Connect Piwik to ChatGPT

Multi-Site Client Health Radar

Using the Catchr MCP, pull Piwik data for [List of Client Sites or Apps] over [Recent Period] and compare it with [Baseline Period]. For each Site or app name, review Sessions, Visitors, Page views, Bounce rate, Goal conversions, Goal conversion rate, Orders, Order rate, and Revenue where relevant to [Client Objectives and KPI Targets]. Classify every client as Healthy, Watch, or Critical, quantify the largest deviation, identify whether Channel, Source / medium, Campaign name, or Session entry URL is driving it, and return a ranked consultant action list with the client to contact, the evidence to share, and the next check to run.

Client Acquisition and Journey Brief

Using the Catchr MCP, analyze Piwik performance for [Client Site or App] over [Reporting Period] versus [Comparison Period]. Break down Sessions, Visitors, Bounce rate, Goal conversions, Goal conversion rate, Orders, Order rate, and Revenue by Channel, Source / medium, Campaign name, and Session entry URL; use Session exit URL and Exit rate to localize journey friction. Produce a client-ready brief with three wins, three risks, and one evidence-based acquisition, landing-page, or journey action for each risk, and clearly distinguish measured findings from hypotheses that require validation.

Portfolio Consent and Measurement Watch

Using the Catchr MCP, review daily Piwik data for [List of Client Sites or Apps] over [Analysis Period] against [Baseline Period]. Compare Consent form impressions, Consent form clicks, Full consents, Any consents, No consents, No decisions, Consents to analytics, Sessions, Goal conversions, and Orders by Site or app name. Flag abrupt consent-rate shifts, sudden zeros, or conversion drops that coincide with a consent change; rank affected clients by business impact and provide the first impacted date, supporting metrics, likely consent or tracking area to validate, and a concise client-facing explanation without exposing visitor-level data.

Morning Client Analytics Priority Queue

Using the Catchr MCP, pull Piwik data for [List of Client Sites or Apps] for [Recent Period] and compare it with [Baseline Period and Client KPI Targets]. For each client, review Sessions, Visitors, Bounce rate, Events per session, Goal conversions, Goal conversion rate, Orders, and Revenue where applicable. Rank clients by urgency and business impact, identify the largest measurable driver through Channel, Source / medium, Campaign name, Device type, or Session entry URL, and give the freelancer one sentence on what changed, one evidence-based likely cause, and the first action to take today.

Monthly Website and Product Story

Using the Catchr MCP, create a client-ready Piwik report for [Client Site or App] covering [Reporting Period] versus [Previous Period]. Summarize Visitors, Sessions, Page views, Bounce rate, Events, Goal conversions, Goal conversion rate, Orders, Order rate, and Revenue, then explain the most important changes by Channel, Source / medium, Campaign name, Device type, and the configured Custom event category, Custom event action, or Custom event name values relevant to [Client Objective]. Write in plain English with an executive summary, what improved, what declined, data limitations, and three priorities for [Next Period].

Landing Page and Device Action Backlog

Using the Catchr MCP, analyze Piwik landing-page performance for [Client Site or App] over [Period] versus [Comparison Period]. By Session entry URL, Session entry title, and Device type, compare Sessions, Bounces, Bounce rate, Page views, Exits, Exit rate, Goal conversions, Goal conversion rate, Orders, Page generation time, Time until DOM is ready, and Time to interact where available. Require [Minimum Sessions], rank high-traffic pages with weak engagement, conversion, or speed signals, and produce a client-ready backlog with evidence, recommended test, expected impact, KPI, and review date for every item.

Product Funnel Leak Finder

Using the Catchr MCP, pull Piwik e-commerce data for [Store Site or App] over [Period] and compare it with [Comparison Period]. By Product category, Product name, Product SKU, and Device type, analyze Product detail views, Adds to cart, Cart-to-detail rate, Orders, Order-to-detail rate, Product quantity, Product revenue, and Revenue. Apply [Minimum Product Detail Views], identify the funnel stage and products responsible for the largest lost opportunity, and recommend three prioritized merchandising, product-page, or checkout actions with a success metric for each.

Abandoned Cart Recovery Map

Using the Catchr MCP, analyze Piwik cart performance for [Store Site or App] over [Period] versus [Comparison Period]. Compare Adds to cart, Removes from cart, Abandoned carts, Cart abandonment rate, Abandoned cart value, Orders, Order rate, and Revenue by Product category, Product name, Source / medium, and Device type. Rank segments by recoverable Abandoned cart value, flag combinations where abandonment rises while orders fall, and create an action plan covering checkout friction, device experience, offer or shipping review, and tracking validation, with an owner placeholder [Owner] and KPI for every action.

Acquisition Revenue Mix Optimizer

Using the Catchr MCP, evaluate acquisition quality for [Store Site or App] over [Current Period] versus [Comparison Period]. Break down Sessions, Visitors, Bounce rate, Product detail views, Adds to cart, Orders, Order rate, and Revenue by Channel, Source / medium, Campaign ID, Campaign name, Campaign content, and Session entry URL. Apply [Minimum Sessions or Orders], rank traffic sources and campaigns as Scale, Hold, or Investigate against [Revenue or Order-Rate Target], identify whether each weakness comes from traffic quality, landing-page engagement, or checkout progression, and recommend the next budget, tagging, or site action supported by the data.

Piwik Tracking Integrity Audit

Using the Catchr MCP, audit aggregated Piwik data for [Site or App or All Connected Sites] over [Period], grouped by Site or app name and Date. Check completeness and consistency for Sessions, Visitors, Page views, Unique page views, Events, Goal conversions, Unique goal conversions, Orders, Product revenue, and Revenue. Flag missing dates, duplicate site-date groups, negative values, Unique page views above Page views, Visitors above Sessions, conversions without Sessions, Revenue without Orders, and sudden zeros after stable activity. Return a reproducible exception table with failed rule, observed values, severity, first affected date, likely instrumentation area, and exact validation step.

Event and Campaign Taxonomy Monitor

Using the Catchr MCP, inspect Piwik taxonomy for [Site or App] over [Period] using Custom event category, Custom event action, Custom event name, Goal ID, Campaign ID, Campaign name, Campaign content, Source, Medium, and Source / medium. Weight issues with Custom events, Unique custom events, Sessions, Goal conversions, Orders, and Revenue; flag blanks, inconsistent casing, duplicate naming variants, IDs mapped to multiple labels, unexpected source-medium combinations, and high-volume events or campaigns with unusable identity. Deliver a normalized mapping proposal and a remediation queue ranked by reporting impact, with [Owner], proposed standard, and validation query.

Consent-Aware Data Coverage Monitor

Using the Catchr MCP, pull daily aggregated Piwik data for [Site or App or All Connected Sites] over [Lookback Period] and compare each day with a trailing [Baseline Window]. Monitor Consent form impressions, Consent form clicks, Full consents, No consents, No decisions, Consents to analytics, Consents to conversion tracking, Sessions, Events, Goal conversions, Orders, and Revenue by Site or app name and Device type. Apply [Minimum Volume Threshold], flag shifts beyond [Statistical Threshold], and classify each as likely consent-mix change, tracking break, or genuine behavior change. Return the evidence, confidence level, affected reporting coverage, and next validation query using aggregated data only.

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

Connect Piwik to ChatGPT

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How to connect Piwik to ChatGPT ?

Authorize the Piwik 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 Piwik prompts for analyzing real account data.

Piwik to ChatGPT FAQs

What Piwik data can ChatGPT analyze through Catchr?

How granular can Piwik analysis be in ChatGPT?

Can ChatGPT explain traffic, engagement, or conversion changes in Piwik?

Can ChatGPT identify funnel and measurement issues in Piwik?

What types of prompts work best for Piwik analysis?

Can I combine Piwik with other data sources in ChatGPT?

Can I analyze multiple accounts, properties, sites, or apps together?

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

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

Can ChatGPT change anything in Piwik 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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