Graduation Show: Fashion Design & Knitwear Design, NIFT, Mumbai 2011

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Pictures reproduced with the permission of the photographer Shashi.R. Patel.

Online Shopping and its Future in context of Garment Retailing.

The world is moving at a fast pace, people are more connected to each other thanks to the revolution in the communication world.

The shopping habits are changing and more people are willing to pay for a product online than the number of people a decade ago.

This change in human spending behaviour is happening globally and is going to disrupt the existing business model of retailing sooner or later but this change is certain.

Different clothing brands are offering option of online shopping from their well designed portals and websites.

Retail chains are collecting vast amonut of data about the customers through different loyalty, membership and discount programs. A stiff competition is going on between the stores to collect larger amount of customer data in their database.

But there is a lack of a strong mechanism to use this data for the further enhancement of shopping experiences and increasing the sales and brand value of the store.

The percentage of online purchase as compared to traditional purchase is increasing in this world and is carried out through the portals of the garment retailers.

The present model is designed in which a person is required to be a member of the store, s/he logs into his/her account, selects thr commodities from a large database that is tough to browse, most of the time the customer doesn't come through the products s/he is looking for. The customer then puts the order and the product is delivered.

The fundamental flaw with this system is that product discovery mechanism is not strong and the customer seems unsatisfied after the browsing resulting in a bad image of the brand and resulting in non-sales.

If by some mechanism, this experience is enhanced for the end consumer and considering these sales as not a 1 time transaction, it could increase the consumer loyalty.

Now consider a situation in which a customer is an avid shopper and does most of his shopping online, he spends a lot on his shopping and is willing to buy more products if he could find the product he is looking for.

Now the retail chain has an oppurtunity to tap the potential of this field.
Lets assume the retail chain starts collecting user shopping behavior data, analyses it and looks for a shopping pattern and customer's Thinking and his likes/dislikes towards a commodity.

An algorithm is developed by the store that could compare and find some sort of similarity between two products on the basis of type of fabric, silhoutte, colour, shade, style, fit and blah blah blah.

Now analysing the past shopping history, the store could develop a graph of customer's interest, now the next step would be integration of the recommendation system with this intrest graph.

Recommending and displaying the customer products that have a level of similarity with the past shopping history, one example could be if a customer buys trousers with narrow fit most of the times, the recommendation system could display trousers with narrow fit more than any other fit.

Now this personalised suggestion would vary from one consumer to other and would increase the probabilty of the sales.

But this system also has a flaw, if the whole shopping experience is personalised (100% personalisation), it would turn out to be a small world for the consumer with little choices and would lead to balakanisation, the personalised experience should be tailored such that it adds the external shopping enviornment, international trends, what's new in fashion and these stuff that gives a balanced experience (e.g., 50% personalised, 50% random or external).

There is one more factor that affects the shopping experience of a consumer that is his/her social graph, e.g., friends and family.
The customer asks for a suggestion from them.

The system could add a social layer to it with the help of social networks. The system could be developed such that the customer could ask for feedback about a particular product of his choice from his social circle.

Friends could vote for it and comment about the style, this could in turn bring in more interest data about the person voting a product.

The personalised shopping experience would make the product discovery mechanism simplified and  one fring benefit of this system would be contextual discovery from tha addition of social layer to it which would in turn boost sales.

Its all about shopping experiences and if it could be enhanced it would lead to better market value and market share for the brand.