A lot of customer text data you want to analyze comes in CSV format. Free form responses in NPS, CSAT, and in-app surveys, as well as product reviews are some examples.
CSV documents, however, don’t all come formatted in the same way.
To speed up CSV data ingestion so you can start asking questions faster, here are tips for formatting the data before you send it our way.
Data sent to us for ingestion should have rows of entries with the following columns:
Any customer segmentation data for respondents. Some examples include:
Any metadata that applies to the textual comment itself. Some examples include:
The ID of the piece of data from the source tool, i.e. the ID of a Zendesk ticket or Delighted survey.
The Comment column is where free text data will be captured. It doesn’t have to be labeled Comment specifically but it should be labeled the way you’d like to see it appear in Viable.
These are some of the acceptable timestamp formats:
The Unique ID column should include the end user’s email address, user ID, or other unique identifier if applicable. If no unique user identifier is available, we’ll associate the data to a uniquely identifiable Anonymous user.
Customer traits and metadata should be formatted similarly to each other by labeling the column as the type of trait or metadata (e.g. CSAT Score, NPS, Location, Age), the way you’d want to see it in Viable; that is how it'll show up as filters in Viable. For example, a location trait column should be labeled Location rather than user_geo_listed.
The cleaner the column header in the CSV, the cleaner it will appear in Viable.
Data within a trait or metadata cell: if a cell contains more than one trait or metadata value (e.g. “design system, Figma, Jira” for metadata column Tags), these values should be separated by a comma.