Edit data directly in MarketSight®

Clean or edit data in MarketSight using Data Views. Responses are laid out in rows with corresponding variables in each column. Simply click on the cell containing the data point you wish to edit and select the response from the drop-down or enter a new one.

Data Views also allows for entire record deletion, which is an excellent way to remove outliers from the dataset or normalize a set of responses for easier analysis.

This powerful, time saving feature can be turned on or off for certain users or groups, so you never have to worry about unauthorized changes to your data.

editing survey data
editing survey data

Create new variables in MarketSight

Using simple point-and click tools, it's easy to create new variables in your uploaded dataset. For example, if you know each respondent's age and you'd like to create certain age groups, such as: Under 18, 18-24, 25-34, etc., it's easy to do that in MarketSight by creating a Regrouping Variable.

You can also create a Conditional Variable, using Boolean logic to combine different variables to create precise market segments for analysis and reporting.

MarketSight enables you to create and save filters, work with multiple response questions where respondents "check all that apply", and supports grid questions, which mirrors how they are laid out in the survey.

Edit Codes and Labels

Once a dataset is uploaded, you have full control over how each variable, and its corresponding values, are displayed. Add or edit a variable's name for easier identification, and include the original question text in the variable's description field.

The "Edit Variable" window lets you specify the appropriate category and default calculation method used for each variable. Organizing your variable list helps improve your workflow when building crosstabs, as full groups of variables can be added to a crosstab with one gesture.

MarketSight allows you to rename or recode the values of your variables. If your dataset contains similarly structured variables, you can apply the same value name or value code changes to multiple variables at once. Specifying a missing value for a variable is very easy and allows you to denote values that should be omitted from calculations.

Read more about Crosstabs.

editing survey data