Leveraging AI & Composable Architecture for Enhanced CX
AI and machine learning can be used to provide a more unified view of your customers’ behavior and interactions.
Artificial Intelligence (AI) is a hot topic and is often discussed as a controversial “replacement” for the work done by writers, photographers, designers, musicians, and other artists. It is not, however, just used in these ways, and can in fact be quite helpful (and non-threatening) behind the scenes when striving to create seamless digital experiences for your customers.
The number of platforms needed to communicate with various audiences is constantly increasing, and each addition to your tech stack presents a new risk of presenting a disconnected customer experience (CX). This makes connecting and coordinating platforms essential to creating a positive CX—by essentially making what is complex behind the scenes seamless to the user.
AI can play a pivotal role in the process of creating seamless user journeys when used with a composable digital experience platform (DXP). Composable systems—web structures built from reusable components that can be mixed and matched to create varied digital experiences—are on the rise because they allow marketers and technologists to use the best of breed for each system, rather than a single monolithic platform that must do it all (and consequently is expensive to host and maintain).
Composable DXPs are by nature data-driven because they function using APIs, but the data is only as valuable as it can be orchestrated to create a seamless CX. That’s where AI and machine learning come into play. Areas where AI can be beneficial include:
Creating an automated tagging taxonomy for a better information architecture, search experience and personalization.
Powering search by integrating content from multiple sources and using machine learning to weight results based on users’ behavior patterns.
Getting content drafts underway. (A reasonable goal is to get your content 70% of the way there—AI will likely never fully replace your brand voice and style.)
Generating predictive analytics, by which data from your DXP can be used to help segment and personalize your CX.
All these AI use cases help to create a more unified view of your customers’ behavior and interactions with your content and services, which you can then use to continually improve, orchestrating a better CX. And because the integration of AI into DXPs is flexible and component-based, it can be tailored to meet your organization’s specific use cases, comfort level, and risk tolerance.
AgencyQ Is Here to Help
If integrating AI into your tech stack sounds overwhelming, don’t worry: AgencyQ is here to help. We have deep experience in working with API-driven platforms such as Sitecore’s CDP, Search, and Personalize, and in integrating them with AI. Our work with the Department of Energy’s Office of Science saved them seven staff-years of labor analyzing, tagging and migrating data (opens in a new tab). Are you ready for this kind of transformative change? Contact us (opens in a new tab) today!
Meghan Fishburn
Senior Vice President, Client Strategy
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