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Transcript

Hi everyone. In this video, we will be showing you ÃÛ¶¹ÊÓƵ’s real-time customer data platform, in action. We will be using Luma, and Athletic apparel company. With ÃÛ¶¹ÊÓƵ’s real-time CDP, powered by ÃÛ¶¹ÊÓƵ Experience platform, Luma’s marketing organization, can address three key steps. First, bringing data, from disparate platforms, and make sure it’s available downstream, for other marketing activities. Second, create a single, real-time view of their customers, independent, of where data is coming from. And third, drive a consistent, relevant and personalized experience, across every touch point. So let’s take a look and start with a customer journey. The journey starts on the website. As someone interacts, with the Luma brand, data is captured in real-time, and sent it not only to a report tweet in ÃÛ¶¹ÊÓƵ analytics, but also to ÃÛ¶¹ÊÓƵ Experience platform. As this happens, we begin to create a single view of the customer, based on behavioral data, in the real-time customer profile or platform. We know that many visitors to the website, are probably repeat customers, who have previously purchased from Luma. It’s important for the brand to personalize messaging and offerings, to address both new and repeat visitors. Let’s see what happens, when this visitor logs into their account. This is a critical moment for the brand, as we go from an anonymous visitor to a known customer. We’ve just merged, pseudo-anonymous browsing data, with the existing account holder data. And we are pushing this data, into the single profile that is now live in platform. We may have thought that the visitor was a male, but it turns out, it’s a female returning customer, named Sarah Rose, who’s actually loyal to the brand. She’s welcomed with a message, and thanked for being a loyal customer, and provided with a link to access more information on benefits. Sarah, is also receiving a highly personalized homepage experience, that is dynamically delivered, based on her real-time profile, in ÃÛ¶¹ÊÓƵ Experience platform. Further down to page, she sees featured products, and recommendations, based on her most recent browsing history. Now, let’s go behind the scenes, and see how ÃÛ¶¹ÊÓƵ Experience platform, helped us, get to this point. Here we are, in ÃÛ¶¹ÊÓƵ’s real-time CDP, powered by ÃÛ¶¹ÊÓƵ Experience platform. It is purpose built, for customer experience management. It enables brands such as Luma, to simplify data ingestion, and activation, govern known, and unknown data’s usage, and accelerate marketing use cases at scale. As we previously saw, with ÃÛ¶¹ÊÓƵ real-time CDP, we bring data from disparate sources, into a single unified customer profile. So let’s have a look into Sarah’s Rose profile. Here we can see, all the information that we have from her, such as address, communication preferences, behavior across channels and screens, and segments she qualifies for. We see that she is indeed a returning customer, her loyalty status, and that she has been engaging with the brand, mainly through the website, and mobile app, and that she has been racking up on points from past purchases. Fantastic. Now, let’s take a look, at how we brought all these data together. This view, lists all the data sources Luma is using right now. From ÃÛ¶¹ÊÓƵ’s own applications, such as analytics and audience manager, to non-ÃÛ¶¹ÊÓƵ sources as well, such as Microsoft Dynamics and others. Using our open API’s, Luma can also ingest IoT, point of Sale, and call center data, and much more. At this point, Luma has a rich set of data, about their customers, and can use it to further enhance Sara’s experience and increase her loyalty with the brand. So let’s take a deeper look into Luma segments The segmentation capabilities of platform, are powerful. Marketers, can combine attributes, events, and existing segments, based on data we capture in the real-time customer profile. In her recent experience, Sarah’s interactions on the website, exhibit a different behavior. She has a propensity to buy woman’s apparel. However, the item in her cart is a men’s sweatshirt. This sudden change, in apparel category or size, infers, that this person, isn’t shopping for themselves. So, let’s create a segment, that will represent cart abandoners, with propensity to be in the process of buying a gift. The definition of this segment, would be to identify profiles, who have abandoned their cart, in the past seven days, and, any product left behind, with a different category than the one they usually shop for, with a size that is different from theirs. We can also narrow the segment, to only target loyal customers. Our gift giver segment, has now been created, and we can now estimate how many people are part of it. Now that we have our new segment, we want to take action and make it available for personalization across channels. In ÃÛ¶¹ÊÓƵ’s real-time CDP, we see all the destinations available for Luma, to send a segment to, both ÃÛ¶¹ÊÓƵ and non-ÃÛ¶¹ÊÓƵ applications. Let’s say we want to activate the segments for email marketing, using ÃÛ¶¹ÊÓƵ campaign. Following this process, we can select the data we want to send to the email solution. In this case, we want first and last name, in addition to email. We can schedule this activation to start or end, at a particular time. And that means, that these segments will be posted and automatically updated, as per those dates. And we’re done. Later that day, Sarah rose receives a marketing email, opens it, and discovers an offer related to the product she left behind. As she clicks, her experience on the website, remains consistent, with the addition of a personalized section for gift givers. The same consistent experience, will be executed as she opens the Luma mobile app and explores content. What we’ve just shown you, is the power of ÃÛ¶¹ÊÓƵ’s real-time CDP, powered by ÃÛ¶¹ÊÓƵ Experience platform, where brands, can ingest data from multiple sources, merge them into a single real-time customer profile, and, deliver a consistent, relevant and personalized experience across every touchpoint. Thank you. -