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• How to measure the performance of a newsletter (or any email) with Matomo

  19 décembre 2017, par InnoCraft

  To be able to grow your business, it is crucial to track all your marketing efforts. This includes all newsletters and emails that you share with people outside of your business. Otherwise, you won’t be able to know which of your daily efforts are yielding results.

  Are you wondering if it is possible to track the performance of an emailing campaign in Matomo (Piwik) efficiently ? Would you like to know if it is technically easy ? No worries, here is a “How to” tutorial showing you how easily you can track an emailing in Matomo properly.

  Different tracking levels for different needs

  There are many things that you may be interested to track, for example :

  

  1. How many users opened your email
  2. How many users interacted with the links in your email
  3. How many users interacted on your website through your email

  Let’s have a look at each of these levels.

  Step 1 – Tracking email and newsletter openings in Matomo

  Tracking email openings requires to add an HTML code to your newsletter. It works through what we call a tracking pixel, a tiny image of 1×1 that is transparent so the user will not be able to see it.
  In order to install it, here is an example of what this code looks like :

  <img src="https://piwik.example.com/piwik.php?idsite=YOUR_PIWIK_WEBSITE_ID&rec=1&bots=1&url=https%3A%2F%2Fexample.com%2Femail-opened%2Fnewsletter_XYZ&action_name=Email%20opened&_rcn=internal%20email%20name&_rck=newsletter_XYZ" style="border:0;” alt="" />

  The Matomo tracking pixel explained

  The above URL is composed of the following URL parameters which are part of our Tracking API :

  • idsite : Corresponds to the ID of the website you would like to track.
  • rec : You need to have rec=1 in order for the request to be actually recorded.
  • bots : Set it to 1 to include all the connections made to this request, bots included.
  • url : corresponds to the URL you would like to display in Matomo (Piwik) every time the email is opened.
  • action_name : This is the page name you would like to be tracked when the email is opened.
  • _rcn : The name you would like to give to your campaign.
  • _rck : The keyword you may like to use in order to summarize the content of your newsletter.

  You may have noticed some special characters here such as “%20”, “%2F”. That’s because the URL is encoded. We strongly recommend you to do so in order for your tracking not to break. Many tools are available on the web in order to encode your URLs such as https://www.urlencoder.org/.

  If you would like to access the previous tracking code easily, keep in mind that you can always find the tracking code generator within the “Matomo admin panel → Tracking code” :

  

  You can find more information about it on our guide at : How do I track how many users open and read my newsletter emails (using a pixel / beacon) ?

  As a result, the information will be pushed as following for any user who opens your email :

  

  To not bias your regular page views on your website with newsletter openings, we recommend tracking newsletter openings into a new website.

  Tracking even more data : the user ID example

  You can go deeper in your URL tracking by inserting other parameters such as the user id if you have this information within your emailing database. One of the main benefit of tracking the User ID is to connect data across multiple devices and browsers for a given user.

  You only need to add the following parameter &uid=XXX where XXX equals the dynamic value of the user ID :

  

  Make sure that UID from your emailing provider is the same as the one used on your website in order for your data to be consistent.

  Important note : some email providers are loading email messages by default which results in an opening even if the user did not actually open the email.

  Step 2 – Measure the clicks within your emailing

  Tracking clicks within an email lets you know with which content readers interacted the most. We recommend tracking all links in all your emails as a campaign, whether it is a newsletter, a custom support email, an email invoice, etc. You might be surprised to see which of your emails lead to conversions and if they don’t, try to tweak those emails, so they might in the future.

  Tracking clicks This works thanks to URL campaign tracking. In order to perform this action, you will need to add Matomo (Piwik) URL parameters to all your existing link URLs :

  • Website URL : for example “www.your-website.com”.
  • Campaign name : for example “pk_campaign=emailing”. Represents the name you would like to give to your campaign.
  • Campaign keyword : for example “pk_keyword=name-of-your-article”. Represents the name you would like to give to your content.
  • Campaign source : for example “pk_source=newsletter”. Represents the name of the referrer.
  • Campaign medium : for example “pk_medium=email”. Represents the type of referrer you are using.
  • Campaign content : for example “pk_content=title”. Represents the type of content.

  You can find more information about campaign url tracking in our “Tracking marketing campaigns with Matomo” guide.

  Here is a sample showing you how you can differentiate some links in a newsletter, all pointing to the same URL :

  

  Once you have added these URL parameters to each of your link, Matomo (Piwik) will clearly indicate the referrer of this specific campaign when a user clicks on a link in the newsletter and visits your website.

  Important note : if you do not track your campaigns, it will result in a bad interpretation of your data within Matomo (Piwik) as you will get webmail services or direct entries as referrer instead of your newsletter campaign.

  Step 3 – Measure emailing performances on your website

  Thanks to Matomo (Piwik) URL campaign parameters, you can now clearly identify the traffic brought through your emailing. You can now specifically isolate users who come from emails by creating a segment :

  

  Once done, you can either have a look at each user specifically through the visitor log report or analyze it as a whole within the rest of the reports.

  You can even measure your return on investment directly if goals have been defined. In order to know more about how to track goals within Matomo (Piwik).

  Did you like this article ?

  If you enjoyed reading this article, do not hesitate to share it around you. Moreover, if there are any topics you would like to write us about in particular, just drop us an email and we will be more than happy to write about it.

  The post How to measure the performance of a newsletter (or any email) with Matomo appeared first on Analytics Platform - Matomo.

• ffmpeg encoding .mp4 fails in safari when hosted from s3. handbrake encoded video works first time

  11 juin 2018, par Simon Rogers

  The mp4 videos I’ve encoded with ffmpeg work perfectly in Safari if stored locally, but break if hosted from s3. I have tried countless encoding settings to no avail.

  However having just run a mov quickly through Handbrake and ticking ’optimise for web’ and encoding baseline @ 4.0, this has worked perfectly first time.

  I don’t understand what could be going wrong with my ffmpeg encoding.

  Things I have noticed about files from two separate encoders which work :

  They both have yuv420p(tv, bt709) whereas ffmpeg is just saying yuv420p – this is the only thing I can identify from ffprobe that is consistently different.

  I have done a fresh install of ffmpeg to no avail :

  ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"

  brew install ffmpeg --with-fdk-aac --with-ffplay --with-freetype --with-libass  --with-libvorbis --with-libvpx --with-opus --with-x265

  This error appears in all the files I have encoded with ffmpeg :

  Unsupported codec with id 0 for input stream 1

  ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––

  mp4box gives the following for the ffmpeg video, which doesn’t work :

   Tempuras-iMac:tests tempura$ mp4box -info /Users/tempura/tests/mov-output-10-1400.mp4
  
  * Movie Info *
  
  Timescale 1000 - 1 track
  
  Computed Duration 00:00:10.967 - Indicated Duration 00:00:10.967
  
  Fragmented File: no
  
  File suitable for progressive download (moov before mdat)
  
  File Brand isom - version 512
  
      Compatible brands: isom iso2 avc1 mp41
  
  Created: UNKNOWN DATE   Modified: UNKNOWN DATE
  
  File has no MPEG4 IOD/OD
  
  
  
  iTunes Info:
  
  Encoder Software: Lavf58.12.100
  
  1 UDTA types: meta (1) 
  
  
  
  Track # 1 Info - TrackID 1 - TimeScale 15360
  
  Media Duration 00:00:10.966 - Indicated Duration 00:00:10.966
  
  Track has 1 edit lists: track duration is 00:00:10.967
  
  Media Info: Language "English (eng)" - Type "vide:avc1" - 329 samples
  
  Visual Track layout: x=0 y=0 width=1800 height=1200
  
  MPEG-4 Config: Visual Stream - ObjectTypeIndication 0x21
  
  AVC/H264 Video - Visual Size 1800 x 1200
  
  AVC Info: 1 SPS - 1 PPS - Profile Baseline @ Level 4
  
  NAL Unit length bits: 32
  
  Pixel Aspect Ratio 1:1 - Indicated track size 1800 x 1200
  
  Chroma format YUV 4:2:0 - Luma bit depth 8 - chroma bit depth 8
  
  SPS#1 hash: 2BD106A8DFD73B92825D87D4D312B22F9CEC1986
  
  PPS#1 hash: 656AE5F3BE854F3C8B889E72310662390F18EDBD
  
  Self-synchronized
  
  RFC6381 Codec Parameters: avc1.42C028
  
  Average GOP length: 329 samples

  And gives the following for two videos that do work.

  First :

  Tempuras-iMac:tests tempura$ mp4box -info /Users/tempura/tests/mov-output-05-1400.mp4 
  
  [iso file] Unknown box type tmcd
  
  [iso file] Read Box type  (0x00000000) has size 0 but is not at root/file level, skipping
  
   * Movie Info *
  
  Timescale 1000 - 2 tracks
  
  Computed Duration 00:00:10.967 - Indicated Duration 00:00:10.967
  
  Fragmented File: no
  
  File suitable for progressive download (moov before mdat)
  
  File Brand isom - version 512
  
      Compatible brands: isom iso2 avc1 mp41
  
  Created: UNKNOWN DATE   Modified: UNKNOWN DATE
  
  File has no MPEG4 IOD/OD
  
  
  
  iTunes Info:
  
  Encoder Software: Lavf58.12.100
  
  1 UDTA types: meta (1) 
  
  
  
  Track # 1 Info - TrackID 1 - TimeScale 15360
  
  Media Duration 00:00:10.966 - Indicated Duration 00:00:10.966
  
  Track has 1 edit lists: track duration is 00:00:10.967
  
  Media Info: Language "English (eng)" - Type "vide:avc1" - 329 samples
  
  Visual Track layout: x=0 y=0 width=1800 height=1200
  
  MPEG-4 Config: Visual Stream - ObjectTypeIndication 0x21
  
  AVC/H264 Video - Visual Size 1800 x 1200
  
  AVC Info: 1 SPS - 1 PPS - Profile Baseline @ Level 4
  
  NAL Unit length bits: 32
  
  Pixel Aspect Ratio 1:1 - Indicated track size 1800 x 1200
  
  Chroma format YUV 4:2:0 - Luma bit depth 8 - chroma bit depth 8
  
  SPS#1 hash: 39D86732FD5F78B18F2E83C651FAE38EA0E30A6D
  
  PPS#1 hash: 656AE5F3BE854F3C8B889E72310662390F18EDBD
  
  Self-synchronized
  
  RFC6381 Codec Parameters: avc1.42C028
  
  Average GOP length: 329 samples
  
  
  
  Track # 2 Info - TrackID 2 - TimeScale 15360
  
  Media Duration 00:00:10.966 - Indicated Duration 00:00:10.966
  
  Track has 1 edit lists: track duration is 00:00:10.967
  
  Track is disabled
  
  Media Info: Language "Undetermined (und)" - Type "tmcd:tmcd" - 1 samples
  
  Unknown media type
  
  RFC6381 Codec Parameters: tmcd
  
  All samples are sync

  Second :

  Tempuras-iMac:tests tempura$ mp4box -info /Users/tempura/Documents/yes_2106.mp4 
  
  * Movie Info *
  
  Timescale 30000 - 1 track
  
  Computed Duration 00:00:10.966 - Indicated Duration 00:00:10.966
  
  Fragmented File: no
  
  File suitable for progressive download (moov before mdat)
  
  File Brand isom - version 1
  
      Compatible brands: isom avc1 mp42
  
  Created: GMT Fri Jun  1 11:24:54 2018
  
  Modified: GMT Fri Jun  1 11:24:54 2018
  
  
  
  File has root IOD (9 bytes)
  
  Scene PL 0xff - Graphics PL 0xff - OD PL 0xff
  
  Visual PL: ISO Reserved Profile (0x15)
  
  Audio PL: No audio capability required (0xff)
  
  No streams included in root OD
  
  
  
  Track # 1 Info - TrackID 1 - TimeScale 30
  
  Media Duration 00:00:10.966 - Indicated Duration 00:00:10.966
  
  Media Info: Language "Undetermined (und)" - Type "vide:avc1" - 329 samples
  
  Visual Track layout: x=0 y=0 width=1800 height=1200
  
  MPEG-4 Config: Visual Stream - ObjectTypeIndication 0x21
  
  AVC/H264 Video - Visual Size 1800 x 1200
  
  AVC Info: 1 SPS - 1 PPS - Profile Baseline @ Level 4.2
  
  NAL Unit length bits: 32
  
  Pixel Aspect Ratio 1:1 - Indicated track size 1800 x 1200
  
  Chroma format YUV 4:2:0 - Luma bit depth 8 - chroma bit depth 8
  
  SPS#1 hash: ED5CFE0A3F65F36ADCFA347C1273A29784E8AEAC
  
  PPS#1 hash: 7ECF7597FDDAC5F8C82B54BFB40A1F9A8D8807FA
  
  Self-synchronized
  
  RFC6381 Codec Parameters: avc1.42C02A
  
  Average GOP length: 329 samples

• A Guide to App Analytics Tools that Drive Growth

  7 mars, par Daniel Crough — App Analytics

  Mobile apps are big business, generating £438 billion in global revenue between in-app purchases (38%) and ad revenue (60%). And with 96% of apps relying on in-app monetisation, the competition is fierce.

  To succeed, app developers and marketers need strong app analytics tools to understand their customers’ experiences and the effectiveness of their development efforts.

  This article discusses app analytics, how it works, the importance and benefits of mobile app analytics tools, key metrics to track, and explores five of the best app analytics tools on the market.

  What are app analytics tools ?

  Mobile app analytics tools are software solutions that provide insights into how users interact with mobile applications. They track user behaviour, engagement and in-app events to reveal what’s working well and what needs improvement.

  Insights gained from mobile app analytics help companies make more informed decisions about app development, marketing campaigns and monetisation strategies.

  What do app analytics tools do ?

  App analytics tools embed a piece of code, called a software development kit (SDK), into an app. These SDKs provide the essential infrastructure for the following functions :

  • Data collection : The SDK collects data within your app and records user actions and events, like screen views, button clicks, and in-app purchases.
  • Data filtering : SDKs often include mechanisms to filter data, ensuring that only relevant information is collected.
  • Data transmission : Once collected and filtered, the SDK securely transmits the data to an analytics server. The SDK provider can host this server (like Firebase or Amplitude), or you can host it on-premise.
  • Data processing and analysis : Servers capture, process and analyse large stores of data and turn it into useful information.
  • Visualisation and reporting : Dashboards, charts and graphs present processed data in a user-friendly format.

  

  Six ways mobile app analytics tools fuel marketing success and drive product growth

  Mobile app analytics tools are vital in driving product development, enhancing user experiences, and achieving business objectives.

  #1. Improving user understanding

  The better a business understands its customers, the more likely it is to succeed. For mobile apps, that means understanding how and why people use them.

  Mobile analytics tools provide detailed insights into user behaviours and preferences regarding apps. This knowledge helps marketing teams create more targeted messaging, detailed customer journey maps and improve user experiences.

  It also helps product teams understand the user experience and make improvements based on those insights.

  For example, ecommerce companies might discover that users in a particular area are more likely to buy certain products. This allows the company to tailor its offers and promotions to target the audience segments most likely to convert.

  #2 Optimising monetisation strategies for increased revenue and user retention

  In-app purchases and advertising make up 38% and 60% of mobile app revenue worldwide, respectively. App analytics tools provide insights companies need to optimise app monetisation by :

  • Analysing purchase patterns to identify popular products and understand pricing sensitivities.
  • Tracking in-app behaviour to identify opportunities for enhancing user engagement.

  App analytics can track key metrics like visit duration, user flow, and engagement patterns. These metrics provide critical information about user experiences and can help identify areas for improvement.

  How meaningful are the impacts ?

  Duolingo, the popular language learning app, reported revenue growth of 45% and an increase in daily active users (DAU) of 65% in its Q4 2023 financial report. The company attributed this success to its in-house app analytics platform.

  

  #3. Understanding user experiences

  Mobile app analytics tools track the performance of user interactions within your app, such as :

  • Screen views : Which screens users visit most frequently
  • User flow : How users navigate through your app
  • Session duration : How long users spend in your app
  • Interaction events : Which buttons, features, and functions users engage with most

  Knowing how users interact with your app can help refine your approach, optimise your efforts, and drive more conversions.

  #4. Personalising user experiences

  A recent McKinsey survey showed that 71% of users expect personalised app experiences. Product managers must stay on top of this since 76% of users get frustrated if they don’t receive the personalisation they expect.

  Personalisation on mobile platforms requires data capture and analysis. Mobile analytics platforms can provide the data to personalise the user onboarding process, deliver targeted messages and recommend relevant content or offers.

  Spotify is a prime example of personalisation done right. A recent case study by Pragmatic Institute attributed the company’s growth to over 500 million active daily users to its ability to capture, analyse and act on :

  • Search behaviour
  • Individual music preferences
  • Playlist data
  • Device usage
  • Geographical location

  The streaming service uses its mobile app analytics software to turn this data into personalised music recommendations for its users. Spotify also has an in-house analytics tool called Spotify Premium Analytics, which helps artists and creators better understand their audience.

  #5. Enhancing app performance

  App analytics tools can help identify performance issues that might be affecting user experience. By monitoring metrics like load time and app performance, developers can pinpoint areas that need improvement.

  Performance optimisation is crucial for user retention. According to Google research, 53% of mobile site visits are abandoned if pages take longer than three seconds to load. While this statistic refers to websites, similar principles apply to apps—users expect fast, responsive experiences.

  Analytics data can help developers prioritise performance improvements by showing which screens or features users interact with most frequently, allowing teams to focus their optimisation efforts where they’ll have the greatest impact.

  #6. Identifying growth opportunities

  App analytics tools can reveal untapped opportunities for growth by highlighting :

  • Features users engage with most
  • Underutilised app sections that might benefit from redesign
  • Common user paths that could be optimised
  • Moments where users tend to drop off

  This intelligence helps product teams make data-informed decisions about future development priorities, feature enhancements, and potential new offerings.

  For example, a streaming service might discover through analytics that users who create playlists have significantly higher retention rates. This insight could lead to development of enhanced playlist functionality to encourage more users to create them, ultimately boosting overall retention.

  Key app metrics to track

  Using mobile analytics tools, you can track dozens of key performance indicators (KPIs) that measure everything from customer engagement to app performance. This section focuses on the most important KPIs for app analytics, classified into three categories :

  • App performance KPIs
  • User engagement KPIs
  • Business impact KPIs

  While the exact metrics to track will vary based on your specific goals, these fundamental KPIs form the foundation of effective app analytics.

  

  App performance KPIs

  App performance metrics tell you whether an app is reliable and operating properly. They help product managers identify and address technical issues that may negatively impact user experiences.

  Some key metrics to assess performance include :

  • Screen load time : How quickly screens load within your app
  • App stability : How often your app crashes or experiences errors
  • Response time : How quickly your app responds to user interactions
  • Network performance : How efficiently your app handles data transfers

  User engagement KPIs

  Engagement KPIs provide insights into how users interact with an app. These metrics help you understand user behaviour and make UX improvements.

  Important engagement metrics include :

  • Returning visitors : A measure of how often users return to an app
  • Visit duration : How long users spend in your app per session
  • User flow : Visualisation of the paths users take through your app, offering insights into navigation patterns
  • Event tracking : Specific interactions users have with app elements
  • Screen views : Which screens are viewed most frequently

  Business impact KPIs

  Business impact KPIs connect app analytics to business outcomes, helping demonstrate the app’s value to the organisation.

  Key business impact metrics include :

  • Conversion events : Completion of desired actions within your app
  • Goal completions : Tracking when users complete specific objectives
  • In-app purchases : Monitoring revenue from within the app
  • Return on investment : Measuring the business value generated relative to development costs

  Privacy and app analytics : A delicate balance

  While app analytics tools can be a rich source of user data, they must be used responsibly. Tracking user in-app behaviour and collecting user data, especially without consent, can raise privacy concerns and erode user trust. It can also violate data privacy laws like the GDPR in Europe or the OCPA, FDBR and TDPSA in the US.

  With that in mind, it’s wise to choose user-tracking tools that prioritise user privacy while still collecting enough data for reliable analysis.

  Matomo is a privacy-focused web and app analytics solution that allows you to collect and analyse user data while respecting user privacy and following data protection rules like GDPR.

  The five best app analytics tools to prove marketing value

  In this section, we’ll review the five best app analytics tools based on their features, pricing and suitability for different use cases.

  Matomo — Best for privacy-compliant app analytics

  Matomo app analytics is a powerful, open-source platform that prioritises data privacy and compliance.

  

  It offers a suite of features for tracking user engagement and conversions across websites, mobile apps and intranets.

  Key features

  • Complete data ownership : Full control over your analytics data with no third-party access
  • User flow analysis : Track user journeys across different screens in your app
  • Custom event tracking : Monitor specific user interactions with customisable events
  • Ecommerce tracking : Measure purchases and product interactions
  • Goal conversion monitoring : Track completion of important user actions
  • Unified analytics : View web and app analytics in one platform for a complete digital picture

  Benefits

  • Eliminate compliance risks without sacrificing insights
  • Get accurate data with no sampling or data manipulation
  • Choose between self-hosting or cloud deployment
  • Deploy one analytics solution across your digital properties (web and app) for a single source of truth

  Pricing

  Plan	Price
  Cloud	Starts at £19/month
  On-Premise	Free

  Matomo is a smart choice for businesses that value data privacy and want complete control over their analytics data. It’s particularly well-suited for organisations in highly regulated industries, like banking.

  While Matomo’s app analytics features focus on core analytics capabilities, its privacy-first approach offers unique advantages. For organisations already using Matomo for web analytics, extending to mobile creates a unified analytics ecosystem with consistent privacy standards across all digital touchpoints, giving organisations a complete picture of the customer journey.

  Firebase — Best for Google services integration

  Firebase is the mobile app version of Google Analytics. It’s the most popular app analytics tool on the market, with over 99% of Android apps and 77% of iOS apps using Firebase.

  

  Firebase is popular because it works well with other Google services. It also has many features, like crash reporting, A/B testing and user segmentation.

  Pricing

  Plan	Price
  Spark	Free
  Blaze	Pay-as-you-go based on usage
  Custom	Bespoke pricing for high-volume enterprise users

  Adobe Analytics — Best for enterprise app analytics

  Adobe Analytics is an enterprise-grade analytics solution that provides valuable insights into user behaviour and app performance.

  

  It’s part of the Adobe Marketing Cloud and integrates easily with other Adobe products. Adobe Analytics is particularly well-suited for large organisations with complex analytics needs.

  Pricing

  Plan	Price
  Select	Pricing on quote
  Prime	Pricing on quote
  Ultimate	Pricing on quote

  While you must request a quote for pricing, Scandiweb puts Adobe Analytics at £2,000/mo–£2,500/mo for most companies, making it an expensive option.

  Apple App Analytics — Best for iOS app analysis

  Apple App Analytics is a free, built-in analytics tool for iOS app developers.

  

  This analytics platform provides basic insights into user engagement, app performance and marketing campaigns. It has fewer features than other tools on this list, but it’s a good place for iOS developers who want to learn how their apps work.

  Pricing

  Apple Analytics is free.

  Amplitude — Best for product analytics

  Amplitude is a product analytics platform that helps businesses understand user behaviour and build better products.

  

  It excels at tracking user journeys, identifying user segments and measuring the impact of product changes. Amplitude is a good choice for product managers and data analysts who want to make informed decisions about product development.

  Pricing

  Plan	Price
  Starter	Free
  Plus	From £49/mo
  Growth	Pricing on quote

  Choose Matomo’s app analytics to unlock growth

  App analytics tools help marketers and product development teams understand user experiences, improve app performance and enhance products. Some of the best app analytics tools available for 2025 include Matomo, Firebase and Amplitude.

  However, as you evaluate your options, consider taking a privacy-first approach to app data collection and analysis, especially if you’re in a highly regulated industry like banking or fintech. Matomo Analytics offers a powerful and ethical solution that allows you to gain valuable insights while respecting user privacy.

  Ready to take control of your app analytics ? Start your 21-day free trial.