Adobe Unveils Virtual Analyst and Upgrades to Experience Platform
Adobe today unveiled a virtual analyst in Adobe Analytics and several innovations to its Experience Platform that build on existing technologies to automatically uncover insights.
By leveraging the Adobe Sensei artificial intelligence and machine learning framework, the virtual assistant will surface valuable insights around topics like the drivers of unexpected spikes or drops in key metrics, such as online orders and web traffic.
"We took our time to build the new virtual analyst, spending years rigorously validating the technology with real customer data and training the AI model to make sure the outputs solved real problems," said John Bates, director of product management at Adobe Analytics, in a statement.
The virtual analyst will always search and analyze company data, prioritizing changes that it finds interesting. Deep learning models allow it to assess data points across all customer interactions. It then proactively prioritizes data analysis based on business and user context.
Machine learning algorithms will also de-duplicate recommendations and take into consideration the preferences and consumption patterns of users. It will also analyze the behaviors of all other users within a company to find similar people and use that to inform better personalization. The system will provide a means to like recommendations, which reinforces the machine learning model and makes virtual analyst more intelligent over time.
The new virtual analyst is built on an umbrella set of solutions in Adobe Analytics. Powered by Adobe Sensei, this includes Anomaly Detection (where the system looks for statistically significant deviances in data), as well as Contribution Analysis (identifying factors that contribute to anomalies).
The innovations in Experience Platform enable companies to do advanced analysis on customer datasets, improve mobile experiences, create custom data models, and govern data more effectively.
With Adobe's new Experience Query Service in Experience Platform, data scientists will be able to pull all of their datasets stored in Experience Platform—including behavioral data as well as point-of-sale (POS), customer relationship management (CRM), and more—and query those datasets to answer specific questions about the data.
Experience Query Service will provide data scientists with a standard query language to manage the datasets in Experience Platform as well as the querying capabilities to turn those datasets into actions.
Adobe is rolling out new mobile capabilities in Adobe Experience Platform Launch. Now, companies can use Launch as a SDK management system. Mobile app developers and IT professionals can also browse for and activate third-party extensions via a catalog.
With Adobe's new Data Science Workspace, data scientists can access their vast datasets in Experience Platform to create and train custom data models, streamlining the data science workflow, and significantly shorten the time from data to insights. Data scientists can leverage Data Science Workspace using pre-built models or create custom models. Adobe Sensei automatically pulls key insights from these models, enabling companies to deliver more personalized and targeted digital experiences for customers across touchpoints.
To help companies better govern their customer data and manage compliance around its use, Adobe introduced plans for a powerful Data Usage Labeling & Enforcement (DULE) framework in Experience Platform. The DULE framework will simplify and streamline the process of categorizing data and creating data usage policies. This will ensure marketing actions that require data will be immediately evaluated based on the data usage policies that need to be applied.