Luma has a new product launch
for a seasonal line of fall gear,
and they want to promote their new inventory.
They plan to accomplish the objectives you see here
by uniting the transformative
data-driven capabilities of Adobe Experience Platform
with Magento Commerce.
This combination gives them everything they need
to create a single view of their customers
and leverage insights to activate
personalized commerce experiences across channels.
Let's see how Luma uses Adobe Experience Platform
to bring commerce and content together
to deliver a unique shopping experience.
An anonymous shopper starts browsing the Luma storefront
powered by Magento Commerce.
Even though we don't know much about this shopper,
Adobe Experience Platform is already starting to build out
their real-time customer profile
based on the data from Magento.
As this person starts looking at the equipment products
in the new seasonal collection and a new fitness watch,
we see that they're automatically added to the segment
interested in gear based on this behavioral data.
Using the profile viewer, which is a demo tool,
giving us a look into the data flowing into platform,
we see the user's experience cloud ID,
their experience events, and the segment qualification.
Even though this user is anonymous,
we can start to use this data
to personalize their experiences.
Now let's take a look in platform.
Using the same EC ID or Experience Cloud ID,
we can look up the real-time customer profile
to view details around this person's activity
and engagement with Luma.
We also see their segment interested in gear
based on the commerce data coming from Magento.
Back on the website,
the user is interested in the product and adds it to cart.
They sign into the site for more tailored
and faster purchase experience.
Now that she's logged in, she becomes a known shopper
and we can stitch all of her anonymous browsing behavior
together with her known customer information
in Adobe Experience Platform.
This blending of customer data is the difference
that platform can make
and is what creates a single robust customer profile.
We see her CRM and loyalty data coming in
from Microsoft Dynamics,
and that she's also been added to the gold loyalty segment
from this data.
We also see she's a part of the high propensity
to purchase gear segment.
This is because Luma uses customer AI intelligent service
to predict the propensity to convert on gear,
and she has a high propensity,
and all of this new known customer information is added
to her previous browsing where she was qualified
for the interested in gear segment.
If we quickly refresh the profile
in Adobe Experience Platform,
we can see this updated profile information,
including her CRM data, loyalty status,
and even her customer propensity score for gear.
Getting at all this data in a single place
wasn't possible before.
It helps Luma accomplish their objective
of creating a single view of their customers
so they can have a consistent and relevant experience
across channels and devices.
So let's move back to the shopper now.
After logging in, she heads back to the homepage
and we can see that she's being shown this offer
for 20% off gear for gold members.
Having all of the customer data gathered in platform
enables Luma to deliver this unique offer
based on her segment qualification as a gold member
who is interested in and has a high propensity for gear.
She sees a 20% off discount applied in her cart now,
but before she goes on to make the purchase,
she gets distracted and leaves the site.
Let's take a quick look under the hood
at how we created this experience in Magento Commerce.
Here in Magento, we can see all of our segments,
including those coming in from Adobe Experience Platform.
This is powerful because we have enhanced data
from all the sources being streamed into platform
that we can use to customize our commerce experiences.
We've set up a few different promotions
in our cart price rules,
one of which offers 20% off gear to gold loyalty members
who will also have an interest in gear
or high propensity to purchase gear.
I can designate this rule to fire
when a shopper qualifies for our platform segment
and adds a gear product to the cart.
They'll see a 20% off discount apply.
Next, we created a dynamic block
where you can create rich, interactive content
that's driven by logic from price rules
and customer segments.
By combining the intelligence of Adobe Experience Platform
profile data with the flexibility of Magento Commerce,
Luma is able to deliver
amazing personalized commerce experiences
that drive customer lifetime value.
Luma can automatically detect the dwell time
from Sarah not purchasing the fitness watch
that's in her cart and respond with a personalized email
using Adobe's journey orchestration application service.
Journey orchestration allows marketers
to orchestrate individual customer journeys at scale
across channels by intelligently anticipating
every individual's needs in real time.
Luma can trigger this journey
based on when someone abandons cart
and send them a personalized email
pulling in additional data sources available in platform
like the person's nearest store
and the inventory available for the item
that they added to cart.
So here we see this journey mapped out
and we'll send them an email using Adobe Campaign.
Sarah receives this email
that there are only four left of the fitness watch
at her nearby San Francisco store, creating some urgency.
This highly personalized email
along with the reminder that she gets 20% off gear
as a loyalty member entices her
so she clicks through from the email back into the cart
and selects to buy online and pick up in store
and makes the purchase.
When Sarah goes to the store,
the sales associate in the store
uses the Luma clienteling app
to tap into Adobe Experience Platform
and see all the data we have on Sarah.
They can see her profile information
as well as the product she's recently viewed,
the channels she's interacted with Luma on,
her current and previous purchases and more.
Tapping into the new offers decisioning service
on Adobe Experience Platform,
the store associate also sees the next best offer
Sarah's eligible for in the clienteling app.
They make a suggestion based on the next best offer
for buy two and get 100 points.
Sarah, while interested,
doesn't make another purchase at this point.
Adobe's new offers decisioning service
provides a capability to create personalized, optimized,
and orchestrated experiences across customer interactions.
So later, Sarah receives a push message
with that same new offer.
It highlights another channel
that Luma can re-engage with their customers like Sarah on
to drive them back to the site.
In summary, we've seen how Luma used
Adobe Experience Platform together with Magento Commerce
to create a single view of their customers
and leverage insights to personalize experiences
on their digital storefront and across channels.
This helped them accomplish their objectives
leading to a successful data-driven launch
of their new line of seasonal gear.
Adobe is committed to helping customers like Luma
differentiate the customer experience
through the leading content and commerce capabilities
that we looked at today.
Adobe provides a flexible and scalable end-to-end platform
to manage, personalize, and optimize experiences
for every touchpoint across the customer journey.