Comments on: Things that go Bump in the Night – a “Negative” (subtractive) alternative approach to Customer Service Modelling and Monitoring http://dsanalytics.com/dsblog/things-that-go-bump-in-the-night-%e2%80%93-a-%e2%80%9cnegative%e2%80%9d-subtractive-alternative-approach-to-customer-service-modelling-and-monitoring_141 Data Analytics- the art and science of analyzing data Thu, 11 Mar 2010 08:31:01 +0000 http://wordpress.org/?v=2.0.1 by: Analytical Engine » Exploring a New Way to Think about Customer Satisfaction http://dsanalytics.com/dsblog/things-that-go-bump-in-the-night-%e2%80%93-a-%e2%80%9cnegative%e2%80%9d-subtractive-alternative-approach-to-customer-service-modelling-and-monitoring_141#comment-12071 Fri, 15 Aug 2008 15:22:24 +0000 http://dsanalytics.com/dsblog/things-that-go-bump-in-the-night-%e2%80%93-a-%e2%80%9cnegative%e2%80%9d-subtractive-alternative-approach-to-customer-service-modelling-and-monitoring_141#comment-12071 [...] In most organizations, customer satisfaction score is a nebulous measure and hard to map back to improvement opportunities (due to overall high scores across the board). Simplified customer satisfaction measures like net promoter scores are neither accurate nor actionable. Hence it was very refreshing to read John Aitchison’s post on how he is starting to think about customer satisfaction. [...] […] In most organizations, customer satisfaction score is a nebulous measure and hard to map back to improvement opportunities (due to overall high scores across the board). Simplified customer satisfaction measures like net promoter scores are neither accurate nor actionable. Hence it was very refreshing to read John Aitchison’s post on how he is starting to think about customer satisfaction. […]

]]> by: Amaresh http://dsanalytics.com/dsblog/things-that-go-bump-in-the-night-%e2%80%93-a-%e2%80%9cnegative%e2%80%9d-subtractive-alternative-approach-to-customer-service-modelling-and-monitoring_141#comment-12049 Thu, 14 Aug 2008 19:40:05 +0000 http://dsanalytics.com/dsblog/things-that-go-bump-in-the-night-%e2%80%93-a-%e2%80%9cnegative%e2%80%9d-subtractive-alternative-approach-to-customer-service-modelling-and-monitoring_141#comment-12049 John, A very interesting post which makes a lot of intuitive sense. We have experimented a lot around mapping the individual complaints to an actionable list when we do a inbound call monitoring of customer service channels (especially retention queues). We normally start with a top down hierarchical tree structure of root cause categories of dissatisfaction (e.g. product,process issue, returns process) and then map the individual responses to the categories. We have found this to be a very insightful exercise. However, your idea of trying to develop a customer satisfaction metric from this type of data is certainly an area worth exploring. Amaresh John,

A very interesting post which makes a lot of intuitive sense.

We have experimented a lot around mapping the individual complaints to an actionable list when we do a inbound call monitoring of customer service channels (especially retention queues). We normally start with a top down hierarchical tree structure of root cause categories of dissatisfaction (e.g. product,process issue, returns process) and then map the individual responses to the categories. We have found this to be a very insightful exercise.

However, your idea of trying to develop a customer satisfaction metric from this type of data is certainly an area worth exploring.

Amaresh

]]> by: John Aitchison http://dsanalytics.com/dsblog/things-that-go-bump-in-the-night-%e2%80%93-a-%e2%80%9cnegative%e2%80%9d-subtractive-alternative-approach-to-customer-service-modelling-and-monitoring_141#comment-11742 Tue, 05 Aug 2008 09:36:22 +0000 http://dsanalytics.com/dsblog/things-that-go-bump-in-the-night-%e2%80%93-a-%e2%80%9cnegative%e2%80%9d-subtractive-alternative-approach-to-customer-service-modelling-and-monitoring_141#comment-11742 It is worth, also, looking at expectancy disconfirmation theory eg http://goliath.ecnext.com/coms2/gi_0199-5990994/Testing-the-expectancy-disconfirmation-model.html For case based reasoning/ case based explanation, the most up to date set of references I can find is Artificial Intelligence Review Volume 24 , Issue 2 (October 2005) Special Issue on Explanation in Case-Based Reasoning but it is not,unfortunately, free An interesting paper I found was "Case-Based Explanation of Non–Case-Based Learning Methods" http://www.amia.org/pubs/symposia/D005808.PDF which focuses on the problem of how to turn models (eg decision trees) into a semblance of "case based reasoning" .. seems very sensible, and a promising way of communicating complex models It is worth, also, looking at expectancy disconfirmation theory
eg
http://goliath.ecnext.com/coms2/gi_0199-5990994/Testing-the-expectancy-disconfirmation-model.html

For case based reasoning/ case based explanation, the most up to date set of references I can find is

Artificial Intelligence Review
Volume 24 , Issue 2 (October 2005)
Special Issue on Explanation in Case-Based Reasoning

but it is not,unfortunately, free

An interesting paper I found was
“Case-Based Explanation of Non–Case-Based Learning Methods”
http://www.amia.org/pubs/symposia/D005808.PDF

which focuses on the problem of how to turn models (eg decision trees) into a semblance of “case based reasoning” .. seems very sensible, and a promising way of communicating complex models

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