Great customer experience relies heavily on understanding the customer’s context and emotional journey. So, for instance, a 1st-time mortgage application is generally done with high levels of anxiety for 1st-time buyers who are eager for the bank to approve the loan. If you can both state manage(i.e do you know at all times what the status is and when it changes) a customer through the process and identify how to support how they feel in the process. Also one cardinal rule, never ask for data you have already :)
I think taking random sample of customers and meeting them face to face and listen to what they say
Hi Carlos, In my humble opinion you would have to segment your customer base first. What is good experience for one segment may not be so for another segment. For example a customer in 25-35 years of age may look for quick service and may be happier using self care features, where as some one older (50-60 years ) may want the customer service executive to sit down with him and explain the product/service features in detail. So first segment or group different types of customers, then do a dipstick to understand how do they view their current customer experience and what are they looking for to decide on your tactical move.
From a strictly analytical point of view I could say:
First step: customer base clustering with respect to main topics of your business goals (i.e. service consumption, spending, burstiness of habits), very helpful to shape behaviors
Second step: entropy analysis of basic phenomena (segmentation of raw data into significative ranges of the main variables then association with entropy of data taking care also the outliers that carry high entropy). Traditional statistics sometime tells lies or hide data that have heavy tail distribution that could be smoothed by stats.
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