As brands increasingly build internal statistical models and algorithms to tailor experiences, marketing cloud vendors are responding by building AI capabilities into their offerings.

The latest in line is Adobe which last week announced it is opening up its data science and algorithmic optimisation capabilities in Adobe Target, the personalisation engine of Adobe Marketing Cloud. 

The company said brands will be able to insert their own data models and algorithms into Adobe Target to deliver the best experience to customers. 

It will also add new capabilities in Adobe Target by integrating with Adobe Sensei, its AI and machine learning framework, to further enhance customer recommendations and targeting precision, optimise experiences and automate the delivery of personalised offers.

Among the key aspects of the announcement;

  • Open Data Science Capabilities: Adobe plans to open its data science and algorithmic optimisation capabilities in Adobe Target so brands can insert their own algorithms into the platform. This will enable brands to combine their industry expertise with Adobe’s machine learning and AI capabilities to deliver individualised customer experiences at massive scale. More details can be found in the blog post here.
  • One-Click Personalisation: New Auto-Target capability enables brands to automate personalised experiences across their digital properties with one click. Auto-Target uses machine learning in Adobe Sensei to determine the best experience for each consumer and continuously optimises those experiences as the consumer takes additional actions.
  • Personalised Recommendations: New recommendation technology in Adobe Target enables brands to leverage consumer intent to better predict what content and products customers might want next.
  • Automated Offers: With the enhanced decisioning power in Adobe Target, brands can ensure the best offer—out of potentially hundreds—is automatically shown to the right person at the right moment. Adobe Target now provides automated offers for mobile apps and IoT experiences.
  • Precision Targeting: The enhanced integration between Adobe Target and Adobe Analytics Cloud lets marketers target more precisely by using behavioural analytics and audience data to inform deeper segmentation.

“Consumer expectations have sky-rocketed to the point that hyper personalisation is no longer optional for brands, it’s imperative,” said Aseem Chandra, VP, Adobe Experience Manager and Adobe Target.

“Progressive brands are already developing proprietary algorithms. When integrated into Adobe Target, brands can combine their own expertise with the power of Adobe’s AI and machine learning tools to predict what customers want and deliver it before they ask, driving strong business value and brand loyalty.”

The ability to bring in proprietary algorithms into a leading marketing platform is a first for the industry. Brands benefit from the ability to blend their industry expertise with Adobe Sensei’s powerful machine learning and AI capabilities in Adobe Target to deliver individualised customer experiences at massive scale.

For example, a financial services company that created its own algorithm to predict which customers are most likely to respond to an offer can insert that algorithm into Adobe Target to test live traffic against the model to deliver the best possible offer to each customer.

Adobe Target, part of Adobe Marketing Cloud, has leveraged AI and machine learning algorithms for over a decade and is used by major brands worldwide like AT&T, Lenovo, Marriott and Sprint. Highly personalised experiences are leveraged across online channels, including web, mobile, email and more.

With Adobe Experience Manager and Adobe Campaign marketers can seamlessly manage and deliver personalised content. Integration with Adobe Analytics Cloud and Adobe Advertising Cloud ensures that every interaction with customers is hyper personalised.

Adobe was recently named the only leader in “The Forrester Wave: Digital Intelligence Platforms, Q2 2017” report, and received the highest scores possible in nine criteria, including behavioral targeting and online testing.

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