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Google Play Review
Selected accounts
Configured job
Snowflake
Destination table
Join marketing, finance, CRM, and product data inside the same warehouse.
Metrics availables
Dimensions availables
Google Play Review
3 advertising accounts
Connected
Google Ads
2 advertising accounts
Connected
Google Analytics 4
1 web property
Connected
HubSpot
1 CRM portal
Connected
Add the account host, user, and database schema. Use a password for compatible users or a PEM private key for service accounts and stricter policies.
Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your PostgreSQL table.
This example summarizes review volume and average rating by location over the last 30 days.
Each connector has its own entities, fields, historical limits, and reporting uses. Open a source page for the details that belong to that platform.
Answers about PostgreSQL setup, available source data, schedules, table updates, and SQL use cases.
Start with a connected Google Play Review source and an existing Snowflake database. Create a datastream between them, then configure the accounts, fields, schedule, and "ratings" table.
Select concrete Google Play Review fields such as Average Rating, Helpful Votes, Rating, and Day of the year. You can rename the chosen columns, preview the result, and write them to Snowflake tables such as review sources, locations, and reviews.
Set an initial fetch period for Google Play Review, then choose the frequency and lookback window for the job writing to "ratings". Catchr rewrites that selected period on each run.
The partition field tells Catchr which Google Play Review rows in "ratings" belong to the period being refreshed. If you omit it, every run appends records rather than updating them.
With Google Play Review data, a Snowflake query can summarize review volume and average rating by location over the last 30 days. A query built around Average Rating and Helpful Votes can support trend reviews, account comparisons, and operational reporting.
Yes. Connect an existing Snowflake 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.
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