The Future Of Customer Experience Insights
Customer experience (CX) continues to be a key differentiator for many organizations. At the same time, the practice of CX is becoming more quantitative, analytical, and predictive. Data and analytics professionals have a crucial role in evolving the practice of CX. This evolution will require better data, analytics, and collaboration. Few CX teams have the data and analytics capabilities to execute advanced insights strategies alone. Effective partnership with their organization’s data and analytics professionals creates cooperation that helps benefit the entire business by improving customer understanding and providing high-value use cases for advanced data and analytics solutions.
The Missing Linkages To Predict Customer Behavior
Organizations need actionable insights to improve CX. They must leverage more diverse data and advanced analytics to produce these insights. Unfortunately, most organizations we work with lack the data infrastructure and analytics resources they need to develop effective customer insights. Individual business units tend to focus on generating insights from the domain-specific data they measure directly: operational insights in ops, sales and revenue insights in sales and marketing, and financial data siloed in finance. This includes customer experience programs focused on generating insights based solely on the feedback they collect from customers. These data disconnects impede the organization’s progress toward understanding customer behavior. Organizations must combine data from business functions with customer perception data and financial outcome data to produce predictive models of customer behavior.
How To Integrate Experience Data For More Predictive Analytics
To overcome the challenges of disconnected customer data and build a foundation for advanced, predictive CX analytics and insights, data professionals need to partner with their customer experience colleagues to produce holistic customer insights models.
There is a four-step process that data and insights professionals can leverage to create advanced customer insights models. At a high level, the steps are:
- Combine perceptions, interactions, and outcomes. What customers think and feel about their experiences is combined with what happens to the customers during their interactions with the business and what they ultimately do because of their experiences.
- Conduct data exploration and modeling. Combined customer data sets are statistically tested, refined for fit, and modeled to triangulate the cause and impact of changes in experiences.
- Analyze relationships to predict behavior. Holistic customer data models can then be used to predict behavior, prioritize improvements, and prove the value of CX to the business.
- Operationalize insights to drive action. The job of data professionals and their CX colleagues isn’t complete until enhanced analytic capabilities deliver win-win outcomes by improving business performance through elevated experiences.
Data professionals should start planning how best to support their organization’s customer experience and insights needs. By working with CX professionals, they can collectively provide the best analytics and insights for their organization. Data professionals are critical in joining customer perceptions, interactions, and outcomes into holistic models. These predictive models will enable the organization to tie customer experience improvements to improved financial performance for the business. They will also provide high-visibility uses for quickly evolving AI-based predictive tools and techniques.
To learn more about how CX and data professionals can work more closely to ensure that they collectively provide the analytics and insights their organizations need to improve experiences, register to attend Forrester’s Data Strategy & Insights Forum here.
This post was written by Senior Analyst Rich Saunders and originally appeared here.
Read the full article here
