Connect ChatGPT to PostgreSQL

Create the ChatGPT source, then register PostgreSQL with its host, database name, username, and password. Link both through a datastream and target the "answers" table in the job.

Select concrete ChatGPT fields such as Citation Bonus, Frequency Score, Position Modifier, and Day of the month. You can rename the chosen columns, preview the result, and write them to PostgreSQL tables such as monitors, brands, and prompts.

Configure the initial ChatGPT period separately from the recurring schedule for "answers". The source API determines how much history is available.

Choose an eligible date field as the partition for ChatGPT. Catchr can then replace the matching period in "answers"; without it, later runs append rows and may create duplicates.

With ChatGPT data, a PostgreSQL query can summarize visibility score, average position, and citations by monitored brand. Use Citation Bonus and Frequency Score in a PostgreSQL view to create a reusable reporting layer for client analysis.

Yes. Connect an existing PostgreSQL database first. The Catchr job creates and populates the destination table you configure inside that database.

Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.