No matter what your brand's level of marketing maturity is, SAS can help you move from data to insight to action with rich functionality for adaptive planning, journey activation and an embedded real-time decision engine – all fueled by powerful analytics and artificial intelligence (AI) capabilities. Let's begin with a
After careful consideration of the evolving COVID-19 situation, SAS made the decision in March to cancel the in-person SAS Global Forum 2020 conference in Washington, DC. The health and well-being of SAS customers and employees was the company's top priority in making that decision, and while it's unfortunate that we
In part one of this blog series, we introduced hybrid marketing as a method that combines both direct and digital marketing capabilities while absorbing insights from machine learning. In part two, we will share perspectives on: How SAS Customer Intelligence 360 completes analytic's last mile. How campaign management processes can easily
The marketing industry has never had greater access to data than it does today. However, data alone does not drive your marketing organization. Decisions do. And with all the recent hype regarding the potential of AI, a successful cross-channel campaign is propelled by a personalized, data-driven approach injected with machine
In part one of this blog series, we introduced the automation of AI (i.e., artificial intelligence) as a multifaceted and evolving topic for marketing and segmentation. After a discussion on maximizing the potential of a brand's first-party data, a machine learning method incorporating natural language explanations was provided in the context
Marketers and brands have used segmentation as a technique to deliver customer personalization for communications, content, products, and services since the introduction of customer relationship management (i.e., CRM) and database marketing. Within the context of segmentation, there are a variety of applications, ranging from consumer demographics, psychographics, geography, digital behavioral
A typical day brings countless business decisions that affect everything from profitability to customer experience. What is a reasonable price point? Which audience segments should I personalize offers for? When should I recommend specific content earlier in a customer journey? Daily decisions like these can alter the trajectory of a
In part one of this blog posting series, we introduced that the analytics lifecycle is much more than authoring models. As brands develop and invest into creating models to solve critical business problems, so does the requirement to manage these assets as valuable competitive differentiators. In part two of this
The universe of customer experiences, digital analytics, personalization and decisioning is massive. At times, it can seem as complicated and vast as the galaxy itself. With intricate subjects underneath this umbrella, you can lose direction, wander aimlessly, or feel a misleading sense of success or failure. When you lose vision,
In parts one and two of this blog posting series, we introduced machine learning models and the complexity that comes along with their extraordinary predictive abilities. Following this, we defined interpretability within machine learning, made the case for why we need it, and where it applies. In part three of
