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• Switch to Matomo for WordPress from Google Analytics

  10 mars 2020, par Joselyn Khor — Plugins, Privacy
  While Google Analytics may seem like a great plugin option on the WordPress directory, we’d like to present a new ethical alternative called Matomo for WordPress, which gives you 100% data ownership and privacy protection.

  Firstly what does Google Analytics offer in WordPress ?

  When you think of getting insights about visitors on your WordPress (WP) sites, the first thing that comes to mind might be Google Analytics. Why not right ? Especially when there are good free Google Analytics plugins, like Monster Insights and Site Kit. 

  These give you access to a great analytics platform, but the downside with Google Analytics is the lack of transparency around privacy and data ownership.

  

  Matomo Analytics for WordPress is an ethical alternative to Google Analytics for WordPress

  If you’re more interested in a privacy-respecting, GDPR compliant alternative, there’s now a new option on the WP plugins directory : Matomo Analytics – Ethical Stats. Powerful Insights. 

  It’s free and can be considered the #1 ethical alternative to Google Analytics in terms of features and capabilities. Why is it important to choose a web analytics platform that respects privacy ?

  

  Risk facing fines for non-GDPR compliance and privacy/data breaches

  In Europe there’s an overarching privacy law called GDPR which provides better privacy protection for EU citizens on the web. 

  Websites need to be GDPR compliant and follow rules governing how personal data is used or risk facing fines up to 4% of their yearly revenue for data/privacy breaches or non-compliance. Even if your website is based outside of Europe. If you have visitors from Europe, you can still be liable.

  

  In the US, there isn’t one main privacy law, there hundreds on both the federal and state levels to protect the personal data (or personally identifiable information) of US residents – like the California Consumer Privacy Act (CCPA). There are also industry-specific statutes related to data privacy like HIPAA.

  To protect your website from coming under fire for privacy breaches, best practise is to find platforms that are privacy and GDPR compliant by design. 

  When you own your own data – as with the case of Matomo – you have control over where data is stored, what you’re doing with it, and can better protect the privacy of your visitors.

  At this point you may be asking, “what’s the point of an analytics platform if you have to follow all these rules ?”

  The importance of analytics for your WordPress site

  • Figuring out how your audience behaves to increase conversions
  • Setting, tracking and measuring conversion goals
  • Being able to find insights to improve and optimize your site 
  • Making smarter, data-driven decisions so your company can thrive, rather than risk being left behind

  Analytics is used to answer questions like :

  • Where are your website visitors coming from (location) ?
  • How many people visit your website ?
  • Which are the most popular pages on your site ?
  • What sources of traffic are coming to your site (social, marketing campaigns, search) ?
  • Is your marketing campaign performing better this month compared to last ?

  Matomo can answer all of the above questions. BONUS : On top of that, with Matomo you get the peace of mind knowing you’re the only one who has access to those answers.

  

  Matomo Analytics vs Google Analytics on WordPress

  The top 5 most useful features in Matomo Analytics that’s comparable to GA

  1. Campaign measurement – traffic. Matomo also has a URL builder that lets you track which campaigns are working effectively
  2. Tracking goals. Matomo empowers you to set goals you can track. Being able to see this means you can accurately measure your return on investment (ROI) 
  3. Audience reports to learn about visitors. Matomo’s powerful visitors feature lets you learn who is visiting your site, what their journey is and the steps they take to conversion.
  4. In depth view of behaviour with Funnels in Matomo. This tracks the journey of your visitors from the moment they enter your site, to when they leave. Giving you insight into where and why you lose your visitors.
  5. Custom reports. Where you create your unique reports to fit your business goals.

  Other benefits of using Matomo :

  • No data sampling which means you get 100% accurate reporting
  • 100% data ownership
  • Free Tag Manager
  • Search engine keyword rankings
  • Unlimited websites
  • Unlimited team members
  • GDPR manager
  • API access
  • Hosted on your own servers so you have full control over where your data is stored

  Learn more about the differences in this comprehensive table.

  

  Matomo Analytics for WordPress is free !

  Matomo Analytics is the best free Google Analytics alternative on the WordPress Directory. In addition to having comparable features where you can do pretty much do everything you wanted to do in GA. Matomo Analytics for WordPress makes for an ethical choice because you can respect your visitor’s privacy, can become GDPR compliant, and maintain control over your own data.

  Google Analytics leads the market for good reasons. It’s a great free tool for those who want analytics, but there’s no clarity when it comes to grey areas like privacy and data ownership. If these are major concerns for you, Matomo offers complete peace of mind that you’re doing the best you can to stay ethical while growing your business and website.

  It’s just as easy to install in a few click !

  Install and see for yourself !

• Inside WebM Technology : VP8 Intra and Inter Prediction

  20 juillet 2010, par noreply@blogger.com (Lou Quillio)
  Continuing our series on WebM technology, I will discuss the use of prediction methods in the VP8 video codec, with special attention to the TM_PRED and SPLITMV modes, which are unique to VP8.

  
  

  First, some background. To encode a video frame, block-based codecs such as VP8 first divide the frame into smaller segments called macroblocks. Within each macroblock, the encoder can predict redundant motion and color information based on previously processed blocks. The redundant data can be subtracted from the block, resulting in more efficient compression.

  
  Image by Fido Factor, licensed under Creative Commons Attribution License.
  Based on a work at www.flickr.com

  
  

  A VP8 encoder uses two classes of prediction :

  • Intra prediction uses data within a single video frame
  • Inter prediction uses data from previously encoded frames

  The residual signal data is then encoded using other techniques, such as transform coding.

  
  

  VP8 Intra Prediction Modes

  VP8 intra prediction modes are used with three types of macroblocks :

  • 4x4 luma
  • 16x16 luma
  • 8x8 chroma

  Four common intra prediction modes are shared by these macroblocks :
  

  • H_PRED (horizontal prediction). Fills each column of the block with a copy of the left column, L.
  • V_PRED (vertical prediction). Fills each row of the block with a copy of the above row, A.
  • DC_PRED (DC prediction). Fills the block with a single value using the average of the pixels in the row above A and the column to the left of L.
  • TM_PRED (TrueMotion prediction). A mode that gets its name from a compression technique developed by On2 Technologies. In addition to the row A and column L, TM_PRED uses the pixel P above and to the left of the block. Horizontal differences between pixels in A (starting from P) are propagated using the pixels from L to start each row.

  For 4x4 luma blocks, there are six additional intra modes similar to V_PRED and H_PRED, but correspond to predicting pixels in different directions. These modes are outside the scope of this post, but if you want to learn more see the VP8 Bitstream Guide.

  
  

  As mentioned above, the TM_PRED mode is unique to VP8. The following figure uses an example 4x4 block of pixels to illustrate how the TM_PRED mode works :

  

  Where C, As and Ls represent reconstructed pixel values from previously coded blocks, and X₀₀ through X₃₃ represent predicted values for the current block. TM_PRED uses the following equation to calculate X_ij :

  
  

  X_ij = L_i + A_j - C (i, j=0, 1, 2, 3)

  
  

  Although the above example uses a 4x4 block, the TM_PRED mode for 8x8 and 16x16 blocks works in the same fashion.

  TM_PRED is one of the more frequently used intra prediction modes in VP8, and for common video sequences it is typically used by 20% to 45% of all blocks that are intra coded. Overall, together with other intra prediction modes, TM_PRED helps VP8 to achieve very good compression efficiency, especially for key frames, which can only use intra modes (key frames by their very nature cannot refer to previously encoded frames).

  
  

  VP8 Inter Prediction Modes

  
  

  In VP8, inter prediction modes are used only on inter frames (non-key frames). For any VP8 inter frame, there are typically three previously coded reference frames that can be used for prediction. A typical inter prediction block is constructed using a motion vector to copy a block from one of the three frames. The motion vector points to the location of a pixel block to be copied. In most video compression schemes, a good portion of the bits are spent on encoding motion vectors ; the portion can be especially large for video encoded at lower datarates.

  
  

  Like previous VPx codecs, VP8 encodes motion vectors very efficiently by reusing vectors from neighboring macroblocks (a macroblock includes one 16x16 luma block and two 8x8 chroma blocks). VP8 uses a similar strategy in the overall design of inter prediction modes. For example, the prediction modes "NEAREST" and "NEAR" make use of last and second-to-last, non-zero motion vectors from neighboring macroblocks. These inter prediction modes can be used in combination with any of the three different reference frames.

  
  

  In addition, VP8 has a very sophisticated, flexible inter prediction mode called SPLITMV. This mode was designed to enable flexible partitioning of a macroblock into sub-blocks to achieve better inter prediction. SPLITMV is very useful when objects within a macroblock have different motion characteristics. Within a macroblock coded using SPLITMV mode, each sub-block can have its own motion vector. Similar to the strategy of reusing motion vectors at the macroblock level, a sub-block can also use motion vectors from neighboring sub-blocks above or left to the current block. This strategy is very flexible and can effectively encode any shape of sub-macroblock partitioning, and does so efficiently. Here is an example of a macroblock with 16x16 luma pixels that is partitioned to 16 4x4 blocks :

  
  

  

  
  

  where New represents a 4x4 bock coded with a new motion vector, and Left and Above represent a 4x4 block coded using the motion vector from the left and above, respectively. This example effectively partitions the 16x16 macroblock into 3 different segments with 3 different motion vectors (represented below by 1, 2 and 3) :

  
  

  

  
  

  Through effective use of intra and inter prediction modes, WebM encoder implementations can achieve great compression quality on a wide range of source material. If you want to delve further into VP8 prediction modes, read the VP8 Bitstream Guide or examine the reconintra.c and rdopt.c files in the VP8 source tree.

  
  

  Yaowu Xu, Ph.D. is a codec engineer at Google.

  
  

  

• Inside WebM Technology : VP8 Intra and Inter Prediction

  20 juillet 2010, par noreply@blogger.com (Lou Quillio)
  Continuing our series on WebM technology, I will discuss the use of prediction methods in the VP8 video codec, with special attention to the TM_PRED and SPLITMV modes, which are unique to VP8.

  
  

  First, some background. To encode a video frame, block-based codecs such as VP8 first divide the frame into smaller segments called macroblocks. Within each macroblock, the encoder can predict redundant motion and color information based on previously processed blocks. The redundant data can be subtracted from the block, resulting in more efficient compression.

  
  Image by Fido Factor, licensed under Creative Commons Attribution License.
  Based on a work at www.flickr.com

  
  

  A VP8 encoder uses two classes of prediction :

  • Intra prediction uses data within a single video frame
  • Inter prediction uses data from previously encoded frames

  The residual signal data is then encoded using other techniques, such as transform coding.

  
  

  VP8 Intra Prediction Modes

  VP8 intra prediction modes are used with three types of macroblocks :

  • 4x4 luma
  • 16x16 luma
  • 8x8 chroma

  Four common intra prediction modes are shared by these macroblocks :
  

  • H_PRED (horizontal prediction). Fills each column of the block with a copy of the left column, L.
  • V_PRED (vertical prediction). Fills each row of the block with a copy of the above row, A.
  • DC_PRED (DC prediction). Fills the block with a single value using the average of the pixels in the row above A and the column to the left of L.
  • TM_PRED (TrueMotion prediction). A mode that gets its name from a compression technique developed by On2 Technologies. In addition to the row A and column L, TM_PRED uses the pixel P above and to the left of the block. Horizontal differences between pixels in A (starting from P) are propagated using the pixels from L to start each row.

  For 4x4 luma blocks, there are six additional intra modes similar to V_PRED and H_PRED, but correspond to predicting pixels in different directions. These modes are outside the scope of this post, but if you want to learn more see the VP8 Bitstream Guide.

  
  

  As mentioned above, the TM_PRED mode is unique to VP8. The following figure uses an example 4x4 block of pixels to illustrate how the TM_PRED mode works :

  

  Where C, As and Ls represent reconstructed pixel values from previously coded blocks, and X₀₀ through X₃₃ represent predicted values for the current block. TM_PRED uses the following equation to calculate X_ij :

  
  

  X_ij = L_i + A_j - C (i, j=0, 1, 2, 3)

  
  

  Although the above example uses a 4x4 block, the TM_PRED mode for 8x8 and 16x16 blocks works in the same fashion.

  TM_PRED is one of the more frequently used intra prediction modes in VP8, and for common video sequences it is typically used by 20% to 45% of all blocks that are intra coded. Overall, together with other intra prediction modes, TM_PRED helps VP8 to achieve very good compression efficiency, especially for key frames, which can only use intra modes (key frames by their very nature cannot refer to previously encoded frames).

  
  

  VP8 Inter Prediction Modes

  
  

  In VP8, inter prediction modes are used only on inter frames (non-key frames). For any VP8 inter frame, there are typically three previously coded reference frames that can be used for prediction. A typical inter prediction block is constructed using a motion vector to copy a block from one of the three frames. The motion vector points to the location of a pixel block to be copied. In most video compression schemes, a good portion of the bits are spent on encoding motion vectors ; the portion can be especially large for video encoded at lower datarates.

  
  

  Like previous VPx codecs, VP8 encodes motion vectors very efficiently by reusing vectors from neighboring macroblocks (a macroblock includes one 16x16 luma block and two 8x8 chroma blocks). VP8 uses a similar strategy in the overall design of inter prediction modes. For example, the prediction modes "NEAREST" and "NEAR" make use of last and second-to-last, non-zero motion vectors from neighboring macroblocks. These inter prediction modes can be used in combination with any of the three different reference frames.

  
  

  In addition, VP8 has a very sophisticated, flexible inter prediction mode called SPLITMV. This mode was designed to enable flexible partitioning of a macroblock into sub-blocks to achieve better inter prediction. SPLITMV is very useful when objects within a macroblock have different motion characteristics. Within a macroblock coded using SPLITMV mode, each sub-block can have its own motion vector. Similar to the strategy of reusing motion vectors at the macroblock level, a sub-block can also use motion vectors from neighboring sub-blocks above or left to the current block. This strategy is very flexible and can effectively encode any shape of sub-macroblock partitioning, and does so efficiently. Here is an example of a macroblock with 16x16 luma pixels that is partitioned to 16 4x4 blocks :

  
  

  

  
  

  where New represents a 4x4 bock coded with a new motion vector, and Left and Above represent a 4x4 block coded using the motion vector from the left and above, respectively. This example effectively partitions the 16x16 macroblock into 3 different segments with 3 different motion vectors (represented below by 1, 2 and 3) :

  
  

  

  
  

  Through effective use of intra and inter prediction modes, WebM encoder implementations can achieve great compression quality on a wide range of source material. If you want to delve further into VP8 prediction modes, read the VP8 Bitstream Guide or examine the reconintra.c and rdopt.c files in the VP8 source tree.

  
  

  Yaowu Xu, Ph.D. is a codec engineer at Google.