Oracle Boosts Marketing Cloud Services With Added AI, Chat Features

Marketers are on the front lines in the development war for artificial intelligence (AI), as another major marketing cloud vendor announced expanded AI capabilities on Wednesday.

Oracle unveiled new chat features and adaptive intelligence to its Customer Experience (CX) Cloud Suite at the company’s Las Vegas conference, Oracle Modern Customer Experience. Oracle’s CX Cloud Suite is a part of the company’s Oracle Applications Cloud, and includes a wide variety of business intelligence applications such as the Oracle Marketing Cloud, Oracle Sales Cloud, Oracle Service Cloud, and Oracle Social Cloud.

Oracle CX Cloud Suite users can now incorporate chat bots into their communications programs to facilitate customer experiences on both text and voice-driven platforms, such as Facebook Messenger or Amazon Alexa.

In addition, Oracle has embedded the Oracle CX Cloud Suite with a series of customer experience applications powered by artificial intelligence. The new Adaptive Intelligent Apps for CX incorporates first-party and third-party data with machine-learning algorithms to help Enterprise companies optimize digital communication in real-time.

Oracle’s Adaptive Intelligence Apps are powered by the company’s data marketplace, a collection of more than 70,000 attributes and six billion consumer and business profiles available in the Oracle Data Cloud. Marketers can pull in a wide consortium of data points to optimize digital campaigns, including historical customer data, social activity, Internet of Things (IoT) data, and weather.

Since the adaptive intelligence applications are embedded in Oracle’s cloud suite, Oracle users can utilize the insights without needing to be a dual customer of multiple products. It brings in the data from Oracle’s Data Cloud to provide insights, without a marketer needing to buy any specific data attributes or subscription to the data cloud.

Email marketers can plug adaptive intelligence offers directly into Responsys to create dynamic email campaigns, and the insights populate when the email is opened as opposed to when it was sent.

“Adaptive Intelligent Offers is basically a recommendation engine,” says Steve Krause, GVP of product management at Oracle Marketing Cloud. “In any predictive intelligence or machine-learning system, better data tends to make better results.”

Krause says Oracle’s data marketplace is a differentiator for the company, allowing it to reach beyond brand data to see what else a customer has done online. 

For example, Oracle will populate a retail Web site with women’s clothing if it knows that there is an extremely high likelihood that a new Web site visitor identifies as female. When an anonymous person shows up on a company’s digital properties, Oracle can pull in data from its Data Cloud to see if it has any known identifiers on that individual.

Machine-learning algorithms require a treasure trove of data before they can begin to crank out successful recommendations because the machines legitimately need a substantial period of time to learn. Krause compares this issue to cold-start engine problem in automobiles, highlighting how data serves as the engine fuel for artificial intelligence. 

“Oracle’s approach to AI is very pragmatic,” says Krause. “The algorithms are not magic. Yes, they can do things that look amazing. But at the end of the day in machine-learning, the lessons are in the data.”

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