an exploration program that has been completed with the backing of the Institute for Online Consumer Studies (IOCS).This study has demonstrated that personalization has enormous effect on both purchasers and merchants.Research on internet purchasing conduct has demonstrated that, after some time, online customers can develop to be exceptionally steadfast customers (Brynjolfsson and Smith 2000;Johnson, Bellman and Lohse, 2003).This happens in light of the fact that, it is anything but difficult to explore starting with one web merchant then onto the next, purchasers like to shop utilizing interfaces that they are knowledgeable about.Consequently, giving customized shopping interfaces can prompt higher unwaveringness of the clients.
The objectives of the study were to study two different apparel brands, owned by the same group.Each brand had its own physical as well as online retail outlet.Customer profiles across both the brands was studied along with the difference in the two sets of customer profiles, customer's buying behavior and reaction towards these brands, and similarities and differences in buying behavior of customers.This study used K-means clustering for understanding the customer segments.It used web diagrams for identifying purchasing patterns.Based on cluster analysis, differences in customer segments are highlighted.Differences in purchase patterns are recognized by using link analysis based on the web diagrams created individually for the two distinct types of stores.A GfK study on thereasoning and attitudes of Europeans and Americans when buying clothes and accessories ( 2006) providesa fruitful insight into consumer's buying habits.It was concluded that four out of five Europeans and Americans bought clothes because they needed them, whereas three out of four bought clothes if good deals were offered on them.Countries of origin and fashion aspects were less pressing issues.The most common reason to purchase clothes was obviously necessity, followed by the second most favourite reason, of getting a good chance to bargain, as stated by three quarters of the respondents.In Western Europe, cut price clothes and accessories were quite popular with Germans, whereas Bulgarians were not too attracted by these.The third most popular reason was the pleasure derived on buying new clothes, followed by product's country of manufacture.Fifth reason seemed to be impulse buying, especially prevalent among Austrians and Germans.The last reason in the list was that of latest trends falling down.

Monthly Income
Table 1.3 (Appx.)shows that respondents with 2000-5000 income range limit their purchase by being a Need-Based customer.Respondents with income range 5000-15000 range are mostly loyalcustomers, whereas respondents with income ranges 15000-30000 and 30000 & above are Need-Based customers, thereby having intentions to purchase apparels only at the time of urgency.
Ho: Monthly Income is related to the kind of customer H1: Monthly Income is not related to the kind of customer P-value: 0.176877, F value: 1.940928, F critical: 3.490295.F< Fcritical, hence Ho is accepted, i.e.Monthly Income has a relation to the kind of customer.
The respondents were asked where did they shop frequently, and based on their responses, the data was divided into 3 types of population • Physical Store: These kind of respondents (73/158) shopped their apparels solely from physical retail outlets.
• Online Store: The respondents (7/158) purchased their apparels solely from online retail stores.
• Both: The respondents (78/158) purchased their apparels from both physical retail outlets and online retail store.
From where do customers shop frequently?
Based on the responses received, the following data analysis took place for 3 different kinds of populations.For Physical Retail Stores and Both, Data Analysis is done based on their dependence on Independent Variables (Age, Gender, and Monthly Income)

Monthly Income
Table 2.3 (Appx.)shows that all the income groups prefer purchasing from physical retail outlets due to the assurance of quality guaranteed while purchasing the clothes.
Ho: Monthly Income is related to the factors affecting purchase decisions of apparels H1: Monthly Income is not related to the factors affecting purchase decisions of apparels P value: 0.627476, F value: 0.599574, F critical: 3.490295.F < F critical, hence Ho is accepted, i.e.Monthly Income is related to the factors affecting purchase decisions of apparels from physical retail stores.

Age
According to Ho: Age is related to preference of kind of sale H1: Age is not related to preference of kind of sale P-value: 0.014337, F value: 5.345248, F critical: 3.490295.F> F critical, hence Ho is rejected, i.e. age is not related to the kind of sale one opts for while purchasing clothes from physical retail stores.

Gender
In Table 5.2 (Appx.),both males and females prefer end of season sale, as they seem to get hefty discounts and good clothes at great prices during the season end.Second most popular sale for both males and females is the Festive season sale.
Ho: Gender is related to the preference of kind of sale H1: Gender is not related to the preference of kind of sale P-value: 0.440376, F value: 0.682369, F critical: 5.987378.F< F critical, hence Ho is accepted, i.e.Gender is related to the kind of sale customer opts for while purchasing clothes from physical retail stores.

Monthly Income
In Table 5.3 (Appx.),all income ranges prefer End of season sale as they get decent clothes at great prices at the end of the season.Income range 2000-5000's second most preferred sale is the sale throughout the year.Some stores keep a sale and offer hefty discounts on attires throughout the year, no matter what.They can go and purchase attires at any time during the year, thereby having ease and having to pay low at any time of the year.Income range 5000-15000, 15000-30000 and 30000 & above, all have their second most preferred sale as the Festive season sale.Festive time discounts help these customers get the necessary festive based attires at a low price.
Ho: Monthly Income is related to the kind of sale H1: Monthly Income is not related to the kind of sale P-value: 0.227961, F value: 1.660767, F critical: 3.490295.F< F critical, hence Ho is accepted, i.e.Monthly Income is related to the kind of sale customer is attracted to while purchasing clothes from the physical retail stores.
Understanding consumer's behavior towards issues while purchasing clothes from physical retail stores For this purpose, a few issues were stated, and consumers were asked to rate them on a scale of 1 to 5, with 1 being Not important and 5 being Most important.For computation of responses, weighted mean average was applied to read the response of the average population.
The following weights were applied: Not Important: 1, Slightly Important: 2, Moderately Important: 3, Important: 4, Very Important: 5 (N= 73) Table 6.1 (Appx.)states the ratings given by the customer to various issues they consider essential before purchasing the clothes from physical stores.
Ability to try clothes on: Table 6.2 (Appx) states the weighted average as 4.0411, thereby stating that the population considers the ability to try clothes on in a physical retail store an important issue that helps them choose physical stores for shopping.
Waiting in long queues to try clothes on: Table 6.3(Appx.)states average as 2.9452, thereby stating that for the average population waiting in long queues to try clothes on during sale period from physical retail stores is slightly to moderately important an issue.
Waiting in long queues to make payment: Table 6.4 (Appx.)states that the population with an average of 3.0548 is moderately concerned about waiting in long queues to make payment while purchasing clothes from physical stores during sale.
Cleanliness of the store: Table 6.5 (Appx.), with an average of 3.4384, the population largely feels it to be a moderately important issue to consider the cleanliness of the store while purchasing clothes from the physical retail stores during sale.
Crowded atmosphere: In Table 6.6 (Appx.), with an average of 3.178, the population finds crowded atmosphere a moderately important issue while purchasing clothes from physical retail stores.
Interaction with the salesman before purchasing: In Table 6.7 (Appx.),mean is 3.137, the population finds interaction with salesman a moderately important issue while purchasing clothes from physical retail stores during sales.
Fitting room environment: In Table 6.8 (Appx,), average is 3.247, majority population believes that fitting room environment is a moderately important issue while purchasing clothes from physical retail stores during sale.

Online Store
Based on the total number of responses, the respondents were asked to select from where they shop their clothes the most; only 7 out of 158 opted for online store.
Majority respondent (4) purchased from Myntra, 1bought from Jabong, and 2 of them from other online stores.The most striking reason for them to purchase apparels online was frequent sales and discounts offered, followed by the option of wide variety, and then free home delivery and the comfort of sitting at home and shopping.The avid online customers purchase apparels online during sale just Volume 16, Number 1 (2016) "sometimes", whereas the remaining prefer to purchase online depending on their preferred brand availability online.The sale attributes that seem to attract customers while purchasing clothes online are percentage discounts, followed by free shipping, and then loyalty discounts.The kind of sale on apparels on online stores that convince customers to check them out and initiate purchase are the "Special Sales (e.g.: Amazon's Great Indian Sale, Flipkart's Big Billion Days)", followed by clearance sale, end of season sale and festive season sale.
During the 'Special Sales'at various Online stores, customers are able to find and purchase clothes they like only sometimes.During online sales, customers don't look for specific products that they want; instead they purchase anything that they like and is discounted.'00Xleft in stock' appearing online while customers stroll during purchasing clothes does not convince customers to initiate purchase immediately.

Both
The respondents here (78/158) shop their clothes from both physical retail stores and online stores.The respondents had to answer questions for both physical retail store shopping as well as online retail shopping.

BOTH: Physical N= 78
Factors affecting purchase decision from physical retail store Age Table 7.1 (Appx.)shows that age group 18-25, 26-35 and 36-45, all opt for quality assurance as an essential factor affecting their purchase of clothes from physical retail stores.Age group 46 & above choose ease to try as a justifiable factor affecting their purchase from physical stores.
Ho: Age is related to factors affecting the purchase decision H1: Age is not related to factors affecting the purchase decision P-value: 0.005289, F value: 7.117117, F critical: 3.490295.F> F critical, hence Ho is rejected, i.e.Age is not related to the factors affecting the purchase decision of the consumer from the physical retail store.

Gender
In Table 7.2 (Appx.),both males and females prefer quality assurance as the most striking reason to affect their purchase of clothes from physical retail stores.
Ho: Gender is related to factors affecting purchase of clothes H1: Gender is not related to factors affecting purchase of clothes P-value: 0.704624, F value: 0.158155, F critical: 5.987378.F< F critical, hence Ho is accepted, i.e.Gender is related to factors affecting purchase of clothes from physical retail stores.

Monthly Income
In table 7.3 (Appx.),Income group 2000-5000 consider ease to try as a factor affecting their purchase decision.Age group 5000-15000 and 15000-30000 prefer quality assurance as a factor affecting their purchase decision, whereas income group 30000 & above prefers more variety and range as a striking

Gender
In Table 8.2 (Appx.),both males and females prefer to shop for clothes just once during sale from physical retail stores.
Ho: Gender is related to frequency of shopping apparels from physical stores H1: Gender is not related to frequency of shopping apparels from physical stores P-value: 0.697014, F value: 0.166957, F critical: 5.987378.F< F critical, hence Ho is accepted, i.e.Gender is related to frequency of purchasing clothes from physical retail stores.

Monthly Income
In Table 8.3 (Appx.),income range 2000-5000 usually shop 2-3 times during sale, whereas income range 5000-15000 shops Once or 2-3 times, based on equal response by the respondents.Income range 15000-30000 also shop 2-3 times or once based on equal responses.Range 30000 & above usually shop just once for their clothes during sale.
Ho: Monthly Income is related to frequency of shopping apparels from physical stores H1: Monthly Income is not related to frequency of shopping apparels from physical stores P-value: 0.199875, F value: 1.804878, F critical: 3.490295.F< F critical, hence Ho is accepted, i.e.Monthly Income is related to frequency of buying clothes from physical retail clothes.

Sale Attributes Age
In

Gender
In Table 9.2 (Appx.),both males and females prefer percentage discounts while purchasing clothes from physical retail stores.
Ho: Gender is related to sale attribute that attracts customer H1: Gender is not related to sale attribute that attracts customer P-value: 0.827047, F value: 0.052089, F critical: 5.987378.F< F critical, hence Ho is accepted, i.e.Gender is related to sale attribute that attracts customer to purchase clothes from physical stores.

Monthly Income
In Table 9.3(Appx.),all income ranges have a preference towards percentage discounts that attract them to purchase clothes from physical retail stores.
Ho: Monthly Income is related to sale attributes that attracts customers H1: Monthly Income is not related to sale attributes that attracts customers P-value: 0.679623, F value: 0.515081, F critical: 3.490295.F< F critical, hence Ho is accepted, i.e.Monthly Income is related to sale attributes that attract customers to buy clothes from physical retail outlets.

Age
In

Gender
In Table 10.2 (Appx.),both males and females prefer end of season sale, which convinces them to purchase clothes from physical retail stores.
Ho: Gender is related to kind of sale customer prefers H1: Gender is not related to kind of sale customer prefers P-value: 0.698972, F value: 0.164666, F critical: 5.987378.F< F critical, hence Ho is accepted, i.e.Gender is related to kind of sale customers prefers to shop from while purchasing clothes from physical retail stores.

Monthly Income
Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 ( 2016) In Table 10.3 (Appx.),income range 2000-5000 and 15000-30000 prefer end of season sale, whereas income range 5000-15000 have equal responses for end of season sale and festive season sale, and so does income range 30000 & above.
Ho: Monthly Income is related to kind of sale customer prefers H1: Monthly Income is not related to kind of sale customer prefers P-value: 0.153557, F value: 2.100946, F critical: 3.490295.F< F critical, therefore Ho is accepted, i.e.Monthly Income is related to kind of sale customer prefers while purchasing clothes from physical retail stores.

Understanding consumer's behavior towards issues while purchasing clothes from physical retail stores (Both)
For this purpose, a few issues were stated, and consumers were asked to rate them on a scale of 1 to 5, with 1 being Not important and 5 being Most important.For computation of responses, weighted mean average was applied to read the response of the average population.
Table 11.1 (Appx.)states the ratings given by the customer to various issues they consider essential before purchasing the clothes from physical stores (Both).
Ability to try clothes on: Table 11.2 (Appx.),states the average as 3.846, thereby explaining that the population finds ability to try clothes on a moderately important issue while buying clothes from physical retail store.
Waiting in long queues to try clothes: In table 11.3 (Appx.),calculated average is 2.948 thereby stating that the population finds waiting in long queues to try clothes on while purchasing from physical stores a slightly important issue.
Waiting in long queues to make payment: In table 11.4 (Appx.) the calculated weighted average mean is 3, meaning that the population finds waiting in queue while purchasing clothes at a store a moderately important issue.
Cleanliness of the store: In table 11.5 (Appx.), the computed weighted average mean is 3.589, thereby stating that population finds cleanliness issue a moderately important one while purchasing clothes from the store.
Crowded Atmosphere: In table 11.6 (Appx.),weighted average is 3.179, meaning that population finds crowded atmosphere while purchasing clothes from a store a moderately important issue.
Interaction with the Salesman: In table 11.7 (Appx.), the computed weighted average is 2.717, and hence population finds interaction with the salesman a slightly important issue while purchasing clothes from the store.
Fitting room environment: In table 11.8 (Appx.),computed weighted average is 2.935, and hence population finds fitting room environment a slightly important issue while purchasing clothes during sale from the store.

BOTH
The respondents here (78/158) shop their clothes from both physical retail stores and online stores.The respondents had to answer questions for both physical retail store shopping as well as online retail shopping.

BOTH :Online N= 78
From where do you purchase apparels online Maximum respondents shop for apparels from Myntra, followed by Amazon, then Jabong and then Flipkart.The least favourite ones are Koovs and Snapdeal.

Age
In Table 12.1 (Appx.),age 18-25 and 46& above consider the comfort of sitting home and shopping a major reason to purchase online.Age 26-35 find a huge variety at one place and the ability to sit at home and shop the major reasons.Age group 36-45 find free return policy as a satisfying reason for them to purchase online.
Ho: Age is related to reasons for buying online H1: Age is not related to reasons for buying online P-value: 0.001547, F value: 8.219993, F critical: 3.238872.F> F critical, hence Ho is rejected, i.e.Age is not related to reason for buying clothes online.

Gender
In Table 12.2 (Appx.),both males and females prefer sitting at home and shopping the most viable reason to shop clothes online.
Ho: Gender is related to reasons for buying online H1: Gender is not related to reasons for buying online P-value: 0.637254, F value: 0.24015, F critical: 5.317655.F< F critical, hence Ho is accepted, i.e.Gender is related to reasons for buying clothes online.

Monthly Income
In Table 12.3 (Appx.),income ranges 2000-5000, 5000-15000 and 30000 & above state their reason to shop online as the comfort to sit at home and shop.Income range 15000-30000 state their reasons as lot of variety at one place and free return policy to purchase clothes online.
Ho: Monthly Income is related to reason for shopping online H1: Monthly Income is not related to reason for shopping online P-value: 0.184177, F value: 1.819672, F critical: 3.238872.F< F critical, hence Ho is accepted, i.e.Monthly Income is related to the reason for shopping clothes online.

Age
In P-value: 0.037053, F value: 3.902611, F critical: 3.490295.F> F critical, hence Ho is rejected, i.e.Age is not related to frequency of purchase of clothes online.

Gender
In Table 13.2 (Appx.),both males and females purchase clothes sometimes during the sale from online stores.
Ho: Gender is related to frequency of purchasing clothes online H1: Gender is not related to frequency of purchasing clothes online P-value: 0.776349, F value: 0.088316, F critical: 5.987378.F< F critical, hence Ho is accepted, i.e.
Gender is related to frequency of purchasing clothes online.

Monthly Income
Table 13.3 (Appx.)states that income range 2000-5000, 5000-15000 and 30000 & above purchase clothes sometimes online during the sale, whereas income group 15000-30000 purchase only depending on the availability of their preferred brand online.
Ho: Monthly Income is related to the frequency of purchasing clothes online H1: Monthly Income is not related to the frequency of purchasing clothes online P-value: 0.478890426, F value: 0.879788639, F critical: 3.490294819.F< F critical, hence Ho is accepted, i.e.Monthly Income is related to the frequency of purchasing clothes online.

Age
Table 14.1 (Appx.)states that all the age groups have a preference towards percentage discounts offered online during sale while purchasing clothes.
Ho: Age is related to sale attributes while purchasing online H1: Age is not related to sale attributes while purchasing online P-value: 0.064331, F value: 2.705669, F critical: 2.946685.F< F critical, therefore Ho is accepted, i.e.Age is related to sale attributes one has preference towards while purchasing clothes online during sales.

Gender
In Table 14.2 (Appx.),both males and females get attracted by percentage discounts while purchasing clothes online.
Ho: Gender is related to sale attributes while purchasing online H1: Gender is not related to sale attributes while purchasing online P-value: 0.801362, F value: 0.06574699, F critical: 4.60011.F< F critical, hence Ho is accepted, i.e.Gender is related to preference towards sale attributes while purchasing clothes online.

Monthly Income
Based on Table 14.3 (Appx.),all income groups get attracted to percentage discounts while purchasing clothes online.Ho: Monthly Income is related to sale attributes while purchasing online H1: Monthly Income is not related to sale attributes while purchasing online P-value: 0.549, F value: 0.71911152, F critical: 2.946685.F< F critical, hence Ho is accepted, i.e.Monthly Income is related to sale attributes that attract customer while purchasing clothes online.

Age
In Table 15.1 (Appx.),age groups 18-25, 26-35 and 36-45 get attracted to special sales online while buying clothes, which helps them get great deals and offers.
Ho: Age is related to kind of sale online while purchasing clothes H1: Age is not related to kind of sale online while purchasing clothes P-value: 0.001507, F value: 8.26606976, F critical: 3.238872.F> F critical, hence Ho is rejected, i.e.Age is not related to the kind of sales that attract customer while purchasing clothes online.

Gender
In Table 15.2 (Appx.),both males and females get attracted to special sales online while purchasing clothes, as they offer better deals and variety at a discounted price.
Ho: Gender is related to kind of sale while purchasing clothes online H1: Gender is not related to kind of sale while purchasing clothes online P-value: 0.677615, F: 0.186047, F critical: 5.317655.F< F critical, hence Ho is accepted, i.e.Gender is related to kind of sale customer is attracted to for purchasing clothes online.

Monthly Income
In Table 15.3 (Appx.),all income groups get attracted to special sales for purchasing clothes online, as they offer variety and great deals at reduced prices.
Ho: Monthly Income is related to kind of sale while purchasing clothes online H1: Monthly Income is not related to kind of sale while purchasing clothes online P-value: 0.137261, F value: 2.12440191, F critical: 3.238872.F< F critical, hence Ho is accepted, i.e.Monthly Income is related to kind of sales customers are attracted to while purchasing clothes online.
During the 'Special Sales' at various online stores, customers manage to find and purchase clothes they like, just at times.
Based on responses received, mostly customers purchase just about anything that they like and is discounted during sale at online retail store.
Majority of the respondents initiate immediate action at times when they see '00X left in stock' while purchasing clothes online.

Understanding consumer's behavior towards issues while purchasing clothes from online retail stores (Both)
For this purpose, a few issues were stated, and consumers were asked to rate them on a scale of 1 to 5, with 1 being Not important and 5 being Most important.For computation of responses, weighted mean average was applied to read the response of the average population.
Table 16.1 (Appx.)states the ratings given by the customer to various issues they consider essential before purchasing the clothes from online stores (Both).N= 78 Site traffic: Table 16.2 (Appx.)states the computed weighted average mean as 2.884; hence majority of the population finds this just a slightly important issue.
Free delivery and returns: Table 16.3(Appx.)states the computed weighted average as 3.794, stating that average population finds free delivery and returns a moderately important issue while purchasing clothes online.
Product suggestion and feedback: Table 16.4 (Appx.)states the computed weighted average as 3.423, stating that average population finds Product suggestions and feedback moderately important issue while purchasing clothes online during sale.
Special added discount: Table 16.5 (Appx.)states the computed average as 3.538 stating that average population finds special added discounts a moderately important issue.

Mode of payment:
In table 16.6 (Appx.)computed average is 3.8333 stating that the population finds mode of payment while purchasing clothes online a moderately important issue.

00X left in stock:
In Table 16.7 (Appx.)computed average is 2.474 stating that population finds '00X' left in stock a slightly important issue while purchasing clothes online.

Frequency of sales:
In Table 16.8(Appx.),the computed average mean is 2.923 stating that average population finds frequency of sales at online portals a slightly important issue.

HYPOTHESIS (Ho)
Age directly related to the kind of customer Based on tests conducted to prove the hypothesis, Age is not related to the buying behavior of consumer.Age is has no relation to the kind of customer, frequency of shopping, factors affecting purchase decision, frequency and reasons to shop online or at physical retail stores.Hypothesis was rejected in case of all dependent variables' relation to the independent variable: Age.
Gender and Income are related to the buying behavior of the customer.The average population finds issues such as frequency of sale online or at physical retail stores moderately important.Other factors such as ability to try clothes on, special discounts, quality assurance, comfort, etc. are more pressing and important issues while making the decision to purchase clothes online or at physical retail stores.Hypothesis was accepted in case of all dependent variables' relation to the independent variable: Gender and Monthly Income.
The analysis provides a deeper insight into 'Special Sales' that customers prefer while purchasing clothes online.Online sites while competing with the physical retail outlets, have been providing added discounts time and again to the customers, as well as rewarding customers for their loyalty towards them.Whereas physical stores focus on providing clearance sales to sell their clothes at dirt cheap prices.Most of the population prefers buying from both physical and retail stores.Anything that provides a better deal to them.Meanwhile customers who purchase from physical stores solely, rate loyalty discounts as important, especially Age group 36-45 and 45 & above.They get quality assurance from where they buy, and don't have enough willingness to shift their buying preference online.
Customers who buy from both physical and online stores don't regard loyalty as supreme as they opt for any medium which provides their desired material at the lowest price.They believe in saving penny at every step, and hence may resort to any medium, brand, stores within physical or online medium that helps them save a buck.

CONCLUSION
After conducting an in-depth consumer analysis for buying apparels during sale, we can conclude that the idea of shopping clothes during sale has become a habit for customers over the past few years, thus providing marketers a potential opportunity to experiment and reach out to customers with great deals and discounts.Customers don't just limit their purchase to physical retail stores, but also purchase from online stores, thanks to varied special discounts, offers, deals and sales available time and again at online stores.The idea of purchasing with the comfort of sitting at home, with free delivery, easy return and exchange policies and much more by mere touch of a button is making customer bend towards online shopping gradually.But a certain percentage of population still resorts to physical purchase due to major assurance of good quality there.
Seeing the data generated by the survey and hypothesis conducted, it could be clearly seen that purchasing for clothes has evolved on many fronts.Firstly and most significant change has been the change in the mindset and perception towards buying online.Customers indulge in showrooming, i.e. look for the product at both physical and online store, and buy it from whichever medium that provides a better and cheap deal.The twin C associated with online purchase: comfort and convenience is a strong tool that marketers are encashing upon to increase their online customer base.Wide variety, appealing online portals, frequent attractive sales and offers are luring customers towards online purchase.This change can be mainly attributed to an effective use of data analytics by marketers which help them customize their offerings based on consumer's needs.
Secondly, consumers aren't letting age get into their decision to purchase clothes.Age is merely a number now, as based on the tests conducted, the hypothesis rejected states that age is not related to what kind of a customer one is, the kind of sale, factors or frequency of shopping, or reasons to consider while purchasing clothes from physical or retail stores.
By changing the attitudes and behaviours of customers, sales promotion techniques motivate customers to initiate an immediate action of purchase, and have a psychological satisfaction of being the lucky one to get a special deal.To compete with the physical retail stores, the 'Special sales' conducted by online stores (Amazon's Great Indian sale, Flipkart's-Big Billion Days) woo the customers right under the physical retail store's noses.Consumers get special discounts (hourly, midnight, threshold purchase discounts) that motivate them to purchase online.Customers are willing to do anything to save their pockets.After all, no one wants to spend unnecessarily.Even though purchase of appliance, gadgets and other products online has increased multifold over past few years, the purchase of clothes online is an emerging trend.Such factors and mediums are evolving the shopping process, and empowering consumers.After all, customer is the king.

SCOPE FOR FUTURE RESEARCH
Internet shopping is expanding day by day, and retail stores are doing everything to retain customers.Sales promotion techniques are the road to achievement for both the mediums.There is a wide scope for future research by comparing which among the two (physical or online stores) provides more satisfaction in purchase of clothes to the customer, conducting concentrated research on why customers are hesitant in purchasing from only online stores and understanding why certain customers opt for non-sale period, fresh additions of clothes, and not wait for sale period.

LIMITATIONS
The data collected did not take 50+ aged population into deep consideration due to their limited exposure to online sites and/or purchase through retail outlets.Also, certain proportion of the population may have been aware but also skeptical in providing true and exact data.Some may have given inaccurate data in order to appear socially responsible while shopping apparels, which may skew the results.Further, the research does not highlight onto effects of dependent variables on independent variables in online store purchases because of few responses and preference towards buying garments solely from online stores.The research focuses on few types of sales promotion technique (discounts, i.e. sale) and ignores other sales promotion that may ignite purchase of the apparels.

APPENDIX
What kind of a customer are you?• During the sale period, how frequently do you go and shop?Table 3   • Which sale attributes at the clothes retail store attract you? • Which kinds of sales at the store convince you to visit them and initiate purchase action?• Which sale attributes at the clothes retail store attract you? • Which kinds of sales at the store convince you to visit them and initiate purchase action?• Which among the following is the most striking reason for you to purchase apparels Online?• How frequently do you purchase clothes online during sale?• Which sale attributes while purchasing clothes Online seem to attract you the most?• Which kind of sales on clothes at online stores convince you to check them out and initiate purchase?

Table 1 .
1 (Appx.)shows that age group 18-25 are mostly need-based customers, as they only buy when there is an urgency.Age-group 26-35 are impulse and need-based customers, as they buy clothes based on whatever they like when they go for a visit, and/or based on urgency.Age group 36-45 tends to be loyal customers as they buy from the same place always and 46 & above age group tends to be wandering customers as they have no specific desire to shop, they just go to have an experience.
Paul and Hogan (2015)state factors evolving shopping process and empowering customers.The factors are further divided into three R's namely Research, Recommendations and Returns.In 2014, a Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 (2016) Gender Table 1.2 (Appx.)shows that both males and females are mostly Need-Based customers, i.e. the intention to buy apparels is based on urgency of requirement.Ho: Gender has a direct relation to the kind of customer H1: Gender does not have a direct relation to the kind of customer P-value: 0.467146, F value: 0.582759, F critical: 5.317655.F< Fcritical, hence Ho is accepted, i.e.Gender has a direct relation to the kind of customer.

Table 3
Ho is accepted, i.e.Monthly Income is related to sales attributes while purchasing clothes from physical retail stores.

Table 5
.1 (Appx.)shows that age group 18-25 prefer End of season sale, as they seem to get hefty discounts then, whereas age group 26-35 are equally inclined towards clearance sale and festive season sale.Age group 36-45 opts for clearance sale, as they tend to get decent clothes at great discounts then, whereas age group 46 & above prefers Festive season sale, for they get good attires based on the festive demands at low prices.

Table 9
H1: Age is not related to sale attribute that attracts customer P-value: 0.206374, F value: 1.7696, F critical: 3.490295.F< F critical, hence Ho is accepted, i.e.Age is related to sale attribute that attracts customer to purchase clothes from physical retail stores.
.1 (Appx.),age group 18-25 and 46 & above get attracted by Percentage discounts to purchase clothes.Age group 36-45 get attracted by Loyalty discounts, whereas group 26-35 have an equal bent towards loyalty discounts and percentage discounts.Ho: Age is related to sale attribute that attracts customer Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 (2016)

Table 10
.1 (Appx.),age18-25 prefer end of season sale, whereas age 26-35 prefer clearance sale or festive season sale.Age group 36-45 prefer end of season sale.Ho: Age is related to kind of sale customer prefers H1: Age is not related to kind of sale customer prefers P-value: 0.003911, F value: 7.712692, F critical: 3.490295.F> F critical, hence Ho is rejected, i.e. age is not related to the kind of sale customer prefers.
Ho: Age is related to frequency of purchase of clothes online H1: Age is not related to frequency of purchase of clothes online Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 (2016)

Table 1 . 1 :
Tabular representation of age and kind of customer

Table 1 . 2 :
Tabular representation of gender and kind of customer.

Table 1 . 3 :
Tabular representation of monthly income and kind of customer.

Which among the following factors is the most striking one for you to purchase apparels from physical stores?
Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 (2016)

Table 2 . 2 :
Tabular representation of gender and factors affecting purchase decisions of apparels at physical retail stores

Table 2 . 3 :
Tabular representation of monthly income and factors affecting purchase decision of apparel from physical retail stores

.1: Tabular
representation of age and frequency of shopping apparels during sale from physical retail stores

Table 3 . 3 :
Tabular representation of monthly income and frequency of shopping apparels during sale period from physical retail stores

Table 4 . 1 :
Tabular representation of age and sale attributes that attract customers to buy from physical retail stores

Table 4 . 3 :
Tabular representation of monthly income and sale attributes that attract customers to purchase clothes from physical retail stores Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 (2016)

Table 5 . 1 :
Tabular representation of age and kind of sale that attracts customers to purchase clothes from physical retail store

Table 5 . 2 :
Tabular representation of gender and kind of sale that attract customer to initiate purchase action

Table 5 . 3 :
Tabular representation of monthly income and kind of sale customers opt for while purchasing clothes from physical retail stores

Table 6 . 2 :
Ability to try clothes on

Table 6 . 3 :
Waiting in long queues to try clothes on

Table 6 .4:
Waiting in long queues to make payment

Table 6 . 5 :
Cleanliness of the store

Table 6 .7:
Interaction with the salesman before purchasing

Table 7 . 1 :
Tabular representation of age and factors affecting purchase of clothes from physical stores.

Table 7 . 2 :
Tabular representation of gender and factors affecting purchase of clothes from physical retail stores.

Table 7 . 3 :
Tabular representation of monthly income and factors affecting purchase of clothes from physical stores.

Table 9 . 1 :
Tabular representation of age and sale attributes that attract customers to buy from physical retail stores

Table 9 . 3 :
Tabular representation of gender and sale attributes that attract customers to buy from physical retail stores

Table 10 . 1 :
Tabular representation of age and kind of sale that attracts customers to purchase clothes from the physical retail store

Which kind of sales at the stores convince you to visit them and initiate purchase action?
Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 (2016)

Table 10 . 2 :
Tabular representation of gender and kind of sale that attracts customers to purchase clothes from the physical retail store

Table 10 . 3 :
Tabular representation of monthly income and kind of sale that attracts customers to purchase clothes from the physical retail store

Table 11 . 3 :
Waiting in long queues to try clothes

Table 11 . 7 :
Interaction with the Salesman

Table 12 .1:
Tabular representation of age and reason to purchase clothes online

Table 12 . 2 :
Tabular representation of gender and reasons to purchase clothes online Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 (2016)

Table 12 . 3 :
Tabular representation of monthly income and reasons to purchase clothes online

Table 13 . 1 :
Tabular representation of age and frequency of purchasing clothes online during sale

Table 13 . 2 :
Tabular representation of gender and frequency of purchasing clothes online during sale.

Table 13 . 3 :
Tabular representation of monthly income and frequency of purchasing clothes online during sale Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 (2016)

Table 14 . 1 :
Tabular representation of age and sale attributes that convince customer to purchase online

Table 14 . 2 :
Tabular representation of gender and sale attributes that convince customer to purchase online

Table 14 . 3 :
Tabular representation of monthly income and sale attributes that convince customer to purchase online

Which sale attributes while purchasing clothes Online seem to attract you the most?
Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 (2016)

Table 15 . 1 :
Tabular representation of age and sale attributes that convince customer to purchase online Which

Table 15 . 2 :
Tabular representation of gender and sale attributes that convince customer to purchase online

Table 15 .3:
Tabular representation of monthly income and sale attributes that convince customer to purchase online

Which kind of sales on clothes at Online stores convince you to check them out and initiate purchase?
Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 (2016)

Table 16 . 1 :
Ratings over various issues while purchasing apparels online Jaipuria Institute of Management Management Dynamics, Volume 16, Number 1 (2016)