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Connect Matomo to ChatGPT

Connect Matomo to ChatGPT and ask about any metrics or dimensions using current integrations data. No CSV exports or manual campaign summaries.

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How to connect Matomo to ChatGPT ?

Three steps to your first source-aware prompt.

Step one

Authorize the Matomo account in Catchr

Select Matomo, sign in, and choose the client or business accounts you want to connect.

Client A · Connected sources
5 sources ready
Meta Ads 3 advertising accounts Connected
Google Ads 2 advertising accounts Connected
Google Analytics 4 1 web property Connected
HubSpot 1 CRM portal Connected
Step two

Add the Catchr MCP from official ChatGPT store

Configure the Catchr remote MCP connection in ChatGPT using the connector details from Catchr.

Step three

Choose, adapt, and run a prompt.

Replace account, period, KPI target, and threshold variables before you ask ChatGPT.

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

“Why did CPA rise?” sounds simple. The answer is usually buried across exports, formulas, filters, and tabs before the analysis can even start.

Pull another CSV

Choose the right account, date range, breakdowns, and fields. Then wait for the file and do it again when the question changes.

Rebuild the context

Rename columns, fix formats, join tabs, and check formulas before you can trust the comparison.

Summarize it by hand

Turn the numbers into a client-ready answer, then repeat the whole process for the inevitable follow-up.

Ask the account. Get to the explanation.

Catchr MCP gives ChatGPT access to the marketing accounts you select, so each follow-up starts with the same marketing context instead of a new manual export.

The hard way

Prepare data before every question.

  • Export files from the marketing platform
  • Reformat and reconcile columns
  • Rebuild the analysis for each follow-up
The Catchr way

Connect once. Keep asking.

  • Select the right accounts and data
  • Ask in the language your team already uses
  • Investigate with follow-up questions

Twelve Matomo prompts for analyzing real account data.

Choose your role, open a workflow, then replace the bracketed variables before pasting the prompt into ChatGPT. Every prompt asks for evidence, limits, and a concrete output.

Agency promptCopy prompt
Multi-Site Client Health Radar
Using the Catchr MCP, pull Matomo data for [List of Client Websites/Accounts] over [Period] and compare it with [Comparison Period]. For each Website, summarize Visits, Unique visitors, Pageviews, Bounce Rate, Avg. Time on Website, Conversions, Conversion Rate, Unique Purchases, and Revenue where available. Score each client as Healthy, Watch, or Critical against [Client Targets or Historical Baseline], identify the metric driving every Watch or Critical status, and return a ranked action list so the consultant knows which client to contact first and what to investigate.
Client Acquisition and Conversion Brief
Using the Catchr MCP, analyze Matomo acquisition performance for [Client Website/Account] over [Period] versus [Comparison Period]. Break down Visits, Bounce Rate, Conversions, Conversion Rate, Unique Purchases, and Revenue by Source - Medium, Campaign Name, Campaign Source, and Campaign Medium. Identify the channels and campaigns driving growth or decline, distinguish traffic-volume changes from conversion-efficiency changes, and produce a client-ready brief with three wins, three risks, and one evidence-based next action for each risk.
Portfolio Tracking Anomaly Watchlist
Using the Catchr MCP, review aggregated Matomo data for [List of Client Websites/Accounts] over [Period], grouped by Website and Date. Monitor Visits, Unique visitors, Pageviews, Events, Conversions, Unique Purchases, and Revenue against each site's [Baseline Window]. Flag sudden zeros, gaps, spikes, or broken relationships such as Pageviews with zero Visits or Revenue with zero Unique Purchases. Return a prioritized watchlist with the affected client, first impacted date, evidence, likely tracking area to validate, and a specific next check; keep the output privacy-safe by excluding UserId and any user-level detail.
Morning Client Website Priority Queue
Using the Catchr MCP, pull Matomo data for [List of Client Websites/Accounts] for [Recent Period] and compare it with [Baseline Period]. For each Website, review Visits, Unique visitors, Bounce Rate, Avg. Time on Website, Conversions, Conversion Rate, Unique Purchases, and Revenue where available. Flag meaningful deterioration against [Client KPI Targets or Historical Baseline], rank clients by urgency and business impact, and give the freelancer one sentence on what changed, one likely cause supported by the data, and the first check or action to take today.
Monthly Website Performance Story
Using the Catchr MCP, pull Matomo data for [Client Website/Account] for [Reporting Period] and [Previous Period]. Summarize Visits, Unique visitors, Pageviews, Bounce Rate, Avg. Time on Website, Conversions, Conversion Rate, Unique Purchases, Average Order Value, and Revenue, then explain the most important changes by Source - Medium and Campaign Name. Write a concise client-ready report in plain English covering what improved, what declined, what the data can and cannot prove, and the three priorities for [Next Period].
Landing Page Optimization Backlog
Using the Catchr MCP, analyze landing-page performance for [Client Website/Account] over [Period]. By Entry Page URL and Entry Page title, compare Entrances, Bounces, Bounce Rate, Pageviews, Avg. time on page, Avg. page load time, Conversions, Conversion Rate, and Revenue where available. Apply [Minimum Entrances] to avoid low-volume conclusions, identify pages with high traffic but weak engagement or conversion and pages with slow loading plus high bounce, then create a backlog ranked by expected impact and effort with one test, KPI, and review date per page.
Product Revenue and Cart-Risk Scorecard
Using the Catchr MCP, pull Matomo e-commerce data for [Website/Account] over [Period] and compare it with [Comparison Period]. By Product Category, Product Name, and Product SKU, report Unique Purchases, Quantity, Product Revenue, Average Price, Average Quantity, and Products left in cart. Rank products by revenue contribution and cart-risk, flag products whose Products left in cart rise while Unique Purchases or Product Revenue fall, and recommend the three product, pricing, merchandising, or checkout checks with the highest likely impact.
Checkout Journey Leak Detector
Using the Catchr MCP, analyze the e-commerce journey for [Website/Account] over [Period] using [Cart URL Pattern], [Checkout URL Pattern], and [Confirmation URL Pattern]. Group Pageviews, Unique Pageviews, Exits, Exit rate, Avg. time on page, Events, Conversions, Unique Purchases, and Revenue by Page URL and Page Title. Compare each journey step with [Comparison Period], identify the pages where exits rise or progression weakens, separate low-traffic noise using [Minimum Pageviews], and return a prioritized list of UX, performance, tracking, and checkout tests with a success metric for each.
Privacy-Safe Acquisition Revenue Mix
Using the Catchr MCP, evaluate acquisition quality for [Website/Account] over [Period] using aggregated Matomo data only. Compare Visits, Bounce Rate, Conversions, Conversion Rate, Unique Purchases, Average Order Value, and Revenue across Source - Medium, Channel Type, Campaign Name, and Campaign Source. Suppress segments below [Minimum Visit Threshold], exclude UserId and other user-level output, identify which sources bring valuable versus low-quality traffic, and recommend budget, landing-page, or campaign-tagging actions supported by the observed changes versus [Comparison Period].
Matomo Metric Integrity Audit
Using the Catchr MCP, audit Matomo data for [Website/Account or All Connected Websites] over [Period], grouped by Website and Date. Check completeness and consistency for Visits, Unique visitors, Users, Pageviews, Unique Pageviews, Events, Conversions, Unique Purchases, Product Revenue, and Revenue. Flag missing Website or Date values, duplicate Website-Date groups, negative metrics, Pageviews with zero Visits, Unique Pageviews above Pageviews, Unique visitors above Visits, or Revenue present with zero Unique Purchases. Return an exception table with the failed rule, observed values, severity, first affected date, and recommended validation step.
Campaign Taxonomy Hygiene Monitor
Using the Catchr MCP, inspect Matomo acquisition dimensions for [Website/Account] over [Period]: Campaign Id, Campaign Name, Campaign Source, Campaign Medium, Campaign Content, Campaign Keyword, Source - Medium, and Channel Type. Weight issues using Visits, Conversions, and Revenue, and flag blank values, inconsistent casing, duplicate naming variants, unexpected source-medium combinations, and campaigns with traffic but no usable campaign identity. Deliver a normalized mapping proposal and a remediation queue ranked by reporting impact, including the affected value, proposed standard, owner placeholder [Owner], and validation query.
Privacy-Preserving Segment Stability Monitor
Using the Catchr MCP, pull aggregated Matomo data for [Website/Account] over [Lookback Period], grouped by Date and privacy-safe dimensions such as Device type, Browser, Country, User Type, and Channel Type. Monitor Visits, Unique visitors, Bounce Rate, Avg. Time on Website, Conversions, and Conversion Rate against a trailing [Baseline Window], suppress any segment below [Minimum Visits], and never return UserId or individual-level records. Flag statistically unusual shifts beyond [Z-score Threshold], classify each as likely mix change, tracking issue, or genuine behavior change, and provide the evidence and next validation step.
Replace [variables] Facts ≠ hypotheses Action + follow-up metric

Matomo to ChatGPT FAQs

Clear answers for marketers comparing connectors, data sources, reporting workflows, and dashboard setup.

What Matomo data can ChatGPT analyze through Catchr?

ChatGPT can query connected Matomo data for traffic, audience, acquisition, engagement, conversion, revenue, and behavioral reporting.

Representative measures include Users, New Users, Returning Users, Conversion Rate, and Conversions. Useful breakdowns include Date, Campaign Name, Campaign Source, Campaign Medium, and Source - Medium. The exact field set depends on the selected dataset and compatible reporting reporting level.

How granular can Matomo analysis be in ChatGPT?

The available detail depends on the fields returned for the selected dataset. Useful breakdowns include Date, Campaign Name, Campaign Source, Campaign Medium, and Source - Medium.

Ask ChatGPT to state the reporting level it used and keep incompatible levels separate before calculating totals, rates, or comparisons.

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

Yes. ChatGPT can compare acquisition, engagement, conversion, and revenue signals across periods and segments. Relevant fields include Users, New Users, Returning Users, Conversion Rate, and Conversions.

Set the business target, comparison period, and minimum volume before requesting priorities or recommendations.

Can ChatGPT identify funnel and measurement issues in Matomo?

Yes. ChatGPT can surface funnel drop-offs, tracking gaps, unusual metric relationships, or sudden data shifts. Useful breakdowns include Date, Campaign Name, Campaign Source, Campaign Medium, and Source - Medium.

Ask it to separate observed data, possible explanations, and the next validation step so an unusual value is not presented as a proven cause.

What types of prompts work best for Matomo analysis?

Strong prompts name the action, account or entity, date range, comparison, and KPI or threshold.

  • Monitor: “Product Revenue and Cart-Risk Scorecard”
  • Diagnose: “Checkout Journey Leak Detector”
  • Find opportunities: “Landing Page Optimization Backlog”
  • Report: “Monthly Website Performance Story”

Can I combine Matomo with other data sources in ChatGPT?

Yes, when the other sources are also connected to Catchr. Useful combinations include advertising, commerce, CRM, email, or finance sources.

Align dates, currencies, identifiers, and definitions first. If the sources cannot be joined reliably, ask for a side-by-side comparison rather than a single attributed result.

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

Yes, provided each one is connected and available through Catchr MCP. Ask for separate results first, then create the combined view.

Specify the property, timezone, attribution rules, event definitions, period, and KPI target. This keeps one large entity or a definition mismatch from distorting the comparison.

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

You need access that can authorize and view the relevant Matomo data, a Catchr workspace with the source connected, and Catchr MCP enabled in ChatGPT.

After selecting the required entities, you can ask questions in natural language without preparing a new CSV export for each analysis.

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

ChatGPT analyzes the records returned through the connected Catchr source; it should not assume the data is real time. Freshness and historical coverage can vary by dataset, field, selected period, and source API limits.

Ask it to state the latest session, event, page, call, or reporting date, together with the timezone, requested period, and any missing intervals before interpreting a trend.

Can ChatGPT change anything in Matomo through Catchr?

No. Catchr MCP provides Matomo data for analysis; it does not give ChatGPT permission to change tracking, events, properties, goals, or analytics settings.

Use the result to prepare an action plan, then make operational changes in Matomo. Review the supporting figures before acting on the recommendation.

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

Catchr MCP is included in every standard plan—there is no separate fee for the ChatGPT integration. The Starter plan begins at $20 per month when billed annually, or $24 when billed monthly.

It includes 3 platforms, 10 accounts, unlimited users, and unlimited requests. Larger plans increase the number of platforms and accounts available. See Catchr pricing

‍Can I try the ChatGPT integration before choosing a plan?

Yes. Catchr offers a 14-day free trial with no credit card required.

You can use the trial to connect your marketing sources, authorize Catchr MCP in ChatGPT, and test questions using your own data before subscribing.

Still have a question ? 

Our teams is always here to responds to any question you could have about our data connector. 

Ask the account question before building another export.

Connect yout marketing platform to ChatGPT with Catchr MCP and start investigating current campaign performance.

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