451 Research Analyst Sheryl Kingstone, and Cloudera’s Steve Totman recently discussed how a growing number of organizations are replacing legacy Customer 360 systems with Customer Insights Platforms (watch the replay here). In this blog post, Sheryl outlines how next-gen CIP applications are delivering a better customer experience, and why businesses are relying on CIPs as their preferred path to customer insights.
The abundant growth of data, maturation of machine algorithms, and future regulatory compliance demands from the European Union’s General Data Protection Regulation (GDPR) will shift the landscape for creating a single source of the truth for customer data. Historically, companies used combinations of CRM systems, master data management (MDM), and data lakes to create that one source, but all have failed to live up to the expectations, especially for front-line business users in areas such as marketing, customer care, and digital commerce. Businesses have primarily invested in systems of record, such as legacy CRM and ERP, to serve this purpose. While these types of systems are critical for managing internal operational processes, they are typically not effective for consolidating customer information at the rapid pace of business change. Additionally, they only provide one piece of the puzzle.
Structured data from operational data stores now provides a small slice of the overall data needed to improve customer experience. IT departments previously invested in MDM and data warehousing technologies to consolidate information associated with customer profiles. However, the emergence of additional unstructured data, further relegated traditional CRM, MDM, and other systems to just another silo. This further illustrated the need for next-generation marketing platforms that leverage all available data to deliver a better customer experience.
Looking ahead, it is clear that the new requirement will be an investment in customer intelligence platforms (CIPs). These next-generation applications do more than consolidate a single view of the customer; they add a layer of data governance, synthesis, and identity, which powers a dynamic customer graph to fulfill the vision of contextual experiences. Additionally, CIPs utilize technologies such as machine learning and AI to quickly and accurately deliver customer insights to the organization and enhance the experience for the customer.
Advancements in predictive ML intelligence build on a variety of algorithms to achieve real-time, one-to-one capability, ideally in fewer than 20 milliseconds (see Figure below). CIPs are not just about the data, but also the potential for delivery of dynamic rich media content, including images, videos, and voice, which can greatly differentiate and influence the customer journey.
Customer Intelligence Platform For Next-Gen Customer 360
Source: 451 Research
Improving customer experience demands an approach that takes into account all of the tools, processes, and data across the customer journey. This complex process usually involves dynamically maintaining a single source of truth about each customer to drive personalized experiences based on individual preferences and behaviors.
Why is this important? Because it’s virtually impossible to plan for all potential customer journeys because each is essentially a nonlinear, self-directed interaction across a customer’s channel of choice. Given that 80 percent of online purchases in 2018 will be influenced by mobile technology and that, within a decade, the average person will have more conversations with bots than other humans each day, organizations must rise to the occasion to deliver differentiated customer experiences that increasingly demand real-time context and user preferences to enable personalized customer experiences.
Cloudera’s Customer Insights solutions employ analytics, machine learning and AI to drive strategic growth. Email us to learn more about how both our pre-built, and custom solutions empower organizations to unlock the power of their data to better understand customers, learn from their behaviors and deliver relevant interactions.