How do I set up a Tray data source in Kondado to use with Qlik Sense?

Start by selecting Tray from the available data sources in your Kondado account and authenticate using your store credentials. Once connected, you can browse the available pipelines including Orders, Customers, and Products to select exactly which data you want to replicate into Qlik Sense for visualization.

What types of eCommerce dashboards can I build in Qlik Sense with Tray data?

You can create custom dashboards tracking sales performance by combining the Orders and Sold Products pipelines to analyze top-performing items and revenue trends. Marketing teams can build customer segmentation reports using the Customers and Newsletters pipelines to visualize subscriber growth and engagement patterns over time.

How often does Tray data update in my Qlik Sense reports?

Kondado allows you to configure automated updates on a schedule that fits your business needs, ranging from every 5 minutes to daily refreshes. This ensures your Qlik Sense visualizations reflect recent transactions and inventory changes without requiring manual data exports from your Tray store.

Which KPIs should I track when visualizing Tray sales data in Qlik Sense?

Monitor conversion rates by comparing Order Details with Customer data to understand purchase behavior, and track average order value using the Order Transactions pipeline. The Discount Coupons pipeline helps you measure promotion effectiveness by visualizing redemption rates and their impact on overall revenue.

Can I share my Qlik Sense dashboards built with Tray data with my team?

Once your data flows into Qlik Sense, you can distribute reports to stakeholders across marketing, operations, and finance departments through Qlik Sense's native sharing features. This collaborative approach ensures everyone works from the same current data sourced directly from your Tray eCommerce platform.

Do I need technical skills to replicate Tray data into Qlik Sense?

No coding or database management is required to connect Tray with Qlik Sense through Kondado, as the platform handles the data replication process automatically. Business users can set up pipelines and configure refresh schedules through an intuitive interface designed for marketing and operations teams.

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Visualize Tray Data in Qlik Sense with Kondado

Kondado provides a direct way to replicate your Tray eCommerce data into Qlik Sense without requiring technical expertise or complex infrastructure. You simply select Tray as your data source, choose which pipelines you want to replicate, and configure how often the data should refresh. Within minutes, your orders, customer information, and sales metrics become available as structured datasets ready for visualization in your preferred business intelligence tool.

Kondado connects Tray to Qlik Sense using a direct connection that requires no intermediate databases, no coding, and no manual exports, allowing business teams to analyze eCommerce performance through automated data replication on a configurable schedule.

Business users can transform raw eCommerce data into actionable insights by combining multiple pipelines such as Orders, Customers, and Products to create comprehensive reports. The automated refresh ensures your Qlik Sense dashboards always reflect current sales trends, inventory levels, and customer behavior without manual intervention. This empowers marketing and operations teams to make data-driven decisions quickly using visual analytics that update on a schedule you control, helping you identify growth opportunities and optimize your online store performance.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

By combining the Orders and Sold Products pipelines in Qlik Sense, you can analyze which items drive the most revenue and identify seasonal purchasing patterns across your Tray store. The Customers and Newsletters pipelines allow marketing teams to segment audiences based on registration dates and engagement history, enabling targeted campaigns that improve retention rates and conversion metrics. When you add Payments data to your visualizations, operations managers gain immediate visibility into transaction success rates and preferred payment methods, facilitating quick adjustments to checkout processes and financial planning that support business growth.

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Tray data available in Qlik Sense

available pipelines

328

extractable fields

Available integrations

Integration	Description
Customers	Includes information such as name, email, and registration date, along with modification date and last visit.
Discount Coupons	Contains details such as coupon code, creation date, and discount value, along with usage restrictions.
Newsletters	Presents information about the customer's email, newsletter status, and creation and modification dates.
Payments	Includes data on payment methods, status, and values of transactions made by customers.
Orders	Provides information such as order ID, order date, and delivery status, along with customer details.
Order Details	Includes detailed information such as order ID, billing address, and additional cart values.
Order Details: Mercado Livre	Presents data such as customer ID, estimated delivery date, and information about the purchased product.
Additional Product Information for Orders	Contains additional information such as product ID and product name related to each order.
Order Invoices	Includes data such as invoice ID and product CFOP, essential for accounting.
Order Transactions	Provides information on transaction status and values associated with each order made.
Products	Table contains information about products, including id, name, and variants. Fields such as attributes_id and attributes_value provide additional details.
Products (Kits)	Table presents product kits, detailing id and attributes. Fields such as attributes_customer_attribute_id provide information about the characteristics of the kits.
Sold Products	Table displays sold products, including id and sales information. Fields such as order_id and order_item_quantity help understand sales performance.
Products: Variants	Table details product variants, including id and attributes. Fields such as additionalproductinfo_product_id and additionalproductinfo_variant_id provide specific information about each variant.

Customers

Includes information such as name, email, and registration date, along with modification date and last visit.

Discount Coupons

Contains details such as coupon code, creation date, and discount value, along with usage restrictions.

Newsletters

Presents information about the customer's email, newsletter status, and creation and modification dates.

Payments

Includes data on payment methods, status, and values of transactions made by customers.

Orders

Provides information such as order ID, order date, and delivery status, along with customer details.

Order Details

Includes detailed information such as order ID, billing address, and additional cart values.

Order Details: Mercado Livre

Presents data such as customer ID, estimated delivery date, and information about the purchased product.

Additional Product Information for Orders

Contains additional information such as product ID and product name related to each order.

Order Invoices

Includes data such as invoice ID and product CFOP, essential for accounting.

Order Transactions

Provides information on transaction status and values associated with each order made.

Products

Table contains information about products, including id, name, and variants. Fields such as attributes_id and attributes_value provide additional details.

Products (Kits)

Table presents product kits, detailing id and attributes. Fields such as attributes_customer_attribute_id provide information about the characteristics of the kits.

Sold Products

Table displays sold products, including id and sales information. Fields such as order_id and order_item_quantity help understand sales performance.

Products: Variants

Table details product variants, including id and attributes. Fields such as additionalproductinfo_product_id and additionalproductinfo_variant_id provide specific information about each variant.

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