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Send Tray data to AI, reports, spreadsheets and ETL

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Tray

E-commerce and Marketplaces Financial and Payments

Kondado enables you to replicate comprehensive eCommerce data from Tray into your preferred analytics environment. Access detailed information from your online store including customer profiles with registration dates and last visit timestamps, complete order histories with Mercado Livre marketplace specifics, and payment transaction records with method details. You can extract discount coupon usage statistics, newsletter subscription data with modification tracking, and order invoice information essential for accounting reconciliation. Product data includes standard items, kits with attribute details, and variants with specific IDs for comprehensive inventory analysis.

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Kondado provides direct access to 14 distinct pipelines encompassing 328 fields from Tray, covering every aspect of your eCommerce operation from customer behavior and order management to financial transactions and inventory details.

Marketing teams can analyze customer acquisition patterns through newsletter subscription trends and discount coupon redemption rates to optimize campaign performance and retention strategies. Operations teams benefit from monitoring order details, payment statuses, and estimated delivery dates to streamline fulfillment workflows and reduce delays. Data analysts can cross-reference sold products information with inventory variants and additional product attributes to calculate true profit margins, identify top-performing SKUs, and track sales velocity across different marketplace channels including Mercado Livre.

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

Try out all the features for free for 14 days

Below you will find the complete list of available pipelines that Kondado can replicate from your Tray store to power your analytics initiatives. The Customers pipeline delivers essential contact information and behavioral timestamps to help you segment audiences based on registration dates and engagement patterns for targeted marketing campaigns. Orders and Order Details pipelines provide comprehensive transaction data including billing addresses and cart values, while the specific Mercado Livre variant captures marketplace-specific delivery estimates and product information critical for multi-channel sellers. Financial teams can leverage the Payments and Order Transactions pipelines to track revenue flows, transaction statuses, and payment method preferences across your sales channels. By combining Discount Coupons data with Orders information, you can measure promotional campaign effectiveness and calculate actual revenue impact beyond gross sales figures. Linking Products variants with Sold Products records enables accurate inventory turnover analysis and demand forecasting. With automated updates running on your configurable schedule, from every five minutes to daily intervals, you can monitor these KPIs continuously without manual data exports.

Connector schema

Available Tray data

available pipelines

328

extractable fields

Available integrations

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.

See all available data → Use this connector in chat (AI + MCP) →

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How to visualize Tray data in 3 steps

Connect Tray to AI (Claude/ChatGPT via MCP), dashboards, spreadsheets, or databases — no code required.

Add Tray as a Data Source

Log into Kondado and select Tray from the available eCommerce data sources to initiate the connection process using your Tray API credentials.

Select Pipelines and Destination

Choose from 14 available pipelines including Orders, Customers, and Payments, then select where to send your data such as BigQuery, PostgreSQL, Power BI, or Google Sheets.

Analyze in Dashboards, Sheets, and Databases

Create custom reports in Looker Studio or Power BI, analyze metrics in Google Sheets or Excel, or query structured data in PostgreSQL, MySQL, and other database destinations to uncover actionable insights.

Try out all the features for free for 14 days

Hundreds of data-driven companies trust Kondado

Why Kondado?

Focus on extracting value from your data and leave the rest to us

Wherever you need

With the same platform, you send data to AI (Claude/ChatGPT via MCP), reports, spreadsheets, databases, data warehouses, and data lakes. ETL and ELT

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From wherever you need

Data from over 80 sources for Marketing, Ecommerce, ERPs, Customer Service, Finance, Databases, and much more

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Predictable pricing

No surprise invoices, pick a plan and change it anytime

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Pick an AI, Spreadsheet, Database, Data Warehouse or Data Lake to use Tray data

Tray > AI (Claude, ChatGPT, MCP)

Tray > Looker Studio

Tray > Power BI

Other visualizations

Tray > Amazon S3

Tray > BigQuery

Tray > Excel

Tray > Google Sheets

Tray > MySQL

Tray > PostgreSQL

Tray > Redshift

Tray > SQL Server

Choose a tool to visualize your Tray data

If the software you need is not listed, drop us a messagem. You can use almost every tool

Tray > Airtable

Tray > Alteryx

Tray > Amazon Quicksight

Tray > BIMachine

Tray > Cortex

Tray > Data Studio

Tray > Geckoboard

Tray > Grafana

Tray > IBM Cognos Analytics

Tray > Klipfolio

Tray > Looker Studio

Tray > Looker

Tray > Looqbox

Tray > Metabase

Tray > Microstrategy

Tray > Pentaho

Tray > Power BI

Tray > Qlik Cloud Analytics

Tray > Qlik Sense

Tray > Qlik

Tray > QlikView

Tray > Redash

Tray > Superset

Tray > Tableau

Tray > BI TOTVS

Tray > Zoho Analytics

Frequently Asked Questions (FAQ)

Find answers to common questions about connecting Tray to AI (Claude/ChatGPT via MCP), dashboards, spreadsheets, and databases

What Tray data can I extract using Kondado? ▼

You can replicate 14 distinct pipelines covering customers, orders, payments, products, discount coupons, newsletters, and invoices. Specific fields include customer registration dates, Mercado Livre order details, product variant attributes, transaction statuses, and coupon usage restrictions across 328 available fields.

How do I connect Tray to Power BI or Google Sheets? ▼

After adding Tray as a data source in Kondado, select your desired pipelines and choose Power BI or Google Sheets as your destination. The platform handles the data replication automatically on your chosen schedule, delivering fresh data directly to your spreadsheets or BI reports.

How often does Kondado update Tray data? ▼

Kondado updates Tray data on a configurable schedule ranging from every five minutes to daily intervals. You can set different frequencies for different pipelines based on your business needs, ensuring near-real-time visibility for critical metrics like orders and payments while running daily updates for historical product data.

Can I analyze Mercado Livre sales separately from other Tray orders? ▼

Yes, Kondado provides a dedicated Order Details: Mercado Livre pipeline that isolates marketplace-specific data including customer IDs, estimated delivery dates, and purchased product details. This allows you to create separate reports for your Mercado Livre performance while maintaining unified analytics across all sales channels.

What types of analytics can I build with Tray order and payment data? ▼

You can build cash flow analysis by combining Payments and Order Transactions pipelines, calculate average order values using Order Details data, and track payment method preferences over time. These insights help finance teams reconcile accounts and identify trends in customer purchasing behavior across different transaction types.

Does Kondado support Tray product kits and variant data? ▼

Yes, Kondado includes dedicated pipelines for Products (Kits) and Products: Variants, capturing attributes like kit composition and variant-specific IDs. This enables accurate inventory management reporting and profitability analysis for complex product catalogs with multiple configurations.

Which databases and BI tools work with Tray data from Kondado? ▼

You can send Tray data to BigQuery, PostgreSQL, Power BI, Looker Studio, and Google Sheets, plus MySQL, Excel, Redshift, SQL Server, and Amazon S3. This flexibility allows you to store historical data in databases while creating visualizations in your preferred BI platform.

Related on Kondado

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