We need to execute a bulk CSV ticket import into Intercom without losing historical customer satisfaction scores. What is the exact schema and step-by-step process?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
We need to execute a bulk CSV ticket import into Intercom without losing historical customer satisfaction scores. What is the exact schema and step-by-step process?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 1 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT2 real searches · gpt-6
Intercom CSV import tickets conversations schema customer satisfaction rating historical CSAT import Google ↗
site:intercom.com/help import conversations CSV tickets customer satisfaction ratings CSAT Google ↗
- Historical data migration guide · intercom.com
- Import Tickets · developers.intercom.com
- Tickets · developers.intercom.com
- Export your tickets data · intercom.com
- How to set up ticket types · intercom.com
- Reporting metrics & attributes · intercom.com
- Measure customer satisfaction with conversation ratings · intercom.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Intercom CSV import tickets conversations schema customer satisfaction rating historical CSAT import OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 | |
site:intercom.com/help import conversations CSV tickets customer satisfaction ratings CSAT OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 |