Although 2020 ushered in a new decade, the way businesses continue to interact with their customers hasn’t changed. Each customer interaction across channels should provide information to businesses on ways to attract, convert, engage, and deliver a compelling experience.
Why is data the most underutilized asset for companies that collect this information in terabytes year-over-year? Predominantly, it’s because data isn't quickly usable. The problem is that every bit of data seems to be in a different format, or on a different platform.
In order to help companies centralize and standardize their customers data and content across channels, it’s imperative that transactional data and interactional data be integrated. Doing this will support and bring consumers' evolving needs to the surface while also providing a superior customer experience. Hence, the advent of Adobe Experience Platform (AEP), a platform that enables decisioning in milliseconds.
With Adobe Experience Platform (AEP), companies can make disparate data sets work together and be understood. Let’s explore a few applications that exist within AEP that will facilitate this:
Experience Data Model (XDM)
Experience Data Model (XDM) has been developed to help companies avoid much of the constant data translation and re-translation process. XDM is the blue print that stitches the entire journey of a customer across multiple touchpoints, both online and offline. XDM supports integration with extract transform load tools like Informatics, SnapLogic, and Unifi to ensure the data conforms to the correct specifications for use by the AEP platform. XDM can catalog and categorize your data and define policies to manage compliance with regulations such as GDPR and restrictions controlling the use of your data.
With Location Services, companies can gain a deeper understanding of their users with the addition of location context. This will ensure the right message or experience is delivered in real-time at the instant the transaction is taking place. Direct messages and experiences can be delivered based on historical interactions with places and assist with successful conversions of campaigns with a call-to-action to visit a physical location.
Adobe I/O provides everything you need to perform different functions on data (like ingestion, lookup, and processing) and build customer experience applications. The platform is built using API-first design principals; it opens multiple integration opportunities, supports specific task-driven use cases, and offers functionality to integrate with AEP or other Adobe solutions.
Query Service is a powerful analysis tool for discovering and directly querying all of customers datasets stored in the Experience Platform’s cloud data lake. It will answer specific cross-channel and cross-platform questions. A combination of XDM, data lake, and Query Service enables data scientists and analysts to spend less time wrangling data, and more time analyzing customer data in real-time while driving real-time customer journeys. Query Service supports ANSI standard SQL and uses a PostgreSQL client as interface enabling data engineers to accelerate the time to visualize the results of the query inside data visualization platform (like PowerBI, and Tableau). Thus, allowing brands to obtain a clear view and query datasets from multiple business intelligence tools, unlocking omni-channel use cases, and maximizing investment.
Data Science Workspace
Data Science Workspace is fully integrated with the Experience platform, using machine learning (ML) and artificial intelligence (AI) that can run on any of the data within Experience Platform to enrich customer profiles with additional insight to optimize experiences. The workspace includes pre-built machine learning recipes (like Product Recommendation and Retail Sales prediction) powered by Adobe Sensei. It’ll also allow the user to adapt a prebuilt recipe to your needs, bring in existing models, or author custom models from scratch. Thus, helping data scientists to streamline their entire workflow and take advantage of the capabilities that fuel deeper data discovery.
In conclusion, AEP is an all-encompassing infrastructure which can be easily transformed into standardized Experience Data Models, Query Services, and Data Science Workspaces. It’s seamless integration and open APIs are the gateway to simplify and build custom solutions. This helps empower businesses, accelerate time to value, and focus on optimizing experiences, which, in turn, will better serve customers.