{"id":1884,"date":"2025-01-29T21:08:11","date_gmt":"2025-01-29T20:08:11","guid":{"rendered":"https:\/\/webmasterei-prange.de\/matomo-looker-studio-reporting\/"},"modified":"2025-09-23T22:15:14","modified_gmt":"2025-09-23T20:15:14","slug":"matomo-looker-studio-reporting","status":"publish","type":"post","link":"https:\/\/webmasterei-prange.de\/en\/matomo-looker-studio-reporting\/","title":{"rendered":"Matomo Looker Studio Reporting"},"content":{"rendered":"<style>.kb-image1183_8cf785-00 .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<figure class=\"wp-block-kadence-image kb-image1183_8cf785-00 size-full\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/webmasterei-prange.de\/wp-content\/uploads\/2025\/09\/Flowchart-Abb.1.jpg.webp\" alt=\"Flowchart fig.1\" width=\"960\" height=\"540\" class=\"kb-img wp-image-1880 \"><\/figure>\n\n<p>Are you already using Matomo and want to expand your web analytics in a data-driven way? Then you&#8217;ve come to the right place. Here you&#8217;ll learn how to close these gaps using Google Looker Studio and the Matomo API, taking individual web analyses to a new level.  <\/p>\n\n<h2 class=\"wp-block-heading\" id=\"toc_Warum_Matomo\">Why Matomo?<\/h2>\n\n<p>Matomo has become widely used as an open-source web analytics solution, especially since the GDPR came into force in 2016. With a <a href=\"https:\/\/trends.builtwith.com\/analytics\/Matomo\" target=\"_blank\" rel=\"noreferrer noopener\">market share of 6%<\/a> in Germany <a href=\"https:\/\/trends.builtwith.com\/analytics\/country\/Germany\" target=\"_blank\" rel=\"noreferrer noopener\">, Matomo ranks second, just behind Google<\/a> . <\/p>\n\n<p>As a website operator, you enjoy full control over your data thanks to independent hosting on your own infrastructure. This minimizes the risk of sharing data with third parties, as is the case with Google Analytics, and allows you to better respond to data protection requirements. However, Matomo does have limitations in certain areas: The user interface appears outdated, permission management is limited, and extensions like conversion exports often incur additional fees.  <\/p>\n\n<h2 class=\"wp-block-heading\" id=\"toc_Looker_Studio_in_Kombination_mit_Matomo_API\">Looker Studio in combination with Matomo (API)<\/h2>\n\n<p>The biggest pain point with Matomo is often the limited reporting. This is where Looker Studio comes in: By connecting to the Matomo API, you can retrieve visit data and then store it in BigQuery (keyword: Matomo BigQuery). There, it can be transformed as needed and finally flexibly processed via Looker Studio (keyword: Matomo Looker Studio).  <\/p>\n\n<h3 class=\"wp-block-heading\" id=\"toc_Technischer_Ablauf\">Technical Process<\/h3>\n\n<p>The data flow from Matomo to visualization in Looker Studio can be summarized in four steps:<\/p>\n\n<ol class=\"wp-block-list\">\n<li><strong>Querying the Matomo API<\/strong><br\/> A Google Cloud Function regularly retrieves the data via the Live.getLastVisitsDetails endpoint.<\/li>\n\n\n\n<li><strong>Storage in BigQuery<\/strong><br\/> The data is cached in Google Cloud Storage and then loaded into a BigQuery table.<\/li>\n\n\n\n<li><strong>Further processing via Dataform<\/strong><br\/> A dataform package transforms your raw data and makes it available for various applications.<\/li>\n\n\n\n<li><strong>Output in Looker Studio<\/strong><br\/> You can integrate the prepared data into Looker Studio either via a native BigQuery connection or another Cloud Function.<\/li>\n<\/ol>\n\n<p>This way, you bypass the limitations of the Matomo interface and gain more flexibility in your web analyses.<\/p>\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"960\" height=\"540\" src=\"https:\/\/webmasterei-prange.de\/wp-content\/uploads\/2025\/09\/Flowchart-Abb.1.jpg.webp\" alt=\"Flowchart fig.1.jpg\" class=\"wp-image-1227\"\/><\/figure>\n\n<h5 class=\"wp-block-heading\">Matomo Looker Studio<\/h5>\n\n<p>Data flow within the solution: A Google Cloud Function retrieves data from Matomo and stores it in BigQuery.<\/p>\n\n<h3 class=\"wp-block-heading\" id=\"toc_Erster_Erfolg_Zugriff_auf_die_Matomo_API\">First Success: Accessing the Matomo API<\/h3>\n\n<p>To access the Matomo API, you need an API token. You create this token in your Matomo user account. The token is sent as a parameter with every request to ensure only authorized users have access.  <\/p>\n\n<p>Since <strong>Matomo version 5,<\/strong> API retrieval is only possible via POST request (in version 4, it was even easier via browser call).<code>filter_limit<\/code> and<code>filter_offset<\/code> You can also control pagination to load even large amounts of data from Matomo in smaller chunks. <\/p>\n\n<p>In practice, a <strong>Google Cloud Function<\/strong> usually handles the cyclical querying of Matomo data. The Cloud Function temporarily stores the data and then imports it into BigQuery. This even allows for intraday analyses. However, how often you actually retrieve your data also depends on factors such as costs and data volume. Queries every four hours have proven to be effective.    <\/p>\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">import requests\nimport json\nimport os\n\nclass Config:\n  url = os.environ.get(\"URL\") # Matomo Url\n  token = os.environ.get(\"TOKEN\") # Matomo API token\n  idSite = os.environ.get(\"SITEID\", 1) # Matomo siteId to fetch\n  backfill_days = int(os.environ.get(\"BACKFILL\", 1)) # Days of Backfill from the current day.\n  filter_limit = int(os.environ.get(\"FILTER_LIMIT\", 250)) # Set the size of visitor logs you want to fetch\n  period = os.environ.get(\"PERIOD\", \"range\") # Period String for Matomo API\n  location = os.environ.get(\"LOCATION\", \"europe-west3\") # BigQuery and Google Cloud Storage Location\n  project_id = os.environ.get(\"PROJECT_ID\") # GCP Project ID\n  dataset_name = os.environ.get(\"DATASET_NAME\", \"matomo\") # BigQuery DataSet Name\n  table_name = os.environ.get(\"TABLE_NAME\", \"incoming_data\") # Temporary table during the storing process\n  logger_name = os.environ.get(\"LOGGER_NAME\", \"matomo_api\") # Logger Name for GCP Logs\n  bucket_name = os.environ.get(\"PROJECT_ID\") + \"_\" + os.environ.get(\"BUCKET_NAME\", \"matomo_api_data\") # GCP bucket\n  output_format = 'json' # Do not edit\n  filter_offset = 0 # Do not edit\n\nheaders = {}\n\nreq = {\n  'token_auth': Config.token,\n  'idsite': Config.idSite,\n  'period': Config.period,\n  'date': daterange(params.get(\"date_from\"), params.get(\"date_to\")),\n  'format': Config.output_format,\n  'filter_limit': str(Config.filter_limit),\n  'filter_offset': str(Config.filter_offset),\n}\n\nresponse = requests.post(\n  Config.url + '\/index.php?module=API&amp;method=Live.getLastVisitsDetails',\n  headers=headers,\n  data=req\n)\n\nresp = response.text\njdata = json.loads(resp)\n<\/pre>\n\n<p>Example API call in a Cloud Function: The Live.getLastVisitsDetails endpoint is used.<\/p>\n\n<h3 class=\"wp-block-heading\" id=\"toc_Matomo_getLastVisitsDetails_TrackingRohdaten\">Matomo getLastVisitsDetails \u2260 Raw Tracking Data<\/h3>\n\n<p>The endpoint  <a href=\"https:\/\/developer.matomo.org\/api-reference\/reporting-api#Live\" target=\"_blank\" rel=\"noreferrer noopener\"><code>Live.getLastVisitsDetails<\/code><\/a>  does not provide pure raw data, but already processed information. This includes, for example, cleaned URL parameters such as gclid, fbclid, or msclkid. <\/p>\n\n<ul class=\"wp-block-list\">\n<li><strong>Goals<\/strong> are integrated, while certain events (e.g., <code>addEcommerceItem<\/code>) only appear indirectly as an abandoned shopping cart (<code>ecommerceAbandonedCart<\/code>). <\/li>\n\n\n\n<li>You should omit <strong>irrelevant fields<\/strong> such as icon paths or various aggregations when importing into BigQuery to keep your dataset lean.<\/li>\n<\/ul>\n\n<p>Typical information you receive via <code>Live.getLastVisitsDetails<\/code> includes:<\/p>\n\n<ul class=\"wp-block-list\">\n<li><strong>Visit details<\/strong>: Session duration (in seconds and human-readable form), number of pages viewed, etc.<\/li>\n\n\n\n<li><strong>Referrer Information<\/strong>: Type of referrer (search engine, direct entry, social media), name, URL, keyword.<\/li>\n\n\n\n<li><strong>Device Information<\/strong>: Device type (desktop, tablet, smartphone), operating system, browser, installed plugins.<\/li>\n\n\n\n<li><strong>Location Data<\/strong>: City, region, country (with flag), continent, geo-coordinates, language settings.<\/li>\n\n\n\n<li><strong>Page and Event Data<\/strong>: Visited URLs, titles, time spent, load times, event categories and actions.<\/li>\n\n\n\n<li><strong>E-Commerce Data<\/strong>: Product information (name, SKU, price, category), abandoned carts, order ID, revenue, taxes, shipping, discounts, ordered items.<\/li>\n<\/ul>\n\n<p>Here you will find the complete table with all fields of the<code><a href=\"https:\/\/webmasterei-prange.de\/matomos-api-endpunkt-live-getlastvisitsdetails-im-ueberblick\/\">Live.getLastVisitsDetails<\/a><\/code> .<\/p>\n\n<p>With this broad range of data, you can gain deep insights into your visitors&#8217; behavior and thus significantly improve your web analytics in e-commerce and online marketing.<\/p>\n\n<h3 class=\"wp-block-heading\" id=\"toc_Datentransformation_mit_Dataform\">Data transformation with Dataform<\/h3>\n\n<p>To efficiently prepare your Matomo data, it&#8217;s worth taking a look at <strong>Dataform<\/strong> . This tool is integrated into the Google Cloud Platform and supports you in managing, automating, and orchestrating data pipelines. <\/p>\n\n<p><strong>Advantages of Dataform<\/strong> :<\/p>\n\n<ul class=\"wp-block-list\">\n<li>Seamless Git integration for version control.<\/li>\n\n\n\n<li>SQL workflows can be efficiently managed and automated.<\/li>\n\n\n\n<li>Incremental MERGE logics simplify data updates.<\/li>\n\n\n\n<li>A <strong>compilation graph<\/strong> always gives you a visual overview of tables and dependencies.<\/li>\n<\/ul>\n\n<p>Typically, you create two base tables from the raw data using Dataform, e.g.<code>actions<\/code> and<code>sessions<\/code> , which you can then further split or aggregate. This way, you only load the data you really need into Looker Studio \u2013 saving time and keeping your reports clear. <\/p>\n\n<p>An example is the configuration of the table<code>actions<\/code> . Here is: <\/p>\n\n<ul class=\"wp-block-list\">\n<li><strong>Incremental processing<\/strong> (<code>config.type = \"incremental\"<\/code>).<\/li>\n\n\n\n<li>Only a defined period is updated via <strong>partitioned tables<\/strong>.<\/li>\n\n\n\n<li><strong>Assertions<\/strong> ensure that no duplicate entries are created.<\/li>\n\n\n\n<li>With <strong>pre_operations<\/strong>, certain sessions are deleted to potentially recapture incomplete visits.<\/li>\n\n\n\n<li><strong>JavaScript functions<\/strong> enable central CASE statements (e.g., for channel names).<\/li>\n<\/ul>\n\n<p><\/p>\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;69e92d648f252&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"69e92d648f252\" class=\"wp-block-image size-large wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"709\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/webmasterei-prange.de\/wp-content\/uploads\/2025\/09\/Abb.-3-dataform_tables-1024x709.png\" alt=\"Fig. 3 dataform tables \" class=\"wp-image-1228\"\/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n\n<p>Data flow in Dataform: Data is loaded from the rawdata table and written into actions and sessions.<\/p>\n\n<h3 class=\"wp-block-heading\" id=\"toc_Trigger_Timing_Nachrichten\">Triggers, Timing, Messages<\/h3>\n\n<p>A reliable data pipeline requires well-thought-out orchestration. Instead of fixed times, <strong>triggers and Pub\/Sub messages<\/strong> are usually the better choice: <\/p>\n\n<ol class=\"wp-block-list\">\n<li><strong>Cloud Scheduler<\/strong>: Triggers a Pub\/Sub message and starts the Cloud Function.<\/li>\n\n\n\n<li><strong>Cloud Function<\/strong>: Loads the raw data from Matomo into BigQuery and writes a log entry upon success.<\/li>\n\n\n\n<li><strong>Log sink<\/strong>: Detects the entry and triggers a <strong>workflow<\/strong>.<\/li>\n\n\n\n<li><strong>Workflow<\/strong>: Performs an update of your Dataform package and starts Dataform.<\/li>\n\n\n\n<li><strong>Looker Studio<\/strong>: Retrieves the updated data from BigQuery.<\/li>\n<\/ol>\n\n<p>This ensures that no step starts before the previous one has been successfully completed.<\/p>\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;69e92d648fc22&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"69e92d648fc22\" class=\"wp-block-image aligncenter size-large wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"366\" height=\"1024\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/webmasterei-prange.de\/wp-content\/uploads\/2025\/09\/2025-01-29-09_30_26-Abb.-5.docx-LibreOffice-Writer-400x1118-1-366x1024.png\" alt=\"2025 01 29 09 30 26 fig. 5.docx libreoffice writer 400x1118 \" class=\"wp-image-1229\"\/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n\n<p>Sequence of triggers and messages: Ensuring a smooth process.<\/p>\n\n<h3 class=\"wp-block-heading\" id=\"toc_Datenverwendung_Looker_Studio_als_Beispiel\">Data Usage &#8211; Looker Studio as an Example<\/h3>\n\n<p>Once your data is in BigQuery, you can analyze it with various tools. <strong>Looker Studio<\/strong> is a good choice because it&#8217;s free and easy to get started (a Google account is all you need). With a multi-page Looker Studio dashboard, you can view data on acquisition, behavior, e-commerce, and technical details, among other things. <\/p>\n\n<p>With this flexible structure, you have much more freedom in compiling your reports than the Matomo interface allows.<\/p>\n\n<p><\/p>\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"817\" src=\"https:\/\/webmasterei-prange.de\/wp-content\/uploads\/2025\/09\/Abbildung-6-1024x817.png\" alt=\"Figure 6\" class=\"wp-image-1230\"\/><\/figure>\n\n<p>Looker Studio Report: Overview page of the multi-page report.<\/p>\n\n<h3 class=\"wp-block-heading\" id=\"toc_Kopieren_von_Dashboards_mit_dem_LSD_Cloner\">Copying Dashboards with the LSD Cloner<\/h3>\n\n<p>Looker Studio itself doesn&#8217;t offer integrated versioning for dashboards. This is where the <strong><a href=\"https:\/\/github.com\/google\/looker-studio-dashboard-cloner\" target=\"_blank\" rel=\"noreferrer noopener\">Looker Studio Dashboard Cloner (LSD Cloner)<\/a><\/strong> can help you: <\/p>\n\n<ul class=\"wp-block-list\">\n<li>It copies existing dashboards using the Looker Studio Link API.<\/li>\n\n\n\n<li>A <strong>JSON configuration file<\/strong> specifies how data sources and dashboard names should be adjusted.<\/li>\n\n\n\n<li>The tool is a simple npm package that automatically generates a link for you.<\/li>\n<\/ul>\n\n<p>This allows you to quickly duplicate and customize dashboards for different projects or clients.<\/p>\n\n<h3 class=\"wp-block-heading\" id=\"toc_Fazit\">Conclusion<\/h3>\n\n<p>With the Matomo API endpoint<code>Live.getLastVisitsDetails<\/code> You gain detailed insights into your website&#8217;s visitor behavior. Combining this data with <strong>Matomo BigQuery<\/strong> and <strong>Matomo Looker Studio<\/strong> expands your web analytics capabilities far beyond the standard Matomo interface. <\/p>\n\n<p>Especially in the e-commerce environment, this setup enables more precise conversion analysis and a deeper understanding of your user behavior. Thanks to <strong>Dataform,<\/strong> you can efficiently transform and incrementally update your data, while Looker Studio lets you design flexible, attractive dashboards. Overall, this solution is ideal for you if you work with Matomo professionally and want to conduct state-of-the-art web analytics.  <\/p>\n\n<p>If you need a ready-made solution, submit a request. We have developed a fully automated solution for <a href=\"https:\/\/webmasterei-prange.de\/en\/matomo-bigquery-import\/\">transferring Matomo data to BigQuery<\/a> . <\/p>\n<style>.wp-block-kadence-advancedbtn.kb-btns1226_a2b5f3-43{gap:var(--global-kb-gap-xs, 0.5rem );justify-content:center;align-items:center;}.kt-btns1226_a2b5f3-43 .kt-button{font-weight:normal;font-style:normal;}.kt-btns1226_a2b5f3-43 .kt-btn-wrap-0{margin-right:5px;}.wp-block-kadence-advancedbtn.kt-btns1226_a2b5f3-43 .kt-btn-wrap-0 .kt-button{color:#555555;border-color:#555555;}.wp-block-kadence-advancedbtn.kt-btns1226_a2b5f3-43 .kt-btn-wrap-0 .kt-button:hover, .wp-block-kadence-advancedbtn.kt-btns1226_a2b5f3-43 .kt-btn-wrap-0 .kt-button:focus{color:#ffffff;border-color:#444444;}.wp-block-kadence-advancedbtn.kt-btns1226_a2b5f3-43 .kt-btn-wrap-0 .kt-button::before{display:none;}.wp-block-kadence-advancedbtn.kt-btns1226_a2b5f3-43 .kt-btn-wrap-0 .kt-button:hover, .wp-block-kadence-advancedbtn.kt-btns1226_a2b5f3-43 .kt-btn-wrap-0 .kt-button:focus{background:#444444;}<\/style>\n<div class=\"wp-block-kadence-advancedbtn kb-buttons-wrap kb-btns1226_a2b5f3-43\"><style>ul.menu .wp-block-kadence-advancedbtn .kb-btn1226_17d76e-91.kb-button{width:initial;}<\/style><a class=\"kb-button kt-button button kb-btn1226_17d76e-91 kt-btn-size-standard kt-btn-width-type-auto kb-btn-global-fill  kt-btn-has-text-true kt-btn-has-svg-false  wp-block-kadence-singlebtn\" href=\"https:\/\/webmasterei-prange.de\/matomo-bigquery-import\/\"><span class=\"kt-btn-inner-text\">Matomo BigQuery Importer + Looker Studio Dashboard<\/span><\/a><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Are you already using Matomo and want to expand your web analytics in a data-driven way? Then you&#8217;ve come to the right place. Here you&#8217;ll learn how to close these gaps using Google Looker Studio and the Matomo API, taking individual web analyses to a new level. Why Matomo? Matomo&#8230;<\/p>\n","protected":false},"author":1,"featured_media":1880,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_kad_blocks_custom_css":"","_kad_blocks_head_custom_js":"","_kad_blocks_body_custom_js":"","_kad_blocks_footer_custom_js":"","_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","slim_seo":{"title":"Matomo Looker Studio Reporting - Webmasterei Prange","description":"Are you already using Matomo and want to expand your web analytics in a data-driven way? 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