Cutting Through the Data Glut: Getting Answers Fast for Personalization with AI and the Adobe Experience Platform

As brands continue to deploy new MarTech tools for tracking the customer experience and ramp up the data collection efforts of the tools currently in place, the result for many companies is data overload. As they gather more raw data, in disparate forms, too often it can’t be easily integrated and analyzed. In this scenario, real-time personalization is impossible.

What’s needed to bring real-time personalization to life is a single platform that combines many different data sources (behavioral, point of sale, CRM, etc.) while providing best-in-class tools driven by artificial intelligence and Machine Learning that can quickly organize and utilize all that data. 

Data integration is the starting point. It’s estimated that data analysts spend 80% of their time being data janitors, cleaning up data from disparate sources. With a single platform, the number of sources is dramatically reduced. Integration of the data platform and analytic tools also speeds up the process for building real-time, data-driven models and algorithms. This integration will empower brands to make real-time personalization a reality.

This is the thinking behind Adobe’s new solution for enabling real-time personalization.  By using Adobe Experience Platform (AEP) as the central point of data management and collection, in combination with its new Experience Platform Query Service and Data Science Workspace for data manipulation and analytics, brands have an optimal solution for taming data overload and developing real-time personalization.  It enables brands to “humanize” the customer experience.

Query Service simplifies stitching together various data points quickly to create specific datasets that will power fine-grained analyses. Because analysts don’t have to do the data janitor work, they can focus on delivering results and insights faster. Query Service also incorporates several analytic tools for the business analyst to get the most from these newly created datasets.  

Meanwhile, Data Science Workspace provides an AI-enabled platform for data scientists, empowering them to provide the models and algorithms with the performance necessary for real-time personalization. Data Science Workspace utilizes Adobe’s intelligent Sensei technology to provide the AI-assisted functionality necessary to quickly get key insights from the large datasets. Adobe Sensei technology provides the deeper data understanding and adaptive intelligence that is essential for model development that supports dynamic, real-time personalization. With Data Science Workspace, data scientists can deliver “self-tuning” models using Machine Learning for real-time personalization to address key elements such as correlation, causation, and affinity for buying specific products.

A real-world example of this approach is provided by DXC Technology, which is using Data Science Workspace to learn how to enhance its website redesign activities. The company uses Data Science Workspace to build Machine Learning models that complement the rich reports it gets from Adobe Experience Platform as it seeks to reduce website bounce rates. The models help it pinpoint factors that are predictive of bounces (such as geography and browser types). In the future, they could help drive personalization on a website by watching for indications that a visitor is likely to leave the site and then serving up proactive interactions, such as a chat window, to prevent that bounce.

The combination of the data management/organization capabilities of Adobe Experience Platform and the data manipulation and analytic/modeling tools found in Query Service and Data Science Workspace provides a comprehensive solution. Brands can now deliver a true, real-time customer experience to gain competitive advantage. 

To learn more, click here.