Intelligent Commerce
Online shopping can be highly
disconcerting for both shoppers and ecommerce companies. But algorithms feeding
on trillions of bytes of data are working hard at simplifying as well as
advancing the process without human intervention
The next time you shop on
fashion website Myntra, you might end up choosing a t-shirt designed completely
by a software--the pattern, colour and texture-without any intervention from a
human designer. And you would not realise it. The first set of these t-shirts
went on sale four days ago. This counts as a significant leap for Artificial
Intelligence in ecommerce.
For customers, buying
online might seem simple--click, pay and collect. But it's a different ballgame
for e-tailers.Behind the scenes, from the warehouses to the websites,
artificial intelligence plays a huge role in automating processes. Online
retailers are employing AI to solve complex problems and make online shopping a
smoother experience. This could involve getting software to understand and
process voice queries, recommend products based on a person's buying history,
or forecast demand.
SO WHAT ARE THE BIG NAMES DOING?
“In terms of industry
trends, people are going towards fast fashion. (Moda) Rapido does fast fashion
in an intelligent way,“ said Ambarish Kenghe, chief product officer at Myntra,
a Flipkart unit and India's largest online fashion retailer.
The Moda Rapido clothing
label began as a project in 2015, with Myntra using AI to process fashion data
and predict trends.The company's human designers incorporated the inputs into
their designs. The new AI-designed t-shirts are folded into this label
unmarked, so Myntra can genuinely test how well these sell when pitted against
shirts designed by humans.
“Till now, designers could
look at statistics (for inputs). But you need to scale. We are limited by the
bandwidth of designers.The next step is, how about the computer generating the
design and us curating it,“ Kenghe said. “It is a gold mine. Our machines will
get better on designing and we will also get data.“
This is not a one-off
experiment.Ecommerce, which has a treasure trove of data collected over the
last few years is ripe for disruption from AI. Companies are betting big on AI
and pouring in funds to push the boundaries of what can be done with data. “We are
applying AI to a number of problems such as speech recognition, natural
language understanding, question answering, dialogue systems, product
recommendations, product search, forecasting future product demand, etc.,“ said
Rajeev Rastogi, director, machine learning, at Amazon.
An example of how AI is
used in recommendations could be this: if you started your search on a
retailer's website with, say, a white shirt with blue polka dots, and your next
search is for an shirt with a similar collar and cuff style, the algorithm
understands what is motivating you. “We start with personalization--it is key.
If you have enough and more collection, clutter is an issue. How do you (a
customer) get to the product that you want? We are trying to figure it out. We
want to give you precisely what you are looking for,“ said Ajit Narayanan,
chief technology officer, Myntra.
A related focus area for AI
is recommending the right sizes as this can vary across brands. “We have pretty
high return rates across many categories because people think that sizes are
the same across brands and across geographies. So, trying to make
recommendations with appropriate size is another problem that we are working
on. Say, a size 6 in Reebok might be 7 in Nike, and so on,“ Rastogi said in an earlier
interview with ET.
Myntra uses data
intelligence to also decide which payment gateway is the best for a
transaction.
“Minute to minute there is
a difference.If you are going from, say, a HDFC Bank card to a certain gateway
at a certain time, the payment success rate may be different than for the same
gateway and for the same card at a different time, based on the load. This is
learning over a period of time,“ said Kenghe. “Recently, during the Chennai
cyclone, one of the gateways had an outage. The system realised this and
auto-routed all transactions away from the gateway. Elsewhere, humans were
trying to figure out what happened.
SUPPORT FROM AI SPECIALISTS
A number of independent
AI-focused startups are also working on automating manually intensive tasks in
ecommerce.Take cataloging. If not done properly, searching for the right
product becomes cumbersome and shoppers might log out.
“Catalogues are (usually)
tagged manually. One person can tag 2,000 to 10,000 images. The problem is, it
is inconsistent.This affects product discovery. We do automatic tagging (for
ecommerce clients) and reduce 90% of human intervention,“ said Ashwini Asokan,
chief executive of Chennai-based AI startup Mad Street Den. “We can tag 30,000
images in, say, two hours.“
Mad Street Den also offers
a host of other services such as sending personalised emails to their clients'
customers, automating warehouse operations and providing analysis and
forecasting.
Gurugram-based Staqu works
on generating digital tags that make searching for a product online easier. “We
provide a software development kit that can be integrated into an affiliate
partner's website or app. Then the site or app will become empowered by image
search. It will recognise the product and start making tags for that,“ said
Atul Rai, cofounder of Staqu, which counts Paytm and Yepme among clients. Staqu
is a part of IBM's Global Entrepreneurship Program.
The other big use of AI is
to provide business intelligence. Bengaluru-based Stylumia informs their
fashion retailer clients on the latest design trends. “We deliver insights
using computer vision, meaning visual intelligence,“ said CEO Ganesh Subramanian.
“Say, for example, (how do you exactly describe a) dark blue stripe shirt. Now,
dark blue is subjective.You cannot translate dark blue, so we pull information
from the Net and we show it visually.“
In product delivery,
algorithms are being used to clean up and automate the process.
Bengaluru-based Locus is
enabling logistics for companies using AI. “We use machine learning to convert
(vaguely described) addresses into valid (recognizable) addresses. There are
pin code errors, spelling mistakes, missing localities.Machine learning is
critical in logistics.We even do demand predictions and predict returns,“ said
Nishith Rastogi, chief executive of Locus, whose customers include Quikr,
Delhivery, Lenskart and Urban Ladder.
Myntra is trying to use AI
to predict for customers the exact time of product delivery. “The exact time is
very important to us. However, it is not straightforward. It depends on what
time somebody placed an order, what was happening in the rest of the supply
chain at that time, what was its capacity. It is a complicated thing to solve
but we threw this (challenge) to the machine,“ said Kenghe. “(The machine)
learnt over a period of time. It learnt what happens on weekends, what happens
on weekdays, and which warehouse to which pin code is (a product) going to, and
what the product is and what size it is. It figured these out with some
supervision and came up with (more accurate delivery) dates. I do not think we
have perfected it, but it is a big deal for us.“
THE NEXT BIG CHALLENGE
One of Myntra's AI projects
is to come up with a fashion assistant that can talk in common language and
recommend what to wear for various occasions. But “conversational flows are
difficult to solve.This is very early. It will not see the light of the day
very soon. The assistant's first use would be for support, say (for a user to
ask) where is my order, (or instruct) cancel order,“ said Kenghe.
The world over,
conversational bots are the next big thing. Technology giants like Google and
Amazon are pushing forward research on artificial intelligence. “As we see
(customer care) agents responding (to buyers), the machine can learn from
it.The next stage is, a customer can say `I am going to Goa' and the assistant
will figure out that Goa means beach and give a list of things (to take
along),“ Kenghe said.
While speech is one crucial
area in AI research, vision is another. Mad Street Den is trying to use AI in
warehouses to monitor processes. “Using computer vision, there is no need for
multiple photoshoots of products. This avoids duplication and you are saving
money for the customer...almost 16-25% savings on the operational side. We can
then start seeing who is walking into the warehouse, how many came in,
efficiency, analytics, etc. We are opening up the scale of operations,“ said
Asokan.
Any opportunity to improve
efficiency and cut cost is of supreme importance in ecommerce, said Partha
Talukdar, assistant professor at Bengaluru's Indian Institute of Science, where
he heads the Machine and Language Learning Lab (MALL), whose mission is to give
a “worldview“ to machines.
“Companies like Amazon are
doing automation wherever they can... right to the point of using robots for
warehouse management and delivery through drones. AI and ML are extremely
important because of the potential. There are a lot of diverse experiments
going on (in ecommerce). We will certainly see a lot of innovative tech from
this domain.“
J Vignesh
ET10MAR17
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