Since time immemorial Indians have attributed great fascination and pride to "location.” As any real estate agent will tell you, “There are three things that matter in property: location, location, location.”
Ones “location” can help
others draw inferences about your preferences, needs and consumption behaviors.
In essence, the locations frequented by a user can help advertisers understand
their real world behaviors and therefore location becomes critical to help users
discover propositions that would interest them.
Until the recent
widespread adoption of smartphones, advertisers only had billboards as a medium if they wanted
to target consumers based on their location. While outdoor advertising has
multiple challenges exist with billboard advertising. It is a broadcast
advertising medium, which tries to appeal to all audiences without any focused
targeting or feedback loop mechanisms. The messaging is largely static (unless
digital) and typically loses oomph after several viewings.
Hence, the smartphones
that we carry with us everywhere have interestingly become a powerful medium
for location targeting.
In the PC era, a mouse was
magical as its actions made changes on the desktop screen. Mobile, with
real-time location information has effectively become the cursor of the real world.
Today, with a few taps on your smartphone you can get a taxi to pick you up, or
find the closest Chinese restaurant, petrol pump or ATM machine. Interestingly,
all the new on-demand services such as cabs, grocery and food delivery have
existed for quite some time, it is just that the smart phone has removed a lot
of real world friction, making the user experience magical.
Over the last few years, at
InMobi we have made significant investments in honing our location targeting
capabilities. Our diverse and widespread SDK footprint across news, gaming,
entertainment and utility apps provides us access to accurate location data, IP
addresses and hashed device IDs at scale. Access to this aggregate, anonymized dataset coupled with our
investments in big data platforms and data sciences enables us to cleanse the
data and derive meaningful insights to be leveraged for significantly enhancing
our ad relevance.
Dots represent ad requests from respective cities
targeting product capabilities may broadly be analyzed on two dimensions:
1. Targeting users based on where they are in the real world. The
use cases within this category include:
- Targeting administrative regions such as country, state, city or
zipcode as per the advertiser requirement. A typical use case for the above
targeting includes on demand services (such as cab aggregators, food delivery
companies) wanting to run campaigns only in their geographic service areas.
- Geo-fencing and Geo-conquesting (targeting within a specific
distance of a predetermined location) is largely used by retailers, automobile dealers
and quick-service restaurants to drive footfalls into their stores and
distribute coupons or offers.
- Points-of-Interest Targeting: Another interesting manifestation
of location-based targeting is the ability to use location as a proxy for audience
and target users around specific points of interest such as airports, universities,
railway stations, shopping malls and IT parks. Some of the use cases for this
targeting include youth-focused brands targeting around shopping malls or universities
and perhaps real estate companies targeting IT parks.
2. Crafting audiences based on the history of real world places visited
by users: Places visited by a user can provide us with very clear insights into
their life stage and behavioral attributes, enabling us to create custom
audience segments based on real world actions. Some of the examples of such
- Business travelers: Users who visit airports and business hotels
- Working parents: Users who visits schools in the morning and an
IT park subsequently.
- International travelers: Users who frequently travel abroad for
business or leisure.
- Commuters: Users who visit bus or train transportation hubs
frequently within a week.
The strength of the
solution lies in the ability to combine “location” specific user information
with “context” i.e. time of day/ week, weather, phone position (user leaning
back or forward). This combined information is like a power tool in the hands
of an advertiser.
As with all power tools, this one too needs to be used carefully
and with responsibility. Successful
advertising campaigns have always thought consumer-first and have benefited
from collaboration with partners who bring in, apart from technology, an
understanding of consumer targeting best practices.
After all, the consumers’ interests need to be paramount.