Customer Experience Tools
Online or mobile behavior trackers help companies identify customer trends or behaviors via analysis of web traffic and other digital data. Mining such data, if it is high quality, can generate a lot of value.
Customer behavior analysis provides insights into the variables that influence an audience on a digital interface. It gives an idea of the motives, priorities and decision-making methods being considered during the customer's digital journey.
How companies use online/mobile behavior tracking
- Identify correlations between segments that inform customer prioritization segment value.
- Identify key challenges and friction points across stages of the customer journey that lead to detractor behavior.
- Identify surprising or delightful moments during online user activity that create promoters and drive share of voice.
- Automate insights by using machine learning to go beyond correlations and better understand causality.
- Improve the customer's overall value by identifying ideal customer characteristics.
- Improve the level of personalization of content, online advertising, products and services.
- Develop new product and service offerings in line with emerging trends.
- Step-by-step implementation. It is essential to do things in the right order; clearly define the business and analytics goals underlying the implementation of behavior tracking.
- Define the right key performance indicators (KPIs). Companies can easily be overwhelmed by the data received from such tools; defining and aligning stakeholders on KPIs helps focus investments on what matters most.
- Dig deeper. Using a behavior tracker is only one step when analyzing customer behaviors. These analyses should be complemented by retention analysis, acquisition improvement or next-best-action or propensity models.
- Quality insights from data. Companies should define how to use artificial intelligence and machine learning models that can synthesize data and learn from consumer behavior to define better qualitative insights.
- Define Elements of Value®. Define a process that uses machine learning to assign specific Element of Value based on verbatim feedback.