Adobe Commerce Data Connection full demonstration

Transcript

Welcome to this exciting new demo for Adobe Commerce data sharing capabilities. CitiSignal is a B2C telecommunications company selling consumer electronics. Their objective is to boost customer loyalty, turning one-time customers into repeat purchasers, and to increase AOV in cross-sell of higher margin items, like accessories. They plan to accomplish those objectives by using the power of Adobe Commerce data sharing to achieve a single view of their customers and deliver uniquely personalized commerce experiences. Let’s see how CitiSignal uses Adobe Commerce with other Adobe Experience Cloud products to deliver a personalized shopping journey that achieves their goals. We begin with a customer who purchased a phone from CitiSignal over a year ago, based on historical purchase data in Adobe Commerce. While they had been a loyal customer in the past, since buying their phone, they haven’t engaged much with CitiSignal. We can see this in Adobe Experience Platform, within the customer profile under Events. Specifically, you can see Adobe Commerce has recorded an order placed event back in 2022. CitiSignal sees customers who haven’t purchased in a year as ripe for re-engagement. Data Connection in Adobe Commerce shares historical purchase data to Adobe Journey Optimizer, where CitiSignal has set up a journey to engage customers one year post-purchase. Adobe Journey Optimizer triggers this email, which lets our customers know that there are some brand new phones that came out in the last year that they might want to explore. Our customer is curious to check out the newest devices, and they click the link in the email, which takes them to our CitiSignal website on the Phones page. Our customer hasn’t logged in, but because they’ve clicked the link in the email and have purchased from CitiSignal before, we can associate that customer with a unique identifier, called an ECID. As our customer engages with our site, we capture those storefront events, and we continue to build out their real-time customer profile. From the Phone page, our shopper opens the Samsung Galaxy S22 product page, and explores the product colors and storage amounts. Now let’s take a look at our Profile Viewer tool, which allows us to see what impact these behavioral actions have had on our customer profile. Even though the customer hasn’t logged in, Adobe Realtime CDP has placed the shopper into a segment called Interested in Samsung Phones in Realtime based on their behavioral shopping data. Thus, we’re already starting to be able to personalize their experience on the site. Our shopper liked what they saw, but decides to continue browsing to check out other devices and clicks back to Phones to do so. Now with our understanding that this is a Samsung customer, we deliver a different content experience, including a Samsung-branded dynamic block. We’ve deployed a dynamic block showing the Samsung Galaxy S22 Ultra, since we know that the customer is interested in Samsung Phones based on our segment qualification, and we can try to drive upsell to the Premium tier. As a result, this is all happening while our shopper is not logged in and in real-time based on in-session actions taken on the site. After seeing this banner, our anonymous shopper is curious to check out the new Samsung S22 Ultra. They’re excited about the powerful new features and is a little hesitant about the price, but they select their color and memory option and add it to their cart. As soon as our customer clicked on the dynamic block, Adobe Realtime CDP added them to another segment called Interested in Premium tier Samsung Phones, which we can see here in the profile viewer. Next, our customer remembers that this site has their information saved to their account from the last time they bought a couple years back, so they sign into the site as they want to go through the checkout quickly. As soon as the customer logs in, Realtime CDP stitches the anonymous browsing behavior with the account and other customer information in Adobe Experience Platform. In Attributes, we can see that this customer has a gold loyalty level, which is data flowing in from our external CRM system. In Segments, we can see that this customer now has multiple segment memberships, including Interested in Samsung Phones and Interested in Premium Samsung Phones from earlier in the session, and both Registered Users and Gold Membership. Getting all this data in a single place helps achieve our objective of creating a single unified profile of the customers, so we can create that relevant experience for CitySignal shoppers. Now that we know all of this about the customer, we can deliver an ultra-specific personalized offer based on her loyalty status, upgrading status and interest in the Samsung Galaxy S22 Ultra. Our shopper sees a new dynamic block on the Samsung Galaxy S22 Ultra product page that shows gold members like her can receive a 20% discount on accessories purchased with an upgrade to the Samsung S22 Ultra. While she was slightly hesitant about the Premium phone before, with the discount she feels like it’s just right for her, and she’s excited to check out the accessories she knows she needs, such as a case. With the phone in her cart, she could either click on Accessories, click the Dynamic Block banner she saw above, or, as we’ll show here, scroll down to the Product Recommendations unit, Related Products, where she adds a phone case to her order. As the customer heads over to check out, she populates her checkout information. Unfortunately, just before she checks out, she gets a phone call that pulls her away from ordering and she abandons her journey. Soon after abandoning her cart, the customer receives a highly tailored email from CitySignal, triggered by Adobe Journey Optimizer, reengaging her with the specifics of her order and cart. Adobe Journey Optimizer can send across channels, so the customer also receives an SMS to engage her. Now that she’s reengaged across multiple channels, which we’ll show on the back end in just a minute, she’s interested in jumping back in. The customer clicks the link to follow the order through and is immediately taken to her cart, with the same discount she was offered before already applied, as we can see here. The customer sees the 20% discount applied in her cart and is pleased with her selection. She enters her credit card information and seamlessly checks out. She’s fulfilled CitySignal’s goal by reengaging with the brand, bundling multiple products, and buying a top-tier new device due to the personalized Journey and Loyalty offer. Next, let’s take a quick peek under the hood at how we created this experience. Let’s start out in Adobe Commerce to see how easy it is to get data flowing from Adobe Commerce to other Adobe Experience Cloud products. Here you can see our connector, Data Connection. Through an entirely UI-based process with no custom coding, you set it up once, then commerce data can flow to any other DX product. While we’re in Adobe Commerce, we can also see how we created the cart price rule for the 20% discount, under Marketing, then Cart Price Rules. If we look at conditions for which this rule is activated and click into Experience Platform Audience, we can see all of our audiences ready to be activated within Commerce. Here you can see we’ve selected three audiences, previously purchased, interested in premium phones, and gold members. This is what allows us to deploy that dynamic block with a related cart price rule in a hyper-personalized way, only to relevant segments. If we take a look at actions, we can see how we’ve set up this cart price rule with a 20% discount if items added to the cart are from the product family of accessories. Next, let’s check out the Shoppers profile within Adobe Experience Platform to show how high-intent, first-party commerce data enriches the profile. Here we can see the customer profile. If we click on Attributes, we can see all the profile data populated here. If we click on Audience Membership, we can see each of the audiences this customer has been added to. And if we click on Events, we can see all of the behavioral events the shopper has taken on the Adobe Commerce site. All of this commerce data flows right back into Adobe Experience Platform in real-time, which can then update our audience membership and modify the site experience. Next, let’s take a look at audiences within Adobe Experience Platform. Here we can see the audiences that are brought in from real-time CDP into Adobe Commerce and then actioned upon in real-time. These audiences are based on data from all sources being streamed into Adobe Experience Platform, including pulling offline data from CRM systems, which we can then use to customize commerce experiences. If we click into one of the audiences interested in Samsung phones, we can see the audience summary, profiles over time, and activated destinations. If we look at Audience Summary, we can see that there are rules for segment qualification. This includes the audience who has viewed the specific product, Samsung Galaxy S22, on the commerce site. If we look at Profiles over Time and change the toggle to Last 7 Days, we can see how the audience is updated as more customers shop. Lastly, if we look at Activated Destinations, we can see that both Adobe Commerce and Adobe Target are serving as destinations for this audience. Next, let’s look at how we involved Adobe Target. For this demo, we used Adobe Target for A-B testing on the CitySignal homepage. Adobe Target helped us create and display the best homepage experience for our customer. Experience targeting can trigger different experiences for different customer segments, dropping out content as needed for hyper-personalization. As you saw in the demo, this personalized experience extends beyond the commerce site to include an initial engagement email and an abandoned cart email in SMS. To show you how that was created, let’s jump into Adobe Journey Optimizer. Here in Adobe Journey Optimizer, we can explore the abandoned cart journey we designed for our customer. Our goal was to re-engage this gold loyalty customer with a targeted email and text message. So you can see just how we’ve designed that journey using commerce events here. Lastly, let’s jump into Customer Journey Analytics to show how commerce data is populating dashboards to help us understand the customer journey and how our customers are engaging. So that concludes our demo flow. In summary, we’ve used real-time behavioral shopper data, loyalty data from other sources, and purchase history, all consolidated within a unified user profile to modify segment membership in real-time and deliver a hyper-personalized shopping experience. We’ve seen how CitySignal was able to achieve their business goals of boosting sales of high-margin items such as accessories and upselling loyal customers on higher-end devices. And we’ve seen how all of this comes together on the back end with Adobe Experience Platform and Adobe Commerce.