The Adobe Experience Platform is an open, extensible system that works in real-time to build robust customer profiles that a business can then act on. It provides integrated functionality for businesses wishing to provide optimal, data-informed customer experience across channels. <\/p>\n\n\n\n
Adobe Experience Platform is the industry\u2019s first open and extensible real-time customer experience platform with continuous intelligence and personalization at scale. The platform can ingest a high volume of customer data from different systems and stitches customer identities from various touchpoints. <\/p>\n\n\n\n
It also transforms the customer profile data into a single source of truth and creates a real-time customer profile. This helps in delivering personalized customer experiences.<\/p>\n\n\n\n
Customer experience management is the practice of designing and reacting to customer interactions to meet or exceed their expectations. This leads to higher customer satisfaction, loyalty, and advocacy.<\/p>\n\n\n\n
In today\u2019s world, customers expect brands to treat them as unique individuals and know their personal preferences and past behavior to create a more personalized & unified experience. Brands may have different touchpoints and departments, but consumers expect a unified & connected digital experience across different channels.<\/p>\n\n\n\n
According to leading industry sources, the importance of customer experience management will grow manifold for businesses. A recent survey by Walker revealed that 86% of consumers are willing to pay more for a great customer experience. Gartner predicts that by 2022, profitability will replace customer experience as the CMO\u2019s No. 1 strategic priority. <\/p>\n\n\n\n
Also, according to Clicktale, customers who have had an unpleasant experience on a brand website are 88% less likely to return.<\/p>\n\n\n\n
Adobe Experience Platform stitches together customer identities received from different touchpoints, and generates real-time customer profile fragments. It also handles not only different customer data attributes like their age, first name, or last name but also their past behavior. Companies can leverage this to deliver meaningful insights in real time.<\/p>\n\n\n\n
The platform also helps brands create high-value segments based on unified customer profile data.<\/p>\n\n\n\n
AEP provides a robust and powerful data governance framework to manage compliance with the regulations and restrictions of data usage.<\/p>\n\n\n\n
The framework lets marketers determine how data should be used in the organization, which makes decisions on how to use it, and who manages it. Marketers can apply specific labels to data based on governance and compliance needs, including contractual, identity, sensitive, and GDPR data labels.<\/p>\n\n\n\n
The data governance framework based on the customer’s consent can directly impact the identity stitching.<\/p>\n\n\n\n
Adobe Experience platform Query Service enables data scientists, data engineers, and marketers to use SQL to find insights from their omnichannel data in the Experience Platform. The Query Service uses a powerful, serverless, petabyte-scale query engine to query complex data efficiently.<\/p>\n\n\n\n
Customers can use different data management tools such as Dbvisualizer, Aqua Data Studio, and others to work with their data in the Adobe Experience Platform.<\/p>\n\n\n\n
The query service lets users connect to business intelligence tools like Power BI, Tableau, Looker, and other such tools.<\/p>\n\n\n\n
Adobe Experience Platform provides a centralized customer data platform for managing a single source of truth for customer data. It is capable of ingesting a high volume of known and unknown customer data.<\/p>\n\n\n\n
The data is ingested into the Experience Platform\u2019s petabyte-scale data lake and can be imported from Adobe solutions like Adobe Analytics and Adobe Target. It can also be imported through Adobe Audience Manager, third-party connectors (Microsoft Dynamics, Salesforce, S3, etc.), or through the available APIs.<\/p>\n\n\n\n
The Adobe Experience Platform is built on open and extensible cloud infrastructure (AWS, Azure). With this, it provides APIs that allow customers to quickly develop innovative experience applications at scale.<\/p>\n\n\n\n
The platform services layer is implemented using a microservices architecture having multiple services<\/p>\n\n\n\n
The Experience platform data science workspace provides the capability to apply machine learning and AI. This lets it normalize cross-channel data to enable intelligent customer journeys with real-time decisions and meaningful actions at scale.<\/p>\n\n\n\n
The platform comes with a fully managed, secure, and scalable infrastructure which helps enterprises leverage out-of-the-box Adobe Sensei models. They can also create their own models and seamlessly train them without the need for any additional infrastructure.<\/p>\n\n\n\n
The data science workspace also streamlines and accelerates data into insights enabling brands to make use of Adobe Sensei.<\/p>\n\n\n\n
Adobe Experience platform provides secured and efficient APIs to easily integrate with any other Adobe Cloud products or any non-Adobe system. Enterprises can analyze and activate the real-time profiles in milliseconds, enabling the delivery of experiences in real-time at scale to any set of devices or channels.<\/p>\n\n\n\n
For example, a consumer may visit a website and add an item to his or her cart, but then leave the website without checking out. Brands can use that data in real time to send an automatic personal email with an exclusive offer.<\/p>\n\n\n\n
Adobe has standardized the customer experience data by introducing a common Experience Data Model (XDM), an open data initiative in collaboration with Microsoft and SAP.<\/p>\n\n\n\n
All the data that is imported from different sources into the Experience Platform gets curated and organized into this normalized model called XDM. This enables brands to be able to surface new insights quickly and deliver experiences in a faster, more integrated way.<\/p>\n\n\n\n
The Experience Platform enhances Experience Cloud products. One such example is Adobe Campaign\u2019s recent functionality \u201ctriggered journeys,\u201d which leverages Experience Platform\u2019s real-time customer profile that automatically delivers real-time and personalized messages based on customer interaction with the brand.<\/p>\n\n\n\n
With Adobe Experience Platform, enterprises no longer need to have a point-to-point integration within Adobe cloud products. Instead, they can leverage a more robust and centralized integration that centers around the Experience Platform. Enterprises can also use APIs and tight integration with the rest of Adobe Cloud products to deliver more contextual and personalized real-time digital experiences.<\/p>\n\n\n\n
In AEP, some tools are labeled as \u201cApplications\u201d, some as \u201cFeatures\u201d, and a few are labeled as \u201cTools.\u201d This can be confusing, but the thing you need to know about AEP is that it has tools that help you do things. <\/p>\n\n\n\n
Here are the five primary tools that help you do things in AEP:<\/p>\n\n\n\n
This tool is a combination between Journey Orchestration and Offer Decisioning.<\/p>\n\n\n\n
CJA is like Analysis Workspace that gets data from the AEP data lake instead of getting it just from Adobe Analytics. Unless you live and breathe SQL, this is a fundamental product that you\u2019ll need for analysis if you\u2019re using AEP.<\/p>\n\n\n\n
This tool composes of fancy algorithms that do stuff like assign scores to determine the likelihood a customer will do something you want them to do on your website (propensity models). It can also automatically build attribution models. <\/p>\n\n\n\n
The tool itself doesn\u2019t DO stuff with the website. It won\u2019t dynamically display an offer. You would use this tool alongside another tool (like Journey Optimizer) to act on those segments and scores. <\/p>\n\n\n\n
This is a platform that creates segments from profiles and other data. You can set up stuff like segments to send emails to people in certain phases and tie it into other ad tech. <\/p>\n\n\n\n
There\u2019s also a B2B and a B2C version of this. The B2B version adds account-based functionality and has built-in connectors to platforms that let you pull in professional industry data (like account status and funnel stage). The B2C version focuses more on the checkout funnel, cart abandonment, etc. <\/p>\n\n\n\n
The following are tools that inform the RTCDP:<\/p>\n\n\n\n
This is a data scientist\u2019s playground where you can run code like R, Python, and Scala to do super complicated stuff that you wouldn\u2019t otherwise be able to do in Analysis Workspace (or CJA).<\/p>\n\n\n\n
In today\u2019s digital market, customers have come to expect personalized digital experiences when they visit a website. This means that businesses need to be able to rapidly capture and interpret the data that will allow them to identify the most appropriate content to serve the user. <\/p>\n\n\n\n
In a best-case scenario, the data collection, analysis, and application would be done in real-time. However, using technology, real-time processing, and machine learning is unquestionably one of the best ways to deliver impactful personalized experiences that will shape how your customers interact with your business. <\/p>\n\n\n\n
A seamless digital experience is critical to customer engagement and loyalty. And effectively putting your data to good use can help you recoup your investment in cutting-edge technology. It also helps you deliver brand-differentiating experiences for your customers and build brand loyalty. <\/p>\n\n\n\n