Play 9: Create Descriptive, Predictive & Prescriptive Data Analytics

Leverage data analytics for constantly changing insights

Data is a key resource for improving performance in useability, compliance, operations, and security. Analytics is leveraging these data for gaining insight by asking the right questions. Data Analytics is an evolutionary process where the insight needs of an organization are constantly changing as its capabilities grow and mature, and the ability to process data improves over time. 

Data is not valuable by itself. Collecting data is easy. It is the actionable patterns, relationships, insights, categorization and predictions derived from the data that make it valuable. Taking action in a timely way in response to events requires an analytics-based platform and team, as well as oversight that can evolve and empower organizations by turning data into a competitive advantage through insight.

There are three main categories of data analytics that tend to evolve together and build on one other as the knowledge of analytics within an organization increases.

  1. Descriptive Analytics – What happened? Ask questions in hindsight.
  2. Predictive Analytics – What will happen? – The data can provide insight about the future
  3. Prescriptive Analytics – What will make it happen? The data provides foresight into what will be needed to foster the desired outcome.

data analytics evolution

Customer Intelligence

To respond quickly and accurately to the pace of change and shifting customer demands, it is beneficial to make decisions based on a single source of customer intelligence across all products and activities.

  • Identify relevant sources of User Experience data. These could include:
    • ERP data – interconnected management of specific business processes
    • CRM data – sales staff feedback
    • Customer satisfaction surveys
    • Existing website data
    • Email or SMS data
    • Transaction data
  • Unify around a shared common analytics platform
    • The technology powering the dashboards must be capable of weaving together disparate data sources
    • Predictive analytics to drive data-driven CX decisions


  • Tie stakeholder goals to questions and KPIs
  • Build a high performing team dedicated to analytics
  • Understand the data from the analytics point-of-view
  • Make data compliance an integral part of analytics
  • Implement continuous refinement and validation
  • Bake in organizational changes needed for data governance
  • Implement insights with data storytelling and change management


  • Does your analytics platform allow you to determine what happened in the past by answering questions in hindsight?
  • Is your analytics platform able to forecast what will happen and provide insight about the future?
  • Is your analytics platform capable of predicting what is needed to make desired behavior happen?