Residential cleaning startup Clean Slate Mates had an issue where independent contractor cleaners were cancelling accepted cleaning jobs last minute.
These last minute cancellations were hurting customer relations and overall business opportunities.
In this, Clean Slate Mates wanted to find out the cause(s) of such cancellations.
Along with recorded data from Clean Slate Mates and the python libraries pandas, numpy, and matplotlib, we were able to clean and graph the collected data.
Based on the graphed data, Clean Slate Mates concluded that cleaning jobs that totaled 8 and above tasks were highly likely to be cancelled by the independent contractors.
As a result, Clean Slate Mates adjusted cleaning jobs to require 2 contractors for jobs with tasks totaling more than 8. This drastically reduced the “time per cleaning” metric and resulted in 0 cancellations for the next 4 months.
Consequently, CSM was able to retain 8/10 customers cancelled on and used this opportunity to increased business operations in security and customer relations.
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