211 Data Visualization

Seeing that the mid-project review is next week, we have really been focusing on creating visualizations of the data we have collected so far.  These visualizations will not only help us present the findings of our project but also help us propose changes to the call menu based on our analysis.  Analyzing the data will also help us create a predictive model for the number of calls for a given day of the week, month, and year.


Calls per Year

This is the number of calls per year from 2011-2014.  The decrease in the number of calls is due to the introduction of email, text, and chat services.


Calls per month

This is the number of calls per month from 2011-2014.  Peak months include the summer, as people look for assistance with childcare and summer camps, and October, as people seek assistance with purchasing gifts for the holidays.  February has the fewest calls, as many people receive income tax refunds in January and therefore need less assistance the next month.


Calls per day

This is the number of calls per day for each day of the week.  Most calls occur on Monday and decrease as the week goes on.  This is because people prefer to seek resources earlier in the week so they have more time in the week to explore the options the agents direct them to.


Call dropped time

This plot illustrates the time callers spend in the menu before hanging up.  Most callers abandon the call between 5 and 10 seconds, during the first spiel of the call menu.  The percentage of abandoned calls hits a local maximum around one minute, which is during the second spiel of the call menu.


Weather conditions

This is a plot of the number of calls received in 2013-2014 based on weather conditions.  Weather conditions such as snow, fog, and thunderstorms increase the number of calls received.