The Modern Marketing Blog covers the latest in marketing strategy, technology, and innovation.

Automate Personalization with Oracle Marketing Recommendations

Dimitris Tsomokos
Senior Product Manager

“Marketers are looking for new ways to drive conversion, revenue, and engagement—and to do so in increasingly automated ways using tools that can really ‘do it for me.’ Recommendations help make that a reality." - Kaushal Kurapati, GVP, CX Marketing, Oracle

For doctors, the first rule of the Hippocratic Oath is to “do no harm.” For marketers, a primary directive is “drive conversion and revenue.” We don’t take an oath, nor do lives depend on us, but we do sort of have our own marketing oath. That’s why the Oracle CX team is excited to announce the launch of Oracle Marketing Recommendations. 

Nearly half of marketers, in a bit of brutal, discouraging honesty, give themselves only a ‘C’ when it comes to their personalization efforts. Powered by machine learning, Recommendations makes real-time decisions to show customers personalized product and content—and help brands drive revenue. 

How It Works

Oracle Marketing Recommendations makes use of contextual and historical customer data and applies machine learning to identify and serve the right item—whether a service, product, or piece of content. The customer experience can be personalized automatically at the individual level, starting from the beginning of their journey from a homepage, a category or listings page, all the way through to product detail pages and checkout.

For example, a marketer in the retail space can personalize key landing pages (Men’s, Women’s, etc.) based on whether the customer is new, returning, or if they belong to a particular audience with a given propensity to buy from a specific brand. Product recommendations can be served on these landing pages using different algorithms for different audiences, such as:

  • most viewed or best-selling items filtered from the relevant category are suitable for new customers,
  • last viewed items or items recommended from the visitor affinity model are highly relevant for return customers,
  • and for product detail pages, you can easily employ strategies like people who viewed or bought this item, then went on to view and buy these items.

Similarly, Recommendations can surface relevant and serendipitous content to users. When you read news on the Internet, once you’ve finished reading an article, a link to something recent and related might pop up. But where automated recommendations really shine is by serving content from a library of stable content, such as a white paper or guide that correlates to a recent search. By guiding your customer through their journey, you’re increasing the breadth and depth of engagement and likelihood to convert. 

Underpinned by Maxymiser’s robust testing and personalization platform, marketers can test different Recommendation strategies against each other to determine what algorithm, location, and styling works best for their business. Plus, using its in-depth campaign reporting, marketers can easily measure the ROI of their Recommendations campaigns. 

Oracle is empowering marketers to easily inject, configure and launch a recommendation widget, without relying on IT resources.

Learn More

So, do you want to be an ‘A’ or a ‘C’ student in your personalization efforts? Check out our webinar recording to learn more about Recommendations. And stay tuned for future updates on how we envision Recommendations playing a central role in driving revenue and engagement across the CX Marketing portfolio!

Be the first to comment

Comments ( 0 )
Please enter your name.Please provide a valid email address.Please enter a comment.CAPTCHA challenge response provided was incorrect. Please try again.