Business Value of Platform and Commerce

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. -