Contrary to popular belief and tradition, concentrating resources and efforts to improve attributes that reveal a low rating is not necessarily the most effective way to improve satisfaction and loyalty. Though a typical survey will convey data on “what” people think, the real effort is to understand “why” people think the way they do. While regression analysis has been frequently used to analyze survey data, a neural network analysis takes it one step further. Neural Networks, which are part of Artificial Intelligence technologies, operate as a simplified computerized model of the neural architecture of the human brain. Just as the human brain “learns” from repeated exposure to neural stimuli, the Neural Network is also a pattern recognition program. In our application of Neural Networks, the model begins to “learn” in a way that simulates the human decision making process. Development II has developed the methodology of deploying this technology in a way that quantifies the impact of various attributes on overall satisfaction and loyalty.
Because it is accomplished without ever having to ask to rate or rank survey attributes, any contextual biases, inaccuracies, and inconsistencies are avoided.
What can you expect from Quantametrics?
- A neural network based analytical tool designed to identify customer importance rankings.
- Pinpoints key drivers impacting customer satisfaction.
- Identifies meaningful repurchase intentions.
- Recognizes significant inputs to customer loyalty.
- Provides information to confidently set priorities and allocate resources to improve business relationships and increase retention.