Measurement, Experimentation, Targeting & Journey Optimization with SAS Customer Intelligence 360
This article and demonstration video represents an important and bold update to the AI-marketing capabilities of SAS Customer Intelligence 360. Spanning across three distinct sections, we will cover the following topics:
- Performance measurement considerations for customer journey analytics.
- Once insight is derived, it is a natural progression for brands to run optimization efforts through experiments, testing and refined targeting to improve specific interactions with customers. Whether you prefer a no, low or high-code experience, the presentation will satisfy a variety of personas.
- Finally, as new analytical techniques evolve and gain attention, reinforcement learning has become a hotbed of research and innovation in AI-based use cases. In the context of customer experience, optimizing a journey of interactions, as opposed to a single interaction, has become a prioritized focus area of infusing machine learning into martech for SAS.
Figure 1: Customer Journey Optimization
Jam packed into a 45 minute video recording available below, we will dive deep into the biggest challenges facing the marketing industry. Attribution, segmentation, automated machine learning, and deep reinforcement learning is a sampling of what to expect. As we gravitate to the year 2021, analytically speaking, we are very excited about recent updates regarding analyst validation, product roadmap and vision related to SAS Customer Intelligence 360 and SAS Viya.
We hope you enjoy this fresh showcase of diverse AI capabilities within the SAS platform offering marketing data management, embedded analytics, customer journey activation and impact optimization.
Learn more about how the SAS Platform can be applied for customer analytics, journey personalization and integrated marketing here.
