Let’s start by sharing a generalized definition for "digital analytics" platforms:
In short, they represent specialized analytic applications used to understand and improve digital channel user experience. Their focus ranges across customer acquisition and behavior, as well as optimizing marketing campaigns. The emphasis is on digital channels and techniques yet use cases can evolve to connect with offline data. They are end-to-end platforms performing functions from data collection through analysis and visualization.
It wasn’t long ago where brands operated across the customer lifecycle of acquisition, cross-sell, and retention using assumptions based on years of practitioner experience. Then up and coming analytic talent prior to the data science explosion began challenging those conventions with hard quantitative data. The shift to today is the monetary expenditures associated with capturing and storing 1st party digital data has decreased significantly opening a new realm of innovative possibilities.
Regarding the capture of 1st party digital data, if one doesn’t take a closer look into how digital analytic technologies differentiate from one another, it is easy to assume they do similar things. For example, both Google Analytics and SAS Customer Intelligence 360 can create new 1st party digital data sources for your brand to exploit. But is that it? No, and if one investigates this topic, it is evident that brands have incremental opportunities to generate business value and insight from their digital properties.
Recent martech industry trends revolving around data deprecation will dramatically shift common, well-adopted approaches to customer acquisition, upsell and retention. Now brands need to assess and potentially adapt their practices towards transparency and choice, value to the customer, and relationship depth. As inferred data gets harder to acquire, brands should prioritize their owned data assets and expand their customer and marketing analytic strategies. The availability and quality of your organization's 1st party data ingredients feeds directly into the potential of AI-based marketing and performance…cross-pollinating across multiple technologies enables a brand to leverage the unique strengths of multiple vendor solutions.
In this video we will discuss, explore and demonstrate the commonalities and differences between Google Analytics and SAS Customer Intelligence 360 in how they support modern customer and marketing analytic applications.
Learn more about how the SAS Platform can be applied for customer analytics, journey personalization and integrated marketing here.
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