Connect Bigcommerce to ChatGPT

Multi-Store Commerce Health Command Center

Using the Catchr MCP, pull BigCommerce data for [List of Client Store/Account IDs] over [Period] and compare it with [Comparison Period]. For each store, calculate order count from unique Orders Id, gross revenue from Orders Total Inc Tax, average order value, refund rate from Orders Refunded Amount divided by revenue, discount rate from Orders Discount Amount plus Orders Coupon Discount divided by revenue, and fulfillment completion from Orders Items Shipped versus Orders Items Total. Assess each store against [Client Targets], label it Healthy, Watch, or Critical, rank the accounts requiring attention, and give one evidence-based next action for every Watch or Critical store.

Client Store Performance Brief

Using the Catchr MCP, analyze BigCommerce performance for [Client Store/Account ID] over [Reporting Period] versus [Previous Period]. Summarize unique orders, Orders Total Inc Tax, average order value, Orders Refunded Amount, Orders Discount Amount, Orders Coupon Discount, and Orders Shipping Cost Inc Tax. Break down material changes by Orders Channel Id, Orders Order Source, Orders Geoip Country, Orders Payment Method, Orders Status, Order Products Brand, Order Products Name, and Order Products Sku where available. Produce a client-ready brief in plain English with key wins, risks, the drivers behind each change, and three prioritized recommendations for [Next Period].

Cross-Client Fulfillment and Refund Watchlist

Using the Catchr MCP, review BigCommerce operations for [List of Client Store/Account IDs] over [Recent Period]. Use Orders Id, Orders Date Created, Orders Date Modified, Orders Date Shipped, Orders Status, Orders Payment Status, Orders Items Total, Orders Items Shipped, Orders Refunded Amount, Order Products Quantity, Order Products Quantity Shipped, Order Products Quantity Refunded, Order Products Refund Amount, Order Products Fulfillment Source, Order Products Name, and Order Products Sku to detect unshipped, partially shipped, delayed, refunded, or payment-risk orders according to [Operational Rules]. Rank clients by exception volume and financial exposure, show the affected order or product identifiers supported by the data, and assign a recommended owner and next action to each issue.

Morning Client Store Priority Queue

Using the Catchr MCP, pull BigCommerce data for [List of Client Store/Account IDs] for [Recent Period, e.g., yesterday or month to date] and compare it with [Baseline Period]. For each client, calculate unique orders, Orders Total Inc Tax, average order value, Orders Refunded Amount, discount rate, and shipped-item completion using Orders Items Shipped versus Orders Items Total. Check performance against [Client KPI Targets], rank the clients I should review today, explain the precise store, order-status, channel, geography, or product signal behind each priority, and give the first investigation or client-communication action to take.

Monthly BigCommerce Client Report

Using the Catchr MCP, pull BigCommerce data for [Client Store/Account ID] for [Reporting Period] and [Previous Period]. Summarize unique orders, Orders Total Inc Tax, average order value, Orders Discount Amount, Orders Coupon Discount, Orders Refunded Amount, Orders Shipping Cost Inc Tax, and fulfillment completion. Break down the material changes by Orders Status, Orders Channel Id, Orders Order Source, Orders Geoip Country, Order Products Brand, Order Products Name, and Order Products Sku. Write a concise client-ready report in plain English covering what improved, what declined, why the available data indicates it changed, and the three recommended priorities for [Next Period].

SKU Recovery Action Backlog

Using the Catchr MCP, analyze BigCommerce order-product performance for [Client Store/Account ID] over [Period] versus [Comparison Period] by Order Products Brand, Name, Sku, Product Id, and Variant Id. Use Order Products Quantity, Quantity Shipped, Quantity Refunded, Total Inc Tax, Cost Price Inc Tax, Applied Discounts, and Refund Amount to identify products losing revenue, margin, or fulfillment quality. Apply [Minimum Quantity or Revenue Threshold] before prioritizing an item, diagnose the strongest available driver, and create a freelancer-friendly backlog ranked by expected impact and effort with a specific action, success metric, and review date for every selected SKU.

Revenue and Order Mix Pulse

Using the Catchr MCP, pull BigCommerce orders for [Store/Account ID] over [Period] and compare them with [Comparison Period]. Calculate unique order count, Orders Total Inc Tax, average order value, Orders Subtotal Inc Tax, Orders Discount Amount, Orders Coupon Discount, Orders Refunded Amount, and Orders Shipping Cost Inc Tax. Segment the results by Orders Channel Id, Orders Order Source, Orders Geoip Country, Orders Currency Code, Orders Payment Method, and Orders Status. Identify the segments driving growth or decline, flag any worsening refund or discount dependency against [Thresholds], and provide a prioritized commercial action plan for [Next Period].

Product Margin and Refund Opportunity Matrix

Using the Catchr MCP, analyze BigCommerce order-product data for [Store/Account ID] over [Period] versus [Comparison Period], grouped by Order Products Brand, Order Products Name, Order Products Sku, Product Id, and Variant Id. Report Order Products Quantity, Quantity Shipped, Quantity Refunded, Total Inc Tax, Cost Price Inc Tax, Applied Discounts, and Refund Amount. Calculate gross margin only where compatible cost and revenue fields are populated, then classify products as Scale, Protect Margin, Fix Fulfillment, Investigate Refunds, or Low Priority using [Business Thresholds]. Explain the evidence for each classification and recommend one specific merchandising, pricing, quality, or fulfillment action.

Customer Growth and Retention Readiness

Using the Catchr MCP, assess BigCommerce customer development for [Store/Account ID] over [Period] and [Comparison Period]. Use unique Customers Id, Customers Date Created, Customers Date Modified, Customers Customer Group Id, Customers Company, Customers Address Count, Customers Authentication, and Customers Tax Exempt Category to summarize new-customer volume and customer mix; separately use Orders Is Email Opt In, Orders Customer Locale, Orders Geoip Country, and unique Orders Id to measure order-level opt-in and market mix without exposing personal contact details. Highlight material changes, identify segments that warrant retention, localization, or B2B follow-up, and deliver three prioritized actions with a target metric and review date.

Commerce Entity Integrity Audit

Using the Catchr MCP, audit BigCommerce data for [Store/Account ID or All Connected Stores] over [Period]. For orders, test Orders Id uniqueness at the expected grain, required Orders Date Created values, valid Orders Status and Payment Status values, non-negative monetary fields, and Orders Date Shipped not earlier than Orders Date Created. For order products, test Order Products Id, Product Id, Variant Id, Sku, Quantity, Quantity Shipped, Quantity Refunded, Total Inc Tax, Cost Price Inc Tax, Is Refunded, and Refund Amount for missing identifiers, invalid negatives, and contradictory quantity or refund states. For customers, test Customers Id and Date Created coverage while excluding personal fields from the output. Return an exception table with store, entity, failed rule, observed value, severity, and next validation step.

Extraction Freshness and Coverage Monitor

Using the Catchr MCP, assess BigCommerce data freshness and coverage for [Store/Account ID or All Connected Stores] over [Lookback Period]. Use Extracted Date, Date, Orders Date Created, Orders Date Modified, Orders Id, Orders Total Inc Tax, Order Products Id, Order Products Sku, Order Products Quantity, Customers Id, and Customers Date Created to detect stale extractions, missing dates, duplicate identifiers at [Expected Grain], unexpected null dimensions, and flatlined volumes or revenue. Quantify each issue by store and affected period, distinguish likely pipeline failures from plausible no-activity days using cross-entity evidence, and output a monitoring summary plus a remediation-ready exception table.

Revenue, Tax, and Refund Reconciliation

Using the Catchr MCP, reconcile BigCommerce financial fields for [Store/Account ID or All Connected Stores] over [Period]. At order level, test whether Orders Subtotal Inc Tax, Subtotal Ex Tax, Subtotal Tax, Shipping Cost Inc Tax, Shipping Cost Ex Tax, Shipping Cost Tax, Handling Cost Inc Tax, Discount Amount, Coupon Discount, Refunded Amount, Total Inc Tax, Total Ex Tax, Currency Code, Default Currency Code, and Currency Exchange Rate form internally consistent records within [Tolerance]. Separately, at order-product level, reconcile Total Inc Tax, Total Ex Tax, Total Tax, Price Inc Tax, Cost Price Inc Tax, Quantity, Quantity Refunded, and Refund Amount at a compatible grain. Do not force a cross-entity join when no confirmed key is available; report each failed equation, affected value, currency, severity, and likely source-system or transformation cause.

Replace [variables] Facts ≠ hypotheses Action + follow-up metric

Connect Bigcommerce to ChatGPT

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How to connect Bigcommerce to ChatGPT ?

Authorize the Bigcommerce account in Catchr

Add the Catchr MCP from official ChatGPT store

Choose, adapt, and run a prompt.

A simple client question should not trigger an hour of data prep.

Pull another CSV

Rebuild the context

Summarize it by hand

Ask the account. Get to the explanation.

Prepare data before every question.

Connect once. Keep asking.

Twelve Bigcommerce prompts for analyzing real account data.

Bigcommerce to ChatGPT FAQs

What Bigcommerce data can ChatGPT analyze through Catchr?

How granular can Bigcommerce analysis be in ChatGPT?

Can ChatGPT identify product and operational risks in Bigcommerce?

Can ChatGPT compare acquisition, customer, and revenue mix in Bigcommerce?

What types of prompts work best for Bigcommerce analysis?

Can I combine Bigcommerce with other data sources in ChatGPT?

Can I analyze multiple stores, shops, or marketplaces together?

What do I need to connect Bigcommerce to ChatGPT with Catchr?

How recent is the Bigcommerce data, and how much history can I analyze?

Can ChatGPT change anything in Bigcommerce through Catchr?

How much does it cost to connect marketing data to ChatGPT with Catchr?

‍Can I try the ChatGPT integration before choosing a plan?

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