C . Sort the data by selling agent ( A to Z ) and then by asking price ( largest to smallest ). D . Convert the sorted data back into a range , and create a summary report showing the total asking price and total selling price by selling agent . E . Create a column chart that shows the difference by agent between asking price and selling price . STEP 4 : Filter the Data A . Create another copy of the original sales data . Rename the sheet Filtered Data . B . Convert the range to a table , and then filter to show only those properties sold in Miami by agent Carey . STEP 5 : Apply Conditional Formatting You determine that one measure of how well the company " gets your price " is to set a scale . Excellent performance is at or above the asking price . Good performance is between 95 % and 100 %. Below 95 % is average performance . You will create conditional formatting rules to display graphically the performance level for each sale . Make a copy of the original sales data chart . Name the new sheet Conditional Format . A . Select the data range and insert a table . B . Use Advanced Formatting to set up the following conditional formatting rules for the field Percent of Asking Price .
• Greater than or equal to 100 % = GREEN
• 95 % to 99.9 % = YELLOW
• Less than 95 % = RED C . Use Percent of Asking Price as the Sort Key , and sort by color with green first , then yellow , and then red . STEP 6 : Create a Pivot Table Now that you have sorted , subtotaled , filtered , and conditionally formatted the data , you have a few more questions to answer . You want to see average percentage of selling price by agent and by city . This will allow you to see whether there are any patterns based on the city or based on the salesperson . To do this kind of comparison , you decide to create a pivot table .