Applications documentation

Adobe has built several applications on top of Experience Platform. You can find documentation for these applications using the links below:

The video below describes the use cases of each application built on top of Experience Platform.

Let’s talk about the applications built on top of Adobe Experience Platform, otherwise known as platform-based applications. Platform-based applications directly utilize Experience Platform’s key capabilities to address emerging next-gen customer experience use cases. These include Real-Time Customer Data Platform, Adobe Journey Optimizer, Customer Journey Analytics, and Adobe Mix Modeler. Let’s start with Customer Journey Analytics. Customer Journey Analytics, or CJA, is a journey-based analytics application that delivers cross-channel analysis and omnichannel insights within seconds. CJA leverages the rich behavior history of Experience Platform datasets to track and analyze journey events in real-time. Using CJA, marketers can analyze customer behaviors online and offline, and then use these insights to understand conversion patterns, optimize experiences, and predict future needs. Product managers can get a better understanding of product usage through a deeper understanding of customer needs and experiences, and data analysts can run unlimited cross-channel data breakdowns for deep ad hoc analysis, helping to drive improved customer experiences. CJA allows you to manage event and journey-based audiences, create end-to-end visualizations, and even leverage anomaly detection AI to find irregularities and pinpoint factors affecting your business. All in all, CJA is enabling organizations to leverage unique insights to activate and optimize engagement across all of their customer journeys. Next up is Real-Time Customer Data Platform, or Real-Time CDP. Real-Time CDP lets marketers collect data from across systems and unify it into rich customer profiles, ready for activation across any channel. Whether you’re operating from a B2C or B2B model, Real-Time CDP can consolidate first-party and partner data across online and offline channels. This data is transformed into profiles for each of your customers, accounts, or prospects, where they can then be grouped into actionable audiences through powerful segmentation workflows. You can enhance profiles with additional attributes, either through merging it with other audience data using Segment Match, or using customer AI to enrich with churn and propensity models. You can also leverage machine learning-based lookalike audiences to identify profiles similar to those in your existing audiences without restricting them to exact matches. When you’re ready to activate your profiles and audiences, Real-Time CDP provides a robust catalog of destination connectors and APIs for paid media, email marketing, web personalization use cases, and more. Let’s move on to Adobe Journey Optimizer. With Journey Optimizer, marketers can manage one-to-one personalized journeys and scheduled campaigns for millions of customers from a single application. Journey Optimizer also includes a set of decisioning capabilities for Next Best Offer, Next Best Action, and more. These capabilities can optimize experiences through email, mobile, in-app, push, SMS, direct mail, and web channels at enterprise scale. Whether you want to create one-off marketing messages or build a personalized multi-step omnichannel campaign, Adobe Journey Optimizer allows you to turn vision into reality. Finally, there’s Adobe Mix Modeler. Powered by Adobe Sensei, Mix Modeler uses AI and machine learning frameworks that let marketing leaders measure and forecast the effectiveness of their campaigns across multiple channels. To achieve this, Mix Modeler uses a combination of marketing mix modeling and multi-touch attribution. Marketing mix modeling processes summary-level data to provide aggregate insights at the channel or product level, while multi-touch attribution processes event-level data to focus on the incremental impact of each individual touchpoint in the customer journey. Mix Modeler is able to share the outputs between these features, producing consistent insights from marketing leaders to measure campaign performance across all channels, optimize budget allocation for marketing spend, and to forecast revenue when planning for different scenario spend mixes on future campaigns. With your data already consolidated in platform, these insights can be generated in minutes, so marketing leaders can always act on the latest information with minimal downtime. So that’s a quick overview of the platform-based applications. To learn more about each of these applications, check out Adobe Experience League, where you’ll find additional guides and tutorials. Thanks for watching.