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Author's profile photo Kevin McConnell

Enterprise Analytics Uncovers the Predictive Nature of the Customer Experience

For nearly two decades, companies of all sizes, industries, and regions have come to know how data and analytics are transforming the art and science of the customer experience. Perhaps it all started with the 2007 release of the widely popular book Competing on Analytics: The New Science of Winning or Brad Pitt’s charisma in the 2013 movie Moneyball. 

 

Whatever the inspiration, the notion of applying data analytics to understand their customers and provide experiences that keep people engaged and loyal has gripped many executives’ imaginations of what’s possible. Data analysts now leverage extensive use of customer analytics to outperform competitors in terms of profit, sales revenue growth, ROI, and other key performance indicators.

 

So why, after all this time and attention, are companies still challenged to advance their customer analytics capabilities? It’s not a lack of will and determination that’s holding businesses back. The real trouble lies in the elusive ability to turn real-time data into the insights needed to drive meaningful actions and deliver productive outcomes.

 

Designing great customer experiences with predictive analytics

 

Twenty years ago, getting the right data was the issue. Nowadays, the customer journey is so digitalized – from e-commerce transactions and browsing data collection to call center history and chatbot interactions – that experience platforms are used to analyze massive volumes of information in real time.  But that is only part of the picture.

 

Some experts may say that businesses have too much data. But I believe businesses just need a better way to consume this intelligence to gain the insight they need and produce personalized experiences that consistently wow customers.

 

Every day, I meet executives from companies that consume data from their customer experience and line-of-business systems and their suppliers’ and partners’ applications to build extensive analytics models to achieve goals, such as:

  • Allow business analysts to execute accurate forecasts directly in their workstreams
  • Immediately determine factors in operations and experiences that may be impacting desired business outcomes and revenue growth
  • Conduct what-if analysis and build collaborative plans across the departments to explore the potential impact of decisions on profitability

 

Take, for example, Velux. The Danish-based provider of high-quality roof windows and skylights wanted to become a data-driven organization to further enhance product quality. By combining the capabilities of SAP BW/4HANA and SAP Analytics Cloud solutions with its data lake, the company created a single platform that gathers, blends, and models data with predictive analytics. This effort improved data governance and protection, empowered employees to make faster and better decisions with self-service reporting, and extended collaboration capabilities across the enterprise.

 

Grupo Polak is another excellent example of a company that is connecting the customer journey with data analytics. The Mexican conglomerate of four global chemical and agrichemical businesses unified its business processes and data across the organization, optimized communication with customers and suppliers, and enhance executive decision-making with strategic dashboards. By adopting SAP Analytics Cloud along with SAP Sales Cloud and SAP Concur solutions, the company’s employees can better meet customer requirements with access to centralized customer information and become more responsive to customer needs. This implementation also led to automated order validation and inventory management processes and a lower average response time from four hours to just a few seconds.

 

Finding value in the democratization of data

 

While the democratization of data has been a much-discussed topic in recent years, today’s advanced analytics solutions are certainly bringing companies closer to realizing the full potential of enterprise-wide access to intelligence and insights.

 

Businesses no longer have to resort to building visualizations from stale subsets of data. Instead, they can create a customer experience fueled by the right people – in the front office, back office, and field – having the right information they need to make decisions and take actions that satisfy every customer’s expectations.

Watch our demo to find out how SAP Analytics Cloud can accelerate one of the most critical processes in the customer experience.

SAP%20Analytics%20Cloud%20with%20Customer%20Experience

SAP Analytics Cloud with Customer Experience

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