Over the last 20+ years, global society has adopted digital devices at scale, and consumer interaction behaviors continually evolve and mature. As analysts, we're uniquely positioned to notice worldwide trends, country-specific nuances and localized market behaviors that can have significant impact on our brand's business goals. This global scope is more significant now than ever before as the proportion of connected users continues to grow, and the expansion of Internet-enabled devices is undoubtedly a massive catalyst for change.
Customer engagement levels vary throughout the journey with a brand, driven by segmented usage patterns across smartphones, smart watches, tablets, desktop computers and other connected devices. Over the last few years, despite the massive uptick in mobile device usage, desktop consumption is not disappearing. Instead, its role is transforming to best fit the customer journey. In short, mobile is not replacing desktop. Instead, customers are spending incremental time on a diversifying ecosystem of digital devices.
Time is not the only variable increasing either. New segments are emerging, such as digital-only audiences, or younger demographic consumers. Marketing and segmentation have always gone hand-in-hand, yet the proliferation of devices is only stressing the increased importance within this area of customer analytics.
Digital analytics, mobile analytics, or journey analytics -- the label doesn't matter. Customer analytics teams must embrace the practice of collecting first-party user behavior data, determining intent from those metrics and taking action to improve acquisition, engagement and retention rates. Regardless of device type, desktop vs. mobile browsers, native iOS or Android applications, cross-platform interactions must be available for machine learning and AI application to successfully nurture customer experiences.
The term "marketing data management" describes how SAS Customer Intelligence 360 can enhance and extend customer data activation, while allowing users to move beyond a traditional customer data platform with our hybrid architecture. With that said, I invite you to view a video that will address the following topics on how SAS:
- Delivers customer device usage analysis.
- Enriches other types of analytics (i.e. segmentation, churn analysis) with device usage analysis.
- Reconciles customer identity across devices and channels.
- Provides a device ID graph.
- Determines identities.