L'Oréal Taiwan uses predictive insights to reach the right
customers
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Case Study
L'Oréal Taiwan uses predictive insights to
reach the right customers
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Google Marketing
Platform
Headquartered in the suburbs of Paris, L'Oréal
is the world’s largest beauty company. With a
portfolio spanning luxury, professional, mass
market, and active cosmetics, L'Oréal helps
hundreds of millions of men and women feel good
about themselves.
Even though many customers discover and
interact with the brand digitally, the majority
of sales for L'Oréal’s luxury products occur
offline, in stores. This fragmented journey
made it difficult for L'Oréal to connect its
digital marketing investment to the return it
was receiving through offline sales. The team
in Taiwan used Google Marketing Platform and
Google Cloud together to predict which
customers would be most likely to purchase in
stores and then reached those customers with
advertising campaigns.
Email support available
Video Transcription
Chiang: L'Oréal is the world’s
largest beauty company
Chiang: The Asia market has
provided much of the growth for the L'Oréal
global business
Chiang: To succeed in Taiwan,
we need to have an advanced data strategy.
Hon: In Taiwan we typically
spend our marketing budget online because we
find out that a lot of customers are browsing
online to find their product, doing their
research, looking at the reviews, yet they make
their purchase offline.
Hon: Our challenge on our team
is that we need to make sure that our money is
well spent and reaching the right people.
Hon: So our Google accounts
team introduced us to a solution that allowed
us to use our data from both of our online and
offline sources.
Hon: With Google Marketing
Platform and Google Cloud we're able to
understand how people browse our websites to
predict which customers will be most likely to
purchase in the stores.
Hon: We started by bringing
all of our information into Google Cloud to
analyze the data. And then we found out that
there is actually a 14 day time lag between
when people visit our website and when they
visit our stores to make a purchase. So with
that insight, we built a customized machine
learning model to predict which people are
likely to go to the store to purchase in the
next two weeks.
Hon: With Google Marketing
Platform we were able to use these insights to
find new audiences and reach these people with
our Google marketing campaigns.
Chiang: With one of our
L'Oréal brands, Lancome, we saw a 2.5 times
increase in offline revenue from product sales
and a 2 times improvement in return on ad
spend.
Hon: This strategy has enabled
us to truly use a data driven marketing
approach by using predictive insights to reach
the right customers.
Hon: And with this successful
case in Taiwan, we are now expanding this
strategy to more L'Oréal brands, with the other
L'Oréal teams around the world.
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