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Next Best Actions for AI Marketing with SAS Intelligent Decisioning & SAS Customer Intelligence 360

Started ‎10-23-2020 by
Modified ‎10-26-2020 by
Views 3,803

In a world of increasingly high consumer expectations, customers want to be known as individuals with distinct preferences, not just a member of a segment. The digital world is challenging marketers to consistently understand and enhance the customer experience across all channels, making mastering the art and science of next-best action (NBA) a worthwhile endeavor.



Figure 1: Next Best Actions & Decisioning for Customer Journey Activation

Next best action is a customer-centric marketing technique that considers the alternative actions during a customer interaction and recommends the best one. Determining what the next best action is leverages an organization’s competitive assets-the data and analytical insights used to understand a customer-in the moment of engagement, and serves that customer in a relevant and contextual manner whether it’s marketing- or service-related. Next best action is effective because it is able to cut through clutter to reach customers. 


SAS Customer Intelligence 360 enables the use of analytical models to provide deeper context in decision making for AI marketing efforts. Model scoring can be incorporated by users of any profile, ranging from no, low and high-code contributing team members. Robust enterprise-grade model management and governance is integrated within decision scenarios providing flexibility and customization in resolving complex customer experiences. 


In addition to analytic models, rules in decisions can also be utilized for customer next best actions. Rules can be used for selection, prioritization & arbitration to ensure the correct actions are delivered.


Within the subject of customer journey activation, let's walk through a presentation and demonstration together in the video below addressing the following questions:


  1. How does SAS enable users to make effective decisions based on the output of analytical models?
  2. How does SAS arbitrate across multiple potential actions for the same customer?
  3. Does SAS identify opportunities and recommend actions?
  4. How does SAS help activate analytical output for frontline users at the time of customer interaction?


The demo video will show how SAS personalizes a customer experience across web, mobile, and email while exploiting powerful analytical insight derived from SAS Visual Data Mining & Machine Learning. Using SAS Intelligent Decisioning, the demonstration highlights both batch and real-time analytical use cases to enable next-best-actions, as well as hyper-personalization.



Learn more about how the SAS Platform can be applied for customer journey activation here.

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‎10-26-2020 03:31 PM
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