A common analysis parses customer feedback to identify problems or causes of dissatisfaction. For example measuring the sentiment (positive or negative) of a hotel guest after a stay. This is an important metric for the hotel management along with identifying the root cause of that sentiment. However, I hope that we pay enough justice to these applications and consider all of their capabilities and potential. Otherwise our vision could be too narrow and a narrow vision is risky for adopters, providers and the industry in general.
The vendors of Customer Experience software and methodologies offer depth that goes beyond the simplistic example of customer sentiment. In my opinion Customer Experience needs to be analyzed in the context of Customer Life-cycle and Customer Value.
Once we have identified and ranked the key factors that drive customer's sentiment, we need to look at those rankings across a number of dimensions, including time and geography but most importantly customer segment. After tracking both sentiments (both positive and negative) across customer segments we need to overlay financial metrics at the customer level and at the company level. How is this sentiment affecting profitability and how big is the impact. For instance "... because the A/C was too loud in these locations, our business traveler segment reduced their number of stays by X which caused a drop in margins of Y ..." These type of analysis would offer a clear and meaningful ROI analysis to justify and champion initiatives to manage and improve Customer Experience. The next step of course is enhancing these analysis with predictive analytics to create stronger leading indicators and react before the problems appear.
Comment on this blog or email if you have any thoughts on this topic. If you are a vendor and have a case study that touches on these topics let me know as well, I'd love to write about it in this space.
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