Matomo External Dashboards & Data Visualisation.pdf
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The document discusses external dashboards and data visualization options for Matomo, emphasizing the importance of customizing data visualizations for different target audiences. It outlines various data transfer methods, including API access, SQL databases, and exporting to external analytic databases, each with its advantages and disadvantages. Additionally, it provides insights into working with Matomo data, including performance considerations and tips for optimizing data queries.
Matomo External Dashboards & Data Visualisation.pdf
- 1. VIU.one External Dashboards & Data Visualization viu.one MatomoCamp 2022
- 2. VIU.one ABOUT ME / ● Online Marketing & Web Analytics since 2001 ● Founder of searchVIU // SEO Data Warehouse & monitoring solution ● Developer of a Matomo Google Data Looker Studio connector michael@searchviu.com https://www.linkedin.com/in/weber-michael/
- 3. VIU.one 02 01 TABLE OF CONTENTS / Why external data visualization? Data visualisation solutions overview 03 Data transfer options 04 Working with data 05 Questions
- 4. VIU.one INDIVIDUAL Matomo has powerful dashboards and widgets - but is limited in visualisation of the data Building Predefined/Filtered Dashboards for each target audience (Management, Departments) Adding data from other sources, combine data sources WHY EXTERNAL DATA VISUALISATION? / TARGET AUDIENCE DATA EXTENSION
- 5. VIU.one Are you using a external visualisation solution for Matomo data already?
- 6. VIU.one DATA VISUALISATION SOLUTIONS / Just some of a wide range of solutions
- 7. VIU.one API Direct access to Matomo API Access to Matomo SQL database Export Matomo data to an external analytic database DATA TRANSFER OPTIONS / SQL DATABASE ACCESS DATA TRANSFER
- 8. VIU.one Direct access to matomo API DATA TRANSFER OPTIONS / API PROS / ● Direct access to up to date data ● Easiest access to matomo data ● No extra cost/maintenance of a additional database CONS / ● Connector or an alternative must be available or it needs to be developed ● Could be slow ● API is not as flexible like Google Analytics api (Only limited possibilities to combine Metrics & Dimensions without custom reports plugin)
- 9. VIU.one Direct access to Matomo / transfer to a SQL Database DATA TRANSFER OPTIONS / SQL DATABASE ACCESS PROS / ● MySQL Connector is available in most visualisation solutions ● Access to RAW data is possible CONS / ● Setting up a secure connection to the database could be difficult ● If using aggregated analytics data it is also not as flexible like Google Analytics api (Only limited possibilities to combine Metrics & Dimensions without custom reports plugin) ● It can harm the Database performance if log data is used to build reports ● Not available in the matomo cloud
- 10. VIU.one Export / Sync Matomo data to an external analytic database (e.g. from Matomo to Google BigQuery with Airbyte) DATA TRANSFER OPTIONS / DATA TRANSFER PROS / ● Analytical database connectors are available in most visualisation solutions ● You can work directly with the log data ● This makes it possible to combine different metrics and dimensions like you need ● Faster on large data set CONS / ● Setting up a data transfer could be difficult ● You need to write complex SQL queries ● Additional cost for data transfer & analytical database Exporting all Data: https://matomo.org/faq/how-to/faq_24536/
- 11. VIU.one API DATA TRANSFER OPTIONS / SQL DATABASE ACCESS DATA TRANSFER Complexity: easy Cost: small/none Flexibility: small/medium Complexity: medium Cost: medium Flexibility: medium Complexity: high Cost: medium/high Flexibility: high In the next slides we will concentrate on the API / “SQL aggregated analytics data” solution
- 12. VIU.one Which data Transfer Option are you using?
- 13. VIU.one Native connector GETTING DATA INTO A VISUALIZATION SOLUTION / A connector developed for the Matomo integration in the data visualization solution Loading data from the API into a other source for which a connector exists (e.g. Google Sheets) Workaround Accessing Report Tables via MySQL connector SQL Connector
- 14. VIU.one ● Get Export URL of data in Matomo -> Export data into Google Sheets -> Configure Google Sheets as Data Source ● It’s a free solution for getting matomo data into a data visualization solution ● You need time for setting this up for different charts / sources ● The base date-range, filters and segments must be pre-defined GOOGLE SHEETS SOLUTION / https://matomo.org/faq/new-to-piwik/how-to-import-matomo-data-in-to-google-data-studio/ https://schuemann.it/de/2021/12/07/display-matomo-data-in-google-data-studio/
- 15. VIU.one DATA VISUALISATION SOLUTIONS / CONNECTOR * This connector is developed by us No matomo connector available Matomo connector available (paid) * No matomo connector available ** No matomo connector available No matomo connector available No matomo connector available ** Session about “Open source dashboards ontop of Matomo with Apache Superset” from Tomas Persson at 16:00 https://schedule.matomocamp.org/matomocamp-2022/talk/ADJLAW/
- 16. VIU.one WORKING WITH DATA / STRUCTURE OF MATOMO DATA ● Each of the reports in Matomo results in one table of preprocessed data ● Each report has its own API request ● Each report has its dimensions & metrics combinations For each of this reports there must be a own data source (for Mysql, Looker Studio Connector, Spreadsheet etc.)
- 17. VIU.one WORKING WITH DATA / CREATING CHARTS Choose - site - report (e.g. Channel types) - Segment, filter etc. Get API URL, import in spreadsheet, set up schedule Step1: Configuration Step2: Connect Data / Schema Step3: Visualize data Connect MySQL / Choose table Use connector Select dimensions / metrics, create time series/bar/maps charts, tables, scorecards, calculated fields etc.
- 18. VIU.one If you want to combine dimensions or metrics which are not available in one of the matomo default reports you can create a custom report and use it the same way like the predefined reports. Working with Data / Individual Dimensions & Metrics
- 19. VIU.one WORKING WITH DATA / PERFORMANCE CONSIDERATIONS ● Loading Data from matomo can be slow ● E.g. requesting visits over time over the last 12 month compared to previous period with a selected segment can take over 30 seconds in matomo cloud (demo site) ● With more data and requesting other time frames / filters / segments etc. it can take longer
- 20. VIU.one Working with data: Performance tipps - Use smaller date ranges in default view let the user change the date range if needed by adding a date range control - Avoid Main Metric reports There are many metrics in there but the most are available in sub reports also. Querying them in sub reports is in most cases more performant. - Avoid Transferring a big amount of result rows if not needed e.g. Top Landing Pages - limit in matomo query not in data studio - Use Custom Reports to create pre filtered data e.g. for a segment or filtered results like "landing page contains url" - Reduce the number of elements per Looker Studio page - Speed up reports with extract data function from Looker Studio https://support.google.com/looker-studio/answer/9019969?hl=en It extracts data regularly from a data source and stores it for faster access Especially using Data Connector / MySQL Access
- 22. VIU.one Thank you! Slides? Just get in contact: michael@searchviu.com https://www.linkedin.com/in/weber-michael/