To sharpen its competitive edge in the increasingly crowded local online grocery retail space, RedMart is tapping real-time data analytics to make shopping easier and more intuitive.
The home-grown grocery giant has recently begun using Amazon Web Services (AWS), a cloud-computing platform, in order to track and process its customers' behavioural data.
In particular, it is using Amazon Kinesis, which allows real-time data to be collected, analysed and used to streamline the shopping process.
International companies that use AWS include Airbnb, Yelp and Net- flix, while local adopters of the service include taxi booking app GrabTaxi and securities broker Kim Eng Securities.
RedMart hopes to tap AWS to gain an edge over competitors such as honestbee and foodpanda.
The online shopping market in Singapore has grown exponentially over the last few years. It was worth $1.1 billion in 2010, and is projected to hit $4.4 billion by this year, according to research by PayPal.
RedMart co-founder and chief technology officer Rajesh Lingappa said: "If you look at a typical large supermarket, you will find about 12,000 unique products in the store.
"But for us, we have over 25,000 products, and just a small screen space, so our biggest challenge is making it easy for customers to browse and pick their items."
One way in which customers are benefiting from the use of AWS is that they now have a personalised search experience.
The service was rolled out in beta about two months ago, and will be released over the next few weeks.
This means that when a customer searches for an item on the RedMart website, the results that show up can be prioritised according to factors such as purchasing history, items already in the cart, and what other customers have bought based on the search term.
"Let's say you have diapers for a newborn in your cart. If you search for something like 'baby powder', we will be able to surface the right kind of powder for newborns," Mr Lingappa explained.
RedMart also uses such real-time analyses to recommend items to customers just before they check out. There are two types of suggestions that may appear - one based on a customer's order history, and the other based on the items that are in his cart.
For example, if a customer previously bought a set of products, but missed out a few of those in the current order, the website will then prompt him by asking if he wants to buy those missing products.
The other type of recommendation is based on the items that have already been selected in the cart.
"For example, if you're ordering for a party, we can tell by looking at the items in your basket," said Mr Lingappa. "If you have everything except the plastic plates or cups or whatever it is, we can ask: 'Did you miss this?'"
While such services are already being tested, Mr Lingappa said that the company is continually finding new ways to use real-time data to enhance customer experience.
For example, other avenues it is exploring include having personalised promotions, perhaps based on a customer's loyalty to a brand, or conducting highly targeted marketing, such as giving out product samples to customers who have ordered similar items.
Mr Lingappa added that with extensive behind-the-scenes data crunching, the end goal is to make the browsing and purchasing experience a seamless one for customers.
"Groceries are a basic necessity, and our customers are ordering on average 1.8 times a month," he said. "We want to make the experience as smooth as possible, so they don't have to waste any time when ordering."
