To maximize engagement, MetroQuest tries to remove any possible barriers to participation. This means that MetroQuest does not require email sign-ups or restrictions on IP Addresses. Instead of enabling restrictions on your Site, it is recommended that you filter your data set to fit your criteria after your engagement period is over.
There are several reasons why filtering your data is useful, but the most common use for this is to make sure that there isn’t a case of ballot-box stuffing.
Ballot box stuffing, in this case, is defined as a participant or a group of participants attempting to sway your survey results by making multiple repeated entries on your Site.
Filtering out duplicate data entries isn’t too challenging, but it can take a bit of time to review the entries and judge which should be removed from your data.
How to filter your Data Set:
- Open the CrossTab data excel file, available from the Data Center on the Welcome tab in the bottom right corner.
- Sort the entire dataset by IP address, then by time. Keep in mind that multiple entries from one IP address could be a library computer, a household computer, or a device shared amongst friends and those responses could all be valid. Sorting will group together matching IP’s so that you can scan through and look for large groups of visits from the same device. Next, you can highlight the column and choose Conditional Formatting by -> Highlight Cells Rules -> Duplicate Values -> Highlight. This will highlight the cells that repeat so that you can hunt down larger groups easily.
- Check the times they were submitted, as a first-time participant should take 5-10 minutes to complete the survey, but a repeat participant knows where to look and what to click and will generally complete the survey in 2-3 minutes.
- It is also recommended to look for response patterns. If you’re concerned about 2 responses being duplicates, check if the rating/ranking patterns are extremely similar. If they have vastly different patterns, they may not be duplicates.
- If you find a duplicate response from the same IP address, within a very short time frame, with very similar responses, you should delete the row from your dataset.
- You’ll need to use this new document for your data analysis, as the Data Center will still reference the full data set.