Connector Database / Loop Returns
Analyze your Loop Returns data with AI
Build interactive dashboards, generate automated reports, and unlock business intelligence insights from your Loop Returns data with AI-powered assistant.
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Start with a question
Generate automated reports and business intelligence insights from your Loop Returns data—as fast as you can ask them.
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Transform your conversation into dynamic data visualizations on an intuitive data canvas.
Integrate all your data
Unify your Loop Returns data with DuckDB-powered data warehouse including Quickbooks, Google Analytics and PostgreSQL.
Available Loop Returns Data
Provides access to Loop Returns data about e-commerce returns and exchanges. Includes return records with timestamps, order and customer identifiers, currency and financial totals (product, discount, tax, refund, credit), line items with SKUs and return reasons, exchange details, and logistics fields like carrier, tracking number, and label status. Enables analysis of return volumes and trends, reasons for return, refund versus exchange value, product performance, and shipping/label operations.
Return
Represents individual return records with timestamps, order/customer identifiers, status, and financial totals (product, discount, tax, refund, credit). Supports analysis of return volumes and trends, refund liability, cycle time, and return rates.
Return Line Item
Item-level details within a return, including SKUs, quantities, and reason codes. Enables product-level return rates, reason distribution, and identification of high-return items.
Exchange
Information on exchanges associated with returns, including exchanged items and credited values. Enables measurement of refund vs. exchange mix, retained revenue, and exchange outcomes.
Return Shipment/Label
Logistics and labeling details such as carrier, tracking number, and label status. Supports operational KPIs like label utilization, processing timelines, and carrier performance.
Product
Product dimension referenced via SKUs on return line items. Enables analysis of SKU-level performance, return propensity, and product quality or fit issues.
Customer
Customers associated with returns via customer identifiers. Supports customer-level analyses such as return propensity, repeat returners, and impact on retention.
Authentication Required
Uses an API key from your Loop Returns admin dashboard to authenticate (sent in the X-Authorization header)
Getting started with
Loop Returns Analytics & Business Intelligence
Connect your Loop Returns data
Connect to Loop Returns once and automatically sync data to your centralized data warehouse for real-time reporting and analytics.
Build business intelligence models
Create automated reports, dashboards, and data visualizations with customizable business logic and AI-powered insights for consistent analytics across your organization.
Generate reports and insights
Create interactive dashboards, automated reports, and data visualizations with AI-powered business intelligence. Share live analytics and scheduled reporting with your team.
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Loop Returns usersDefinite
People love Definite because it lets you focus on what matters. Setting up your own data infrastructure doesn't make your beer taste better. Skip the tedium and start at analytics.
I was leading the efforts of setting up a business intelligence function. I was surprised how complex this all was to do even today. It's something that every tech company would need at some point but it hasn't been simplified. You need a whole team focused on building a data warehouse, setting up the right pipelines, and then integrating a BI tool on top.Definite wasn't only the answer to this problem, it tackled the next problem I knew I'd have as soon as the BI tool was ready — how do we get non-technical teams and people to learn and utilise such a tool.
Our analytics before Definite consisted of dozens of Excel sheets that took hours to update. Manual updates led to errors. Everyone questioned the accuracy of the numbers. Many people just stopped looking at the reports.After Definite, everything ran like clockwork.We immediately saved thousands of dollars per month in the time spent updating reports and have built strategies (e.g. improved ROI on ad spend, inventory management, etc.) on the data that will yield millions to our bottom line.
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