Birdie will handle different data structures to support feedback analysis.
Feedback:
Feedback are records containing one piece of comment, usually associated to a score or rating. Ex.: NPS and CSAT Responses, Reviews, etc.
All feedback sources will potentially have the following Core fields and, depending on the Feedback kind, they may have additional ones, as described:
Core fields - For all Feedback kinds |
|
| This is a unique identifier for the feedback record. It's an important piece of data to avoid duplication once you need to reprocess a record to incorporate additional fields, for example. |
| This is consistent identifier for the user, author of the feedback. This field will be used to match feedback records with customer records when importing. customers and users profile and behavior data. |
| This is consistent identifier for the account associated to the author of the feedback. This field will be used to match feedback records with customer records when importing. customers and users profile and behavior data. |
| This is the main field. The feedback comment itself. This field will be processed and enriched along the AI pipeline |
| This is an eventual title of the feedback. Some kinds as Reviews allows the user to publish a title and a main comment. |
| This is the score associated to the feedback. It will assume different formats and calculations depending on the feedback kind. Ex.: Review records will calculate this Rating field as a Star Rating (avg 1 to 5 stars), NPS records will calculate this Rating as an NPS Score (%promoters - %detractors) |
| This is the publishing date. It will be used to place a feedback record in a timeline for analysis. |
NPS or CSAT |
|
| Name of the user (optional) |
| Name of the Survey |
Conversation:
Conversation are records containing a collection of comments between two or more participants. It's a common format in Support tickets, Issue reports or Social Forums and Posts.
All conversation kinds will potentially have the following Core fields and, depending on the Conversation kind, they may have additional ones, as described:
Core fields - For all Conversation kinds |
|
| This is consistent identifier for the conversation. It typically groups individual messages within a conversation. Ex.: Ticket ID, Forum thread, etc |
| This is consistent identifier for the unique comment within the conversation. It's important to avoid duplication as you reprocess the conversation. |
| This is consistent identifier for the account associated to the author of the feedback. This field will be used to match feedback records with customer records when importing. customers and users profile and behavior data. |
| This is consistent identifier for the user, author of the feedback. This field will be used to match feedback records with customer records when importing. customers and users profile and behavior data. |
| This is the main field. The feedback comment itself. This field will be processed and enriched along the AI pipeline |
| This is the publishing date. It will be used to place a feedback record in a timeline for analysis. |
Support tickets fields |
|
| Subject of the ticket |
| Status of the ticket |
| Priority of the ticket |
| Channel of the ticket (ex.: email, chat, phone, etc) |
| Name of the user |
| Type of the user. This is used to split customers, support agents or bots |
Issue report fields |
|
| Issue title |
| Id of project or product |
| Name of the project or product |
| Status of the Issue report |
| Name of the user |
Social Media Post |
|
| Post title |
| Channel of the Post |
| Owner of the Post |
| Tag collection, associated to the Post |
| Category of the Post |
| URL to the Post |
| Name of the user |
| Type of the user |
| Number of interactions (likes, upvotes, depending on the platform) |