The Statistics Module. Identify & populate missing data in your lists

The Statistics Module. Identify & populate missing data in your lists

The Statistics Module will quickly help identify missing data in your lists, simply and effectively. This can be great for finding out how much of your data is fully populated (eg. How many missing names or postcodes exist on your list, how many contacts have missing email addresses?,etc). Fully populated name and address details is crucial for effective marketing, and this module will help with that. Featuring a score table and score graph, you will be able to quickly view how many records in your list/s have been populated and not been filled in. This module alone could potential save you money on wasted postage (contacts with missing name and address details).

A quick 6-step guide into using the Statistics Module:

Step 1: After importing your list, click the 'Clean' button, as shown below.


Step 2: All the columns will be automatically transferred into the 'Selected Columns', but you can alter this if you wish. Simply then select either the 'Populated Cells' or 'Empty Cells' option from the pull-down menu, as shown below.


Step 3: By clicking the 'Chart Type' option box, you can select 4 different charts that will highlight the results.


Step 4: Understanding the Results - Take a look at the results grid, highlighted below.


Because we selected the 'Populated Cells' option, we can see that the column 'FirstName' has a score of 100%, which means every record in the 'FirstName' column has been filled. Now, lets take a closer look at the 'Surname' column, which has a score of 88.24%. How do you view all the records that have been populated? Well, the answer is simply to double-click on the column name.

Step 5: As we double-clicked on the 'Surname ' column, this will then automatically filter the data, to show all the records that have 'populated cells' within the 'Surname' column. You are now free to view/edit/delete your data list. Suppose now you would like to see the records that have not been filled in on this ;Surname' column. Click 'Clean' button at the top-right to go back onto the 'Statistics Module'.


Step 6: Simply choose 'Empty Cells' and then click 'Refresh'. You will now see that the 'Surname' score is now 11.76%, which indicates that there are a number of records that have not been entered. As before, double-click the column name on the score table to filter the records, of which then you can enter the missing records.