Matomo
Follow our setup guide to connect your Matomo connector with QUANTI:
Prebuilt reports and definition
Prerequisites
To connect Matomo to QUANTI:, you need a Matomo account.
Setup instructions
Find your Auth token
Go to Matomo settings Settings Cog Icon > Personal > Security.
At the bottom of the page, click on Create new token.
Confirm your account password.
Enter the purpose for this token.
Choose if the token should only be valid for secure requests (Matomo 5 and newer).
Click on Create new token.
Connector configuration
Authentication
Enter the Auth token you retrieved in the previous step.
Enter the Matomo URL that allows you to access your reports. This should be in the form: https://data.yourwebsite.com.
Connector information
Connector Name: Name your connector. It must be unique.
Dataset ID: Define the ID of the dataset. It must not already exist, as it will be created and data will be sent there.
Select your Advertiser Id: Choose your Advertiser ID.
Select the pre-built reports you want to synchronize, and/or create your own custom reports. To help you configure custom reports, refer to the Custom reports chapter below.
Prebuilt reports
Visitor
visitor_country: Website visits, user actions and conversions segmented by the visitor's country. Dimensions: date, country. Metrics: visits, users, actions, bounces, conversions, converted_visits, total_visit_length, revenue.
visitor_device_type: Website activity broken down by device type (desktop, mobile, tablet). Dimensions: date, device_type. Metrics: visits, users, actions, bounces, conversions, converted_visits, total_visit_length, revenue.
visitor_language: Engagement metrics segmented by the visitor's browser language. Dimensions: date, language. Metrics: visits, users, actions, bounces, converted_visits, total_visit_length, revenue.
Behaviour
behaviour_page: Page-level engagement — entrances, exits, pageviews and time spent per URL. Dimensions: date, page_title, page_url. Metrics: pageviews, entrances, entry_actions, entry_bounces, exits, total_time_spent, visits_following_search.
behaviour_event: Event tracking by category — event counts, unique events and total/average event value. Dimensions: date, event_category. Metrics: events, unique_events, event_value_sum, event_value_avg.
Acquisition
acquisition_campaign: Visitor metrics grouped by marketing campaign name. Dimensions: date, campaign_name. Metrics: visits, users, actions, bounces, conversions, converted_visits, total_visit_length, revenue.
acquisition_channel_type: Website performance aggregated by high-level marketing channel (organic, paid, social, direct…). Dimensions: date, channel_type. Metrics: visits, users, actions, bounces, conversions, converted_visits, total_visit_length, revenue.
acquisition_referrer: Visits and conversions by referring source, type and URL. Dimensions: date, referrer, referrer_type. Metrics: visits, users, actions, bounces, conversions, converted_visits, total_visit_length, revenue.
Prebuilt reports and definition
Custom reports
Matomo custom reports let you query any endpoint of the Matomo Reporting API and bring the result directly into your data warehouse.
Find available methods and fields
Each custom report is built around a Matomo API method (e.g. VisitsSummary.get, Events.getCategory). The method determines which fields are returned.
The reference for all available methods and their fields is the official Matomo Reporting API documentation: 👉 developer.matomo.org/api-reference/reporting-api
Use an AI assistant to speed up the configuration. Rather than browsing the full API reference manually, describe the report you want to reproduce — as you see it in the Matomo interface — to an AI assistant (Claude, ChatGPT…). For example:
"I want to build a custom Matomo report showing event categories with the number of events and their total value. What API method and fields should I use in the QUANTI JSON format
{ "report": "", "flat": "1", "fields": "" }?"
The AI will identify the correct report value and the exact fields string for you.
Configure the custom report
In QUANTI, at the Select pre-built reports step, click Add custom report. Fill in the following JSON:
report(required): The Matomo API method name (e.g."VisitsSummary.get","Events.getCategory")flat: Set to"1"to flatten nested JSON structures — recommended for most reportsfields(optional): Comma-separated list of field names to retrieve. If omitted, all fields returned by the method are ingested — useful for a first run to discover what arrives in BigQuery
Common report examples
Report
report value
Key fields
Visit summary
VisitsSummary.get
nb_visits,nb_uniq_visitors,nb_actions,bounce_rate,avg_time_on_site
Event categories
Events.getCategory
label,nb_events,sum_event_value,avg_event_value
Campaigns
Referrers.getCampaigns
label,nb_visits,nb_actions,bounce_rate,revenue
Channel types
Referrers.getReferrerType
label,nb_visits,nb_actions,avg_time_on_site,bounce_rate
Map your fields (Schema)
After configuring the query, the Schema step lets you define how fields are stored in your data warehouse:
Set the field type (STRING, INTEGER, FLOAT, DATE…) for each field
Check Unique identifiers to mark dimension fields as part of the primary key (e.g.
date,label,website_id) — they collectively form the unique identifier of each row
Once all fields are mapped, click Save to create the custom report table.
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