What specific Shopify data can I extract through Kondado?

You can access 17 different pipelines including Orders with item and discount details, Customers with complete profile information, Abandoned Checkouts with total value and dates, Products with variants and inventory, plus Shipping, Refunds, and UTM parameters for marketing analysis.

How does the OAuth connection with Shopify work on Kondado?

Authentication uses the official Shopify App via OAuth, allowing you to authorize access to your store data simply and directly. Just click connect, log in to your Shopify account, and authorize the necessary permissions to start replicating data.

How frequently is Shopify data updated on Kondado?

The frequency is fully configurable according to your needs, adjustable to intervals ranging from every 5 minutes to daily updates. This allows you to choose between frequent monitoring for critical operations or periodic updates for strategic analysis.

Can I send Shopify data to Google Sheets or Power BI?

Yes, you can send your Shopify data to various destinations including Google Sheets , Power BI , Looker Studio , BigQuery , PostgreSQL , MySQL, Excel, Redshift, SQL Server, and Amazon S3.

Is it possible to analyze the sales funnel and abandoned checkouts together?

Yes, by combining the Orders pipeline with Abandoned Checkouts you can calculate conversion rates by funnel stage. This helps identify where customers abandon the purchase process and measure the financial impact of checkout recovery on total store revenue.

What marketing analyses can I perform with Shopify data?

Using the Orders Visits UTM Parameters pipeline, traffic managers can track the exact origin of conversions by source, medium, and campaign. You can build custom dashboards in Looker Studio or Power BI to optimize advertising ROI.

Can I track refund and return statuses?

Yes, through the Orders Refunds pipeline you access amounts, reasons, statuses, and dates of returns. This allows data analysts to calculate churn rates and identify patterns in products with higher return rates.

Is it possible to monitor inventory and low-stock products?

With the Inventory Items pipeline, you monitor available quantities, product locations, and SKUs. Operations teams can set up alerts in spreadsheets or dashboards when inventory levels hit critical reorder points.

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Shopify Data Integration for Analytics

Kondado provides complete structured access to your Shopify store data through a powerful official API connection. You can replicate detailed information from Orders including all line items and applied discounts, complete Customer data with history and status, Products with variants and images, plus Abandoned Checkouts, store Events, and financial Transactions. The data includes specific fields such as order number, total value, processing status, item SKUs, detailed shipping information with carrier and cost, UTM campaign parameters, and custom note attributes. All of this becomes readily available for deep analysis in your preferred BI tools, spreadsheets, or databases.

The Shopify data source on Kondado provides 17 distinct pipelines covering 505 data fields, enabling automated replication of complete store information on a configurable update schedule.

Marketing managers and traffic managers can analyze campaign effectiveness using UTM parameters captured in Orders to calculate precise ROI and optimize ad spend. Data analysts can cross-reference Customer demographic information with complete purchase history, refund patterns, and line item details to build advanced audience segmentations and predict behaviors. Sales leaders and commercial managers track crucial metrics such as abandoned checkout conversion rates, average shipping processing time, and average ticket value by product category. Operations teams continuously monitor inventory levels through the Inventory Items pipeline, pending refund statuses, and order timeline events to ensure logistical smoothness.

The Kondado platform takes care of refreshing Shopify data, allowing you to stop wasting time with manual work and complex workflows, and focus on analyzing Shopify data in your report, spreadsheet, data warehouse, data lake, or database

Below you will find all available data pipelines to replicate information from your Shopify store. The Orders pipeline brings complete sales details including items, prices, quantities, and applied discounts, while Customers provides essential demographic and behavioral data for audience segmentation analysis. Abandoned Checkouts allows you to identify valuable opportunities for recovering lost revenue, and Events records important actions in your store’s processing timeline. The Products pipeline details variants, inventory levels, images, and complete descriptions for efficient catalog management.

By combining multiple pipelines, you create powerful cross-analyses and strategic insights: relate Orders with Customers to calculate lifetime value and purchase recurrence, or cross-reference Shipping information with financial Transactions to monitor operational cash flow in a timely manner. With fully configurable update frequency on Kondado, your essential KPI dashboards for conversion rate, average ticket, customer retention rate, and processing velocity remain always updated according to your operational needs.

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Available Shopify data

available pipelines

505

extractable fields

Available integrations

Integration	Description
Abandoned Checkouts	View data on abandoned checkouts, including total value, items in the cart, and abandonment date.
Customers	Track customer information, including name, email, status, and account creation date.
Events	Log important events, including event type, date, and details associated with each event.
Inventory: items	Monitor item inventory, including SKU, available quantity, and product location.
Order timeline events	Analyze order timeline events, including status, date, and actions taken during processing.
Orders	Examine order details, including order number, total value, status, and creation date.
Orders Details	Get detailed information about orders, including items, prices, quantities, and applied discounts.
Orders Discount Applications	View how discounts were applied to orders, including discount type and value.
Orders Discount Codes	Access information on discount codes used in orders, including code and discount value.
Orders Fulfillments	Monitor the status of order fulfillments, including fulfillment date and shipping method.
Orders Line Items	Includes information on products, quantities, and prices, along with fields such as SKU, product title, and applied discount.
Orders Note Attributes	Contains custom attributes associated with orders, such as customer notes, tags, and additional fields that assist in identification.
Orders Refunds	Records information about refunds, including amounts, reasons, and status, along with fields such as refund date and method used.
Orders Shipping Lines	Provides details on shipping options, including carrier, shipping cost, and estimated delivery time.
Orders Transactions	Includes data on financial transactions, such as amounts, payment methods, and payment status, along with timestamps.
Orders Visits UTM Parameters	Captures information on order visits, including UTM parameters such as source, medium, and campaign for marketing analysis.
Products	Contains details about products, including title, description, price, SKU, and images, along with information on variants.

Abandoned Checkouts

View data on abandoned checkouts, including total value, items in the cart, and abandonment date.

Customers

Track customer information, including name, email, status, and account creation date.

Events

Log important events, including event type, date, and details associated with each event.

Inventory: items

Monitor item inventory, including SKU, available quantity, and product location.

Order timeline events

Analyze order timeline events, including status, date, and actions taken during processing.

Orders

Examine order details, including order number, total value, status, and creation date.

Orders Details

Get detailed information about orders, including items, prices, quantities, and applied discounts.

Orders Discount Applications

View how discounts were applied to orders, including discount type and value.

Orders Discount Codes

Access information on discount codes used in orders, including code and discount value.

Orders Fulfillments

Monitor the status of order fulfillments, including fulfillment date and shipping method.

Orders Line Items

Includes information on products, quantities, and prices, along with fields such as SKU, product title, and applied discount.

Orders Note Attributes

Contains custom attributes associated with orders, such as customer notes, tags, and additional fields that assist in identification.

Orders Refunds

Records information about refunds, including amounts, reasons, and status, along with fields such as refund date and method used.

Orders Shipping Lines

Provides details on shipping options, including carrier, shipping cost, and estimated delivery time.

Orders Transactions

Includes data on financial transactions, such as amounts, payment methods, and payment status, along with timestamps.

Orders Visits UTM Parameters

Captures information on order visits, including UTM parameters such as source, medium, and campaign for marketing analysis.

Products

Contains details about products, including title, description, price, SKU, and images, along with information on variants.

See all available data →

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How to visualize Shopify data in 3 steps

Connect Shopify to dashboards, spreadsheets, or databases — no code required.

Add Shopify to Kondado

Access Kondado, select the option to add a new data source, and choose Shopify. Authentication occurs via OAuth through the official Shopify App, where you authorize access to your store information.

Select pipelines and destination

Choose which of the 17 pipelines you want to replicate, such as Orders, Customers, or Products, and define the data destination. You can send to BigQuery, PostgreSQL, Google Sheets, Power BI, Looker Studio, MySQL, Excel, Redshift, SQL Server, or Amazon S3.

Visualize and analyze data

Create custom dashboards in BI tools like Power BI or Looker Studio, analyze metrics in Google Sheets or Excel spreadsheets, or query tables directly in databases such as PostgreSQL, BigQuery, MySQL, Redshift, or SQL Server for advanced SQL analysis.

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