SAS Customer Intelligence 360: Marketing AI Vision

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Your brand is customer journey obsessed, and every interaction with your company provides a potential opportunity to make an intelligent decision, deepen engagement and meet conversion goals. The hype of martech innovation in 2020 is continuing to elevate, and every technology vendor is claiming the following statement:

"Bolster the customer experience with AI."

Problem solved, right? However…is all AI built the same? No. A better question to address is:

What do we actually want AI to achieve?

It will vary from brand to brand. Ultimately, we’re all trying to improve and progress, which means we're measuring our performance in accordance with a variety of metrics.

1. There are positive drivers like sales, acquisition rates, awareness, engagement and customer lifetime value, which depend on techniques like unsupervised and supervised segmentation, recommendations, propensity-based targeting, testing and more.
2. In addition, it’s equally as important to keep negative drivers in check, such as promotion, offer and retention costs using techniques like attribution, forecasting, and prediction.
3. Ultimately, an optimal balance is required.

The analytically-driven marketer plays a critical role in driving this through the use of AI and machine learning to facilitate better customer interactions.

Every brand desires to maximize different flavors of conversion events, like a product purchase, making a donation, or signing up for a contract. Here are a few items to consider:

• There is streaming data available about our customer right now.
• Customers expect brands to know what has happened in the past.
• So, we can use that, along with our potential targeting actions and anticipated financial impact to make the right decision.

That’s easy, right?

[video]

In this video, we dive deeper into this subject by presenting the marketing AI vision for SAS Customer Intelligence 360, and how our technologies have evolved to help brands solve some of today's toughest marketing challenges.

To learn more about how the SAS platform can be applied to other marketing and customer-centric use cases, please check out additional posts here.