CSV is the only file type that can be uploaded to the Keatext text analytics platform.
Your first step to importing data begins with a well-configured CSV file. To learn more about CSV files and preparing your data for upload, click here.
All of your uploaded data sources are accessible on the Sources page of the platform.
Adding a CSV file to your sources
Once your CSV file is properly prepared, you're ready to upload a new data source for analysis. On the Sources page, add your new source from your files on your stored on your computer. Once the CSV file is uploaded, you can start to configure you data fields.
The app automatically detects the delimiter, the fields and the data types used. While typically accurate, it’s a good idea to double-check the data types when configuring the data fields.
Configuring your data fields
Once your CSV file is uploaded, configure the data fields so Keatext can interpret and analyze the data correctly.
Under “Configure fields” you'll see the system has automatically selected “comma” as the delimiter used in your file. If the delimiter hasn’t been correctly auto-detected, choose the right delimiter among the three options in the pull-down menu.
You have the option of giving your dataset a source name: the original spreadsheet file name automatically appears in this field, but can be changed for clarity. For future reference, you have the option to add a brief description of your source. This can be a useful piece of information when working with other people in the same account.
If applicable to your data set, add a primary date (when feedback was originally collected) and commenter ID (a unique customer/employee identifier such as an email or internal customer/employee ID linking an individual across channels). With a primary date, the Keatext system detects time trends, and with commenter IDs, it estimates the number of customers affected by an issue. Currently, these settings can't be changed once you create your data source.
Mapping your data fields
Now it's time to decide which fields to analyze. First, you’ll need to map the data fields in accordance with the configuration of your original spreadsheet. The purpose of this process is to give Keatext accurate information about the original spreadsheet and to identify which spreadsheet fields should be analyzed.
Each field will automatically be named in correlation with the original spreadsheet's fields. Next to each field name, identify that field's data type (as in the original CSV) via a pull-down menu. The options are: Boolean (logic such a true/false and yes/no), string (general characterization, such as language), number (a price or any other numeric value) and datetime (click here for all supported date formats).
Selecting fields for analysis
Perhaps the most important aspect of uploading data for analysis is identifying comment or feedback fields with a check mark. From your original data set, you can see which fields contain comment data that came directly from the customer and which do not.
Fields that do not include this comment data or other direct customer feedback don’t need to be check-marked. Those fields can still be used as filters for meta-data correlation and will be cross-checked by the system.
Keep in mind that you need to select at least one field to be analyzed, and that its data type must be String.
Starting the analysis
Once you've selected the fields to include in the analysis, click the “Add source” box at the bottom of the field list. That’s it. Sit back and relax while the Keatext system gets to work!
If you encounter any problems in the upload process, check that: