Connect Bigcommerce to Claude

Multi-Client Bigcommerce Health Radar

Using the Catchr MCP, analyze Bigcommerce for [List of Client Accounts] over [Reporting Period] against [Comparison Period]. For each account, review Order Products Quantity, Orders Discount Amount, and Order Products Total Inc Tax and break the results down by Order Products Name and Order Products Sku. Focus on product and collection performance across periods and channels. Rank accounts as Healthy, Watch, or Critical using [Client Targets or Historical Baseline], and show the evidence behind each status. Return a client-ready table with the account, main change, supporting fields, business implication, recommended next action, and one sentence for the next client meeting. Separate observed changes from possible explanations, respect the reporting grain, and do not claim causation when Bigcommerce only shows correlation.

Client-Ready Bigcommerce Performance Brief

Using the Catchr MCP, review Bigcommerce for [Client Account] during [Reporting Period] versus [Comparison Period]. Review Order Products Total Inc Tax, Orders Coupon Discount, and Orders Refunded Amount and break the results down by Order Products Brand and Orders Order Source. Explain what improved, what declined, and which changes are material for orders, products, customers, revenue, refunds, discounts, and channel performance. Produce an executive summary, three evidence-backed wins, three risks, and a prioritized action plan with owner and review date. Include a compact evidence table that ties every conclusion to the returned fields. State any unavailable field, incompatible reporting level, or small-sample limitation before recommending action, and write the final recap in language an agency account manager can use with the client.

Bigcommerce Opportunity and Risk Map

Using the Catchr MCP, compare Bigcommerce across [List of Client Accounts] for [Period] using [Materiality Threshold] and [Client-Specific Targets]. For every account, review Orders Refunded Amount, Order Products Quantity Refunded, and Orders Total Inc Tax and break the results down by Orders Currency Code and Orders Geoip Country. Investigate customer mix, repeat purchase behavior, and order value and refund, discount, inventory, and revenue concentration risks. Build an opportunity-and-risk map ranked by business relevance, confidence, and urgency. For each finding, show the account, observed change, supporting fields, plausible explanations, first validation step, and recommended client action. Keep each client separate before creating a portfolio summary, and avoid applying one account's baseline, currency, attribution rule, or reporting definition to another.

Morning Bigcommerce Priority Queue

Using the Catchr MCP, pull Bigcommerce for [List of Client Accounts] over [Recent Period] and compare it with [Baseline Period]. For each client, review Orders Total Inc Tax, Orders Total Ex Tax, and Order Products Quantity Shipped and break the results down by Order Products Name Customer and Order Products Event Date. Flag changes beyond [Alert Threshold], separate high-value issues from low-volume noise, and rank the work I should handle today. Return a queue with the client, issue, exact evidence, likely impact stated cautiously, first validation step, recommended action, and a short update I can send to the client. Do not merge accounts until each result has been checked against its own target, currency, timezone, and reporting grain.

Monthly Bigcommerce Client Report

Using the Catchr MCP, create a monthly Bigcommerce report for [Client Account] covering [Current Period] versus [Previous Period]. Review Order Products Quantity Shipped, Order Products Refund Amount, and Order Products Base Cost Price and break the results down by Order Products Name Merchant and Date. Explain the most important movement in orders, products, customers, revenue, refunds, discounts, and channel performance, including what stayed stable and what needs attention. Write a plain-English report with an executive summary, a concise evidence table, three wins, three concerns, and three actions for [Next Period]. Attach an owner and success measure to each action. State the latest available date and any missing fields or intervals so the client can distinguish measured facts from assumptions or incomplete coverage.

Bigcommerce Optimization Backlog

Using the Catchr MCP, analyze Bigcommerce for [Client Account] over [Lookback Period]. Review Order Products Base Cost Price, Order Products Base Price, and Order Products Base Total and break the results down by Orders Date Created and Orders Date Modified. Identify the largest opportunities related to product and collection performance across periods and channels and refund, discount, inventory, and revenue concentration risks, then create an optimization backlog ranked by expected impact, effort, and confidence. For every task, include the observed evidence, a specific action, an owner, a due date, a success metric, and a guardrail that would stop the test. Use [Minimum Volume] and [Materiality Threshold] to avoid reacting to noise, and label any recommendation that requires a field or business definition not available in the returned dataset.

Bigcommerce Product and Revenue Performance Review

Using the Catchr MCP, analyze Bigcommerce for [Account or Entity] over [Reporting Period] versus [Comparison Period]. Review Order Products Base Total, Order Products Base Wrapping Cost, and Order Products Cost Price Ex Tax and break the results down by Orders Date Shipped and Orders Geoip Country Iso2. Concentrate on product and collection performance across periods and channels. Identify the entities and periods driving the largest change, distinguish material movement from normal variation using [Minimum Volume] and [Business Target], and explain what the available fields can and cannot prove. Return a ranked findings table with evidence, business implication, confidence, and recommended next action, followed by a short decision summary. Keep calculations at a compatible reporting grain and do not invent a metric when Bigcommerce exposes only a related signal.

Bigcommerce Customer and Order Value Analysis

Using the Catchr MCP, investigate Bigcommerce for [Account or Entity] across [Period] with a focus on customer mix, repeat purchase behavior, and order value. Review Order Products Cost Price Ex Tax, Order Products Cost Price Inc Tax, and Order Products Cost Price Tax and break the results down by Order Products Is Refunded and Order Products Applied Discounts. Compare relevant entities against [Target, Peer Group, or Historical Baseline], then locate the strongest opportunities and clearest deterioration. For every finding, show the returned values, comparison dimension, possible explanations, and next check required before action. Deliver a prioritized opportunity map with owner, action, expected signal of improvement, and review date. Treat associations as hypotheses unless the available Bigcommerce fields establish a direct relationship.

Bigcommerce Refund and Discount Risk Scan

Using the Catchr MCP, review Bigcommerce for [Account or Entity] over [Lookback Period] to assess refund, discount, inventory, and revenue concentration risks. Review Order Products Cost Price Tax, Order Products Fixed Shipping Cost, and Order Products Price Ex Tax and break the results down by Customers Date Created and Customers Date Modified. Flag changes outside [Tolerance], rank them by materiality and confidence, and separate confirmed data observations from possible operational causes. Return an exception table with the affected entity, period, supporting fields, severity, owner, first validation step, and recommended response. End with three repeatable monitoring rules, including the threshold, minimum volume, and required field. Do not present an unusual value as proof of an error or business cause.

Bigcommerce Data Quality Audit

Using the Catchr MCP, audit Bigcommerce for [Account or All Connected Accounts] over [Period]. Review Order Products Price Ex Tax, Order Products Price Inc Tax, and Order Products Price Tax and break the results down by Order Products Variant Id and Order Products Bin Picking Number. Check completeness, unexpected nulls, duplicate identifiers at [Expected Grain], invalid values, incompatible aggregation levels, and date consistency where the returned fields support those tests. Return rule-level failure counts and a severity-ranked exception sample with account, field, observed value, expected condition, and reproducible validation step. Distinguish source-data issues from extraction or modeling issues, and do not infer uniqueness, join keys, or business meaning unless confirmed in [Data Contract or Source Documentation].

Bigcommerce Freshness and Coverage Monitor

Using the Catchr MCP, monitor Bigcommerce delivery for [Account or All Connected Accounts] across [Lookback Period]. Review Order Products Price Tax, Order Products Total Ex Tax, and Order Products Total Tax and break the results down by Order Products Configurable Fields and Order Products Depth. Measure date coverage, latest available record, row or entity volume, missing intervals, and field population against [Expected Schedule] and [Freshness SLA]. Flag stale extraction, flatlined volume, schema coverage changes, and gaps beyond [Absolute and Relative Thresholds]. Return an account-level health summary plus an investigation table with first affected period, supporting fields, likely failure domain stated cautiously, owner, and next validation query. Separate genuine source inactivity from a pipeline issue whenever the evidence cannot distinguish them.

Bigcommerce Drift and Reconciliation Review

Using the Catchr MCP, compare Bigcommerce across [Current Window] and [Baseline Window] for [Account or All Connected Accounts]. Review Order Products Total Tax, Order Products Wrapping Cost Ex Tax, and Order Products Wrapping Cost Inc Tax and break the results down by Order Products Ebay Item Id and Order Products Ebay Transaction Id. Profile distributions, null rates, distinct-value counts, volume, and material changes at the declared reporting grain. Reconcile related fields only when their definitions and aggregation levels are compatible. Flag abrupt shifts beyond [Drift Threshold], inconsistent totals, and values that violate [Business or Data Contract Rules]. Produce a reproducible alert table with evidence, severity, probable domain, and next check, followed by a concise assessment of which analyses may be unreliable until each issue is resolved.

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

Connect Bigcommerce to Claude

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How to connect Bigcommerce to Claude ?

Authorize the Bigcommerce account in Catchr

Add the Catchr MCP as a custom connector in Claude

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 Claude FAQs

What Bigcommerce data can Claude analyze through Catchr?

How granular can Bigcommerce analysis be in Claude?

Can Claude compare Bigcommerce performance across periods or accounts?

Can Claude investigate unusual changes in Bigcommerce?

What types of prompts work best for Bigcommerce analysis in Claude?

Can I combine Bigcommerce with other data sources in Claude?

Can Claude compare multiple Bigcommerce accounts or entities?

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

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

Can Claude change anything in Bigcommerce through Catchr?

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

Can I try the Claude integration before choosing a plan?

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