I am trying to explore the relationship between a customer satisfaction rating and a response time (in days). I have been using linear, logistic and quantile regression, to no avail. I believe the issues lies with the distribution of the data. 85% of respondents give a 9 or 10 rating (regardless of response time) and 70% of the data lies in the 9/10 rating and the 0-4 day response time.
Since the data is so negatively skewed, I'm looking for some advice on whether or not to normalize the data and if regression is the right method to define the relationship between the variables (and if not, what would be a better method).
I've attached a summary of the data distributions percents. The range for the rating is 1-10 inclusive and the response rate is continuous, but we limit to 10 days because of low volume for 10+ days. Any assistance is appreciated.