3. The Future of Real-Time Decisioning for Marketing
Enterprise decisioning engines have come a long way and are able to truly transform the way a company interacts with customers. Modern decisioning systems go beyond rules-based decisioning to leverage machine learning and AI to enable hyper personalized messaging and next-best-action decisioning. When implementing a decisioning system, marketers need to consider capabilities and scale across the whole decisioning ecosystem – from data ingestion capabilities and a marketer-friendly environment for designing decisions, through a scalable way to incorporate analytics and machine learning, through flexible deployment capabilities and monitoring and governance to ensure that they continue to get maximum performance on their offers.
4. Responsible Innovation in the Age of AI
In an age when a growing number of decisions are taken by algorithms and AI, the importance of building trust in the technology and data behind it is critical. Artificial intelligence and machine learning can be powerful tools in a marketer’s toolbox and help build and activate attribution and retention models, hyper-personalisation, and smart customer journeys. However, upcoming legislation and the need for both regulatory compliance and building trust in consumers, means that organisations will have to enact ethical and transparent data practices. Enterprises rely more and more on platforms like SAS to provide an environment where data can be ingested, stored, processed, consumed and disposed of in an ethical and compliant way.