Detecting negative customer experiences in an early stage to take proactive actions is better than spending money to react to customer complaints.
What action to take was in many cases a debate between different opinions or hypotheses. Money can only be spent once, it is better to spend it on customer experience improvement actions as soon there are weak signals of negative customer experience rather than to wait until there are strong signals of negative customer experience.
How can we monitor customer experience over time and see the impact of proactive customer experience improvement actions?
By quantifying customer experience it is possible to make evidence-based decisions to improve customer experience. The results can be monitored over time to see the impact on customer experience. We developed several tools to solve the business problem.
- Software to aggregate customer experience data into totals for visualization in a BI tool and create an automated process for weekly updating.
- Create a dashboard to visualize KPIs for customer experience.
- Develop a set of customizable tools to analyze customer journey data combined with customer survey results to detect relevant indicators related to the customer experience. Visualize the results in a BI-tool.
In the first step, the dashboard data was prepared in SQL. To add additional features like incremental calculations, we used Python.
Visuals to detect indicators in the journey data.
Acceptable calculation time.
Reduce analysis time for a journey.
Implement incremental calculation for customer experience.
Creating reusable tools for journey analysis.
Evidence-based customer experience results help to focus on improving the service to the customer. It is no longer a debate about opinions and hypotheses. This will eventually lead to more efficient customer journey management.
