Starter
For freelancers and small teams.
$ 24 /mo
Billed monthly · cancel anytime
Platforms3
Accounts10
Used by the world's leading companies
Available metrics
Available dimensions
What our customers say about us.
After three years of use, Catchr has become essential for both our teams and our clients. So far, it has been our best solution for compiling and analyzing data from different advertising platforms. It’s easy to set up, and the customer service is responsive and excellent.
With Catchr’s automated API, we can finally collect and centralize all advertising data, connect it with booking information, and calculate the real ROAS for our restaurant clients. It gives them full visibility, more autonomy, and the ability to optimize campaigns to maximize ROI.
The solution is a real game changer, providing optimal time savings for our data reporting. The major strength of the solution is their highly responsive and professional support.
Add your BigCommerce store to Catchr using its Store Hash and Access Token. Open the Catchr BigCommerce connector in Looker Studio, authorize Google, and select the connected store. Create an order-level table first, then add product charts to compare what customers bought.
Catchr exposes orders, order products, and customer data. You can report on order status, payment status, totals, discounts, shipping, refunds, product quantities, SKUs, and variants. Use order fields for store-level totals and product fields for item-level analysis; these represent different reporting levels.
Yes. Order-product fields include product ID, variant ID, SKU, name, quantity, and totals with or without tax. They also include shipped and refunded quantities. Use these order-item values to measure sales during the selected period, and check how bundles or parent-child items are represented before aggregating them.
A single order can contain several products, so joining order totals to item rows can repeat the full order value. Count distinct order IDs for order volume and sum item-level totals for product analysis. Check any additional blends for repeated keys before interpreting a higher total as increased revenue.
Yes. The connector includes an order refunded amount and product-level refund amounts, refunded quantities, and refund flags. Keep order and product refund totals separate to avoid counting the same refund twice. A refunded amount on an order is not automatically a daily refund ledger; check the date basis used by your report.
Match order statuses, payment statuses, dates, channel, currency, tax, and shipping treatment. The connector includes both tax-exclusive and tax-inclusive totals, plus separate discounts and refund amounts. Choose the same definition as the store dashboard and avoid adding fees or subtracting discounts a second time if they are already included.
Yes. Add Google Ads to compare costs with store results. Aggregate both sources to compatible dates and currencies before blending, and validate any campaign mapping. Total store sales divided by ad spend is a blended efficiency measure, not the ad platform’s attributed ROAS.
Our team is always here to answer any questions you may have about our data connector.
