How Big Data Helped E-Commerce Firm to Start Sunday Flea Market

Shopclues.com picks winning analysis from Google analytics, which gives him data from where the customers are coming from – tier I, tier II or tier III cities.

Other aspects of leveraging Big Data and Analytics is to have a visibility into what is the demographic of that particular city and a look at the transaction data. There is one element of data source, which is web site analytics, there is another element of Big Data that is the demographic of people and then pulling data from  transaction database in terms of who are transacting? Which city are they coming from? Which city are they shipping it to? What is the price point and what is the kind of product that they are buying?

At Shopclues.com, the product mix on the home page is very different from what Flipkart or Myntra and other people have. Mrinal Chatterjee, CIO, Shopclues.com says, “If we did not know who our customers are or where they are coming from or the value proposition that they perceive –  then we would have been headless chickens”

Sunday Flea Market

Biggest example of the relevance of Big Data is the pattern of time, when their customers come and visit the site. About a year and a half ago, they  realised Sunday is the slowest day.

The shopping pattern was the same as that of the other E-Commerce companies. They were also not happy with the slow Sundays.
    
Shopclues looked at a lot of metrics – and found that customers do shop on Sunday afternoons – but around 3 to 4 PM, there is a sharp decline.

Chatterjee says, “A lot of people might be going out and meeting friends or taking a nap or something like that. But what we saw was a decent amount of traffic, though lesser than other days.”

The firm launched a concept of a Sunday flea market. Sunday flea market is one of the biggest properties – it’s a short term sale only on Sundays, it starts zero hour and it goes on through the entire day of Sunday, but the peak of the traffic comes around the same time – between 10 in the morning to 3 PM.

Chatterjee says, “It has become one of the destinations. There are people who wait for Sunday flea market. Lot of people know us as the website that runs the Sunday flea market. The concept of the flea market was simple, it was lower price point items, with deep discounts – giving an example of the products we sell: we sell skipping ropes, we sell auto accessories like gloves, and we sell womens’ leggings etc. The concept of Sunday flea market was – we don’t have a huge volume of anything.”

One merchant may want to sell 15 skipping ropes, one merchant may have 50 cans of deodorants, which he wants to sell with a deep discount. These are still original brand new products with full warranty. The experience they have created around Sunday flea market is that, you don’t come here looking for any particular product, and you just come to the Sunday flea market! People buy things like socks, car charger for phones etc.

No Copying Others

Without Big Data,Shopclues would have ended up with others models. Chatterjee says, “We would have looked at what SnapDeal or Flipkart or Myntra was doing, and followed the pattern of design and promoted products whatever they were selling.”

For example, Shopclues sell a lot more Micromax phones than Apple iPhones – this is exactly what Big Data has done. It has nurtured this information to come with insights of the value peceptions of the customers. Chatterjee says, “It gives me a clear understanding of the people coming to our site. Customer is not willing to spend Rs. 45,000 – Rs. 55,000 on iPhone because it has a glamour value. They are looking for a very functional phone – they will go for a Micromax or a Xolo, they will buy a Karbonn or a Samsung (we are not selling too many S5s). This comes to us from Big Data.”

Gaining Shipping Upper Hand

Shopclues has merchants across the country – virtually from every state including Andaman and Nicobar – as well as their buyers come across the regions. For instance, there may be a buyer in Chennai and the merchant is in Delhi. Now, while shipping from Delhi to Chennai, there are probably 15 courier companies, which will do the same delivery. The Big Data helps them understand, which courier company would be the best to ship a product with.

They have Data Analytics, which is constantly computing two aspects of the cost of shipping the package, depending on either the volumetric weight and/or the time it takes for the product to be picked up in Delhi and delivered in Chennai – which is the transaction time.

Mrinal says, “We use Big Data to do all these analyses, and the interesting thing is we don’t just run them as reports so that somebody comes every morning and looks at the report. What we do is: we just pump this data back into the transactional business.”
 

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