Adobe unveils experimentation capabilities in Customer Journey Analytics, driving omnichannel personalization

The digital economy has grown substantially since March 2020, and per the Adobe Digital Economy Index — powered by Adobe Analytics — consumers have spent $1.7 trillion online during that time. The COVID-19 pandemic induced a rare step change in e-commerce and cemented omnichannel services like curbside pickup. As more daily activities moved online and blended with offline channels, brands are now having to make the digital economy more personal. In every part of the customer experience, from new digital services to marketing content, brands need to deliver engaging offerings that are customized for individual preferences. In fact, this is now one of the largest industry-wide opportunities, as 77% of Gen Z and millennials say that relevant, personalized content increases their trust in a company (per a new Adobe survey).

To help brands capture this, Adobe Analytics is unveiling the Experimentation Panel in Customer Journey Analytics, a powerful new feature that bridges the gap between deep insights and action. Brands can test real-world scenarios, seeing how changing one aspect of the customer journey affects a different part of the journey. The winning experience can then be personalized to specific audience segments.

For instance, different variations of a new mobile app feature can be tested to see which one drives the greatest reduction in call center inquiries — and improves customer satisfaction as a result. Once implemented, custom audiences (such as customers who have previously engaged a customer service channel) can be engaged with the new offering. These “cause and effect” scenarios can be extended to any use case spanning marketing, customer service, and more. In retail, brands can see which email variation drives the most activity in-store. Benefits of the Experimentation Panel include:

Instant analysis: Robust statistical models, powered by machine learning, will dig into massive amounts of data and instantly provide an analysis on expected lift and confidence. It takes into account historical data, comparable campaigns, ongoing benchmarks, and more, to refine its recommendation for the user.

Flexible data sets: With Experimentation Panel, users can evaluate the cause-and-effect for any data source across online and offline channels. This is made possible through Adobe Experience Platform, which brings together disparate data sets across an organization, under a common language model. Consumers rarely engage a brand on only a single channel, so this helps ensure experiments align with real-world behaviors.

Personalization at scale: Once the Experimentation Panel insights are used to inform a new feature or content, brands can automatically create target segments. These segments feed directly into Adobe’s Real-Time Customer Data Platform (RTCDP) to activate personalization across different channels. A custom promotion that drives high in-store conversion for instance, can be delivered to certain geographies or loyalty members.

Additional Adobe Analytics updates at Adobe Summit include:

Streaming Media Capabilities: Media companies rely on Adobe Analytics to measure and report on the performance of digital content, as the streaming media audience continues to grow. In recent months, Adobe has powered events such as the Olympics and the Super Bowl. Today, we are announcing new Customer Journey Analytics (CJA) capabilities that brings together streaming data with cross-channel insights. By leveraging the power of CJA, which allows brands to analyze the entire customer journey, teams can now tie digital media consumption to conversion events on other channels like social media, the website, and even offline spaces. And with a more comprehensive view of customer journeys, media companies also have a foundation to trigger deeper personalization and drive retention efforts.

Interactive Attribution: The Attribution AI service enables brands to quantify the incremental impact of each marketing touchpoint across web, mobile, email, social media, and more. It leverages AI and machine learning to assess true marketing effectiveness, with insights that can inform budget allocation. At Summit, Adobe announced that models in Attribution AI will now be available in Customer Journey Analytics. Teams can interactively explore the impact of campaigns and budgets, with a data “canvas” that empowers users to be more creative and investigative. The flexibility of CJA also allows brands to customize attribution models that fit their business or a specific industry use case.

To learn more about Customer Journey Analytics and how deep insights can transform your business, click here.