Retail Asia 2018 RA September.October 2018 (Online) | Page 45

E-COMMERCE
the right time, at the right location can
translate into higher sales conversions
using technology such as geo-fencing
and day-parting.
Geo-fencing is a location-based
service that triggers a pre-programmed
action in a given set of boundaries,
allowing retailers to focus on passengers
originating or alighting in a specific area.
For example, Marina Bay Sands (MBS)
ran several in-vehicle campaigns geo-
fenced around its location where the taxi
screen will show passengers, alighting or
departing from their premises, a targeted
promotion for that period.
One of the specific campaigns was to
promote MBS’ celebrity chef restaurants
through an interactive campaign
featuring the various celebrity chefs,
their culinary expertise and restaurant
information. Targeted at tech-savvy
passengers who were familiar with ride-
hailing apps, the four week in-vehicle
campaign resulted in almost 60,000
impressions in Singapore.
On the other hand, there is also
day-parting which schedules content
at opportune moments throughout the
day. It works by dividing a day into
several segments and selecting when the
advertisements should be shown. For
example, ads can be restricted to show
during certain times of the day such
as during store hours or on weekdays,
reinforcing studies of retail behaviour
which suggest that certain times of the
day are better for driving purchases while
other times of the day might be better
for branding.
the passenger’s preferences mapped
against location, geo-location patterns
emerge that improve our predictive
accuracy, allowing us to evolve content
recommendations even as the car cruises
through the city.
Trying it on-the-go
We are starting to see augmented
reality (AR) incorporated into the retail
experience which allow customers to
have an immersive brand experience by
enabling them to envision the item in
their purchase consideration. It works
by supplementing a live view of the
physical, real-world environment with
a computer-generated image such as an
image, video, graphics or even location
data.
AR can be used to do virtual
product testing, gamification and in-
store navigation. Fashion brands such
as Timberland and Topshop have used
Kinect technology to create virtual
fitting rooms for shoppers to try clothes
and accessories, making the retailer
experience more convenient and novel,
thus encouraging footfall into stores.
According to retail solutions
provider RetailPerceptions, 61% of
shoppers would prefer to shop at stores
that offer AR and 40% of them would
be willing to pay more for a product to
experience it through AR.
Expanding the AR experience into
cars opens up exciting possibilities for
mass-customisation. The larger screen
and captive environment provide a
conducive environment for brands to
engage with passengers in a unique and
memorable experience to try products on
themselves — be it accessories, make-up
and glasses/sunglasses — and ultimately
drive sales.
With technology advancing in in-
vehicle screens, retailers have an arsenal
of tools at their disposal to engage with
consumers during their commute. Those
who are innovative in their approach
are better equipped to bridge the gap
between online and offline shopping,
scale their campaigns across geographies
in creative new ways and build a deeper
brand presence through targeted content.
Asian consumers are on the move.
Are you coming along for the ride? ra
Marina Bay Sands (MBS) ran several in-
vehicle campaigns geo-fenced around its
location where the taxi screen will show
passengers, alighting or departing from
their premises, a targeted promotion for
that period.
AI on the rise
We envision 2019 to be the year that
artificial intelligence (AI) will make a
breakthrough in the retail industry, with
more retailers using it to power various
parts of the retail and e-commerce
experience.
With the growing capabilities of
AI, we are experimenting with such
technology in cars to identify and serve
relevant content to consumers, beginning
with presence and facial recognition.
Once a passenger commences a ride, the
screen is engaged while the biometric
sensors and computer vision work out
the person’s demographic characteristics
in a matter of seconds.
Facial recognition goes one step
further to identify the face, not the
person, and their preferences so
that our algorithm then selects and
recommends appropriate content. With
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