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Connect Booking Review to Snowflake

Connect Booking Review to Snowflake and export selected accounts, metrics, and dimensions to your Google BigQuery project.

Configure the historical window, destination table, and recurring schedule without maintaining a Booking Review API pipeline.

Used by the world's leading companies

Export Booking Review data to Snowflake

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Booking Review data in PostgreSQL

Bring all your Booking Review data into your warehouse and make it available for analytics, machine learning, and internal applications.

Data freshness

Keep your Snowflake tables up to date

Automatically sync new data from Booking Review so every dashboard, model, and report works with fresh information.

Analysis

Unify Booking Review with the rest of your business data

Join marketing, finance, CRM, and product data inside the same warehouse.

Booking Review metrics and dimensions available in Snowflake

Access 3 metrics and 24 dimensions from Booking Review connectors including Average Rating, Rating, Review Count, Date, Review DateTime, Review Title, Pros, Cons, Language, Reviewer, Reply Text and many more...

3

Metrics availables

24

Dimensions availables

Connect Booking Review to Snowflake in minutes

Move your data from Booking Review to Snowflake with a simple setup. Once connected, Catchr handles the ingestion automatically so your warehouse stays up to date without manual work.

Step one

Connect your Booking Review account

Authenticate your Booking Review account securely in Catchr. No custom scripts, API maintenance, or engineering work required.

Client A · Connected sources
5 sources ready
Booking Review Booking Review 3 advertising accounts Connected
Google Ads 2 advertising accounts Connected
Google Analytics 4 1 web property Connected
HubSpot 1 CRM portal Connected
Step two

Choose the Snowflake destination

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.

Destination / Snowflake Required fields
Authentication Choose one
Password
Key pair
Host Required
xy12345.eu-west-1
Username Required
catchr_service
Database Required
MARKETING.RAW
Private key passphrase Optional
••••••••••••
Private key Required for key pair
-----BEGIN ENCRYPTED PRIVATE KEY----- MIIE6TAbBgkqhkiG9w0BBQMw... -----END ENCRYPTED PRIVATE KEY-----
Step three

Keep your Snowflake tables updated

Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your PostgreSQL table.

Export job / PostgreSQL Example
Schema Destination
marketing_raw
Table Per job
linkedin_ads_daily
Recurring schedule Choose a cadence
Every 6 hours
Daily · 07:00
Weekly · Mon
First sync scheduledSelected fields · configured history
07:00 UTC

Review 30-day Booking Review customer review performance in SQL.

This example summarizes review volume and average rating by location over the last 30 days.

Booking Review.sql
BigQuery SQL
30-day window
SELECT
  location_name,
  AVG(rating) AS average_rating,
  COUNT(*) AS reviews
FROM `your_project.marketing_raw.booking_review_reviews`
WHERE review_date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY location_name
ORDER BY reviews DESC;
Illustrative SQL — adapt it to the fields and schema selected in your export. Standard SQL

Choose what to load into Snowflake.

Each connector has its own entities, fields, historical limits, and reporting uses. Open a source page for the details that belong to that platform.

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Before you schedule the job.

Answers about PostgreSQL setup, available source data, schedules, table updates, and SQL use cases.

Can Catchr send Booking Review records directly to Snowflake?

Add Booking Review in Sources and connect the existing Snowflake database in Storage. A datastream defines the route, while the job loads the chosen fields into "reviews".

How much control do I have over Booking Review fields in Snowflake?

Select concrete Booking Review fields such as Average Rating, Rating, Review Count, 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.

How should I configure recurring Booking Review imports in Snowflake?

Define the first Booking Review fetch, run frequency, and lookback window in the "reviews" job. Each scheduled run replaces data inside the configured period.

How do I prevent duplicate Booking Review rows in Snowflake?

Use a supported date field to partition "reviews". Recurring Booking Review runs can then update the selected window instead of adding another copy of the same period.

How can a team use Booking Review data after it reaches Snowflake?

With Booking Review data, a Snowflake query can summarize review volume and average rating by location over the last 30 days. Model Average Rating and Rating in SQL, then expose the result to dashboards, internal tools, or recurring client reports.

Does my Snowflake database need to exist before I connect it?

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

Can I load several marketing sources into the same Snowflake 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.

Still have a question ? 

Our teams is always here to responds to any question you could have about our data connector. 

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