STEPHANIE WONG: Hi.
I'm Stephanie.
And today I'll be showcasing the digital shopping
journey of a beauty consumer and how
retailers can improve customer experience and engagement.
With the COVID-19 outbreak and resulting disruptions,
consumers were left homebound for days at a stretch.
A recent Google survey shows beauty consumers
initially purchased less products,
but recently have a revived interest
in beauty categories like makeup, sunscreen, and shampoo.
They've also shifted heavily towards online purchasing.
Of course, with online shopping, consumers
are experiencing the same pain points that have always
come with beauty shopping.
It's hard to choose the right product,
envision the product on themselves,
and decide on a product without prior brand experience.
Today I'll show you how you can empower your customers
with a seamless online shopping experience
and carry them from product discovery
to consideration to purchase.
Meet Mary.
Mary is a marketing consultant by day.
Even though her city does not have
a shelter-at-home order in place,
Mary is working from home.
But summer is here.
And Mary has a socially distant picnic
planned for this weekend with some of her close friends.
It's outdoors and feels relatively safe.
She plans to wear a mask on her way to and from the park.
But she also wants to look great on her rare day
out Mary decides to experiment with a dramatic look
for her eyes.
To start, Mary searches YouTube for a daytime eye look
and finds a full tutorial on it.
She loves this look on the influencer, of course.
But she's not sure it will work on her.
Luckily, she notices a Try It On button under the video.
She's able to try on the look on her eyes
and even experiment with different colors using
a built-in augmented reality feature.
Looks like the blue really pops on her.
All of this works using machine learning and ARCore.
The technology dynamically detects the user's face shape
and attributes rather than static images.
This allows you to create rich, engaging experiences
for your customers.
And with an integrated shopping button, users like Mary
can quickly land on the Shopping page.
To check if the eyeshadow will suit her skin tone,
Mary can simply head to her integrated digital shopping
assistant and ask that question using voice.
The assistant can also show her reviews
and answer any common queries.
With a digital shopping assistant,
you can introduce new interactive ways
for your customers to experience your brand.
Dialogflow is the underlying technology for the shopping
assistant and can be used to easily
train a chat bot on your product graph for a specific SKU,
from product details, or frequently asked questions.
Mary adds this item to her cart.
And as she does that, Mary receives recommendations
on additional products to buy.
Retailers today are increasingly centralizing their user data
in Google's BigQuery data analytics platform
and then building personalization
and recommendation models on top of this data.
Here we're able to take a look at her previous purchase
history, as well as the items in her cart,
to provide more relevant recommendations to complete
her purchase.
As Mary scrolls through the frequently bought together
and other items of interest, she remembers
she could replace her cleanser.
She searches for dry skin cleanser and adds to her cart.
Additionally, she remembers she is running out
of her favorite sunscreen.
So she clicks on Vision Search and simply snaps
a picture of the sunscreen container
that's right next to her desk.
She uses it to search for the product on the retailer
website, and it matches with a click.
Today's retail search is keyword-centric, driven largely
by manual merchandising rules, matching tokens or words
in the query to data in the catalog,
and use of limited data from retailers' logs.
Google Cloud Search for Retail provides retailers
with high-quality product search results for their websites
and mobile applications.
Users can begin a query via voice, image, text, and barcode
and get to their choice of products faster.
With everything she wanted to buy and more,
Mary finalizes a time that works for her
for curbside pickup at her nearest store
and wraps up by paying with GPay.
Contactless feels good not just in store, but online, too.
Now all she needs to do is go pick up her order.
Thankfully, the store was just a mile away.
With integrated maps, she can easily
find her way for her scheduled curbside pickup
right from her confirmation mail,
beauty shopping made fun and easy.
Most of Mary's journey is on the site,
so why have a disconnected experience
before reaching the site?
Mary's journey demonstrates how Google Cloud's AI/ML-powered
products and solutions can create a more seamless user
journey and captivate customers with engaging
and hyperpersonalized moments.
What are you solving for?
To learn more about Google Cloud's Retail solutions,
check out the link here.
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