Connect Piwik to Claude

Multi-Client Piwik Health Radar

Using the Catchr MCP, analyze Piwik for [List of Client Accounts] over [Reporting Period] against [Comparison Period]. For each account, review Goal conversion rate, Revenue, and Goal conversions and break the results down by Source / medium and Page URL. Focus on traffic quality and acquisition efficiency. 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 Piwik only shows correlation.

Client-Ready Piwik Performance Brief

Using the Catchr MCP, review Piwik for [Client Account] during [Reporting Period] versus [Comparison Period]. Review Goal conversions, Bounce rate, and Cart abandonment rate and break the results down by Page title and Channel. Explain what improved, what declined, and which changes are material for acquisition, landing-page, engagement, event, and conversion 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.

Piwik Opportunity and Risk Map

Using the Catchr MCP, compare Piwik across [List of Client Accounts] for [Period] using [Materiality Threshold] and [Client-Specific Targets]. For every account, review Cart abandonment rate, Orders, and Downloads and break the results down by Referrer URL and Campaign name. Investigate landing-page engagement and conversion gaps and device, market, event, and channel differences. 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 Piwik Priority Queue

Using the Catchr MCP, pull Piwik for [List of Client Accounts] over [Recent Period] and compare it with [Baseline Period]. For each client, review Downloads, Outlinks, and Goal conversions in session and break the results down by Product category and 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 Piwik Client Report

Using the Catchr MCP, create a monthly Piwik report for [Client Account] covering [Current Period] versus [Previous Period]. Review Goal conversions in session, Unique goal conversions, and Page bounce rate and break the results down by Medium and Currency conversion date. Explain the most important movement in acquisition, landing-page, engagement, event, and conversion 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.

Piwik Optimization Backlog

Using the Catchr MCP, analyze Piwik for [Client Account] over [Lookback Period]. Review Page bounce rate, Downloads in session, and Unique downloads in session and break the results down by Source and Campaign name (Google Ads). Identify the largest opportunities related to traffic quality and acquisition efficiency and device, market, event, and channel differences, 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.

Piwik Acquisition Quality and Conversion Review

Using the Catchr MCP, analyze Piwik for [Account or Entity] over [Reporting Period] versus [Comparison Period]. Review Unique downloads in session, Orders in session, and Goal revenue and break the results down by Product category (Level 1) and Product category (Level 2). Concentrate on traffic quality and acquisition efficiency. 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 Piwik exposes only a related signal.

Piwik Landing Page Opportunity Map

Using the Catchr MCP, investigate Piwik for [Account or Entity] across [Period] with a focus on landing-page engagement and conversion gaps. Review Goal revenue, Goal revenue (converted), and Goal revenue (USD) and break the results down by Product category (Level 3) and Product category (Level 4). 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 Piwik fields establish a direct relationship.

Piwik Channel and Device Behavior Analysis

Using the Catchr MCP, review Piwik for [Account or Entity] over [Lookback Period] to assess device, market, event, and channel differences. Review Goal revenue (USD), Product revenue, and Product revenue (converted) and break the results down by Product category (Level 5) and Product category (array). 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.

Piwik Data Quality Audit

Using the Catchr MCP, audit Piwik for [Account or All Connected Accounts] over [Period]. Review Product revenue (converted), Product revenue (USD), and Revenue (converted) and break the results down by Product category 1 (array) and Product category 2 (array). 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].

Piwik Freshness and Coverage Monitor

Using the Catchr MCP, monitor Piwik delivery for [Account or All Connected Accounts] across [Lookback Period]. Review Revenue (converted), Revenue (USD), and Outlinks in session and break the results down by Product category 3 (array) and Product category 4 (array). 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.

Piwik Drift and Reconciliation Review

Using the Catchr MCP, compare Piwik across [Current Window] and [Baseline Window] for [Account or All Connected Accounts]. Review Outlinks in session, Unique outlinks in session, and Unique downloads and break the results down by Product category 5 (array) and Bounced session. 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 Piwik to Claude

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How to connect Piwik to Claude ?

Authorize the Piwik 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 Piwik prompts for analyzing real account data.

Piwik to Claude FAQs

What Piwik data can Claude analyze through Catchr?

How granular can Piwik analysis be in Claude?

Can Claude compare Piwik performance across periods or accounts?

Can Claude investigate unusual changes in Piwik?

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

Can I combine Piwik with other data sources in Claude?

Can Claude compare multiple Piwik accounts or entities?

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

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

Can Claude change anything in Piwik 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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