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• A Comprehensive Guide to Robust Digital Marketing Analytics

  15 novembre 2023, par Erin — Analytics Tips

  First impressions are everything. This is not only true for dating and job interviews but also for your digital marketing strategy. Like a poorly planned job application getting tossed in the “no thank you” pile, 38% of visitors to your website will stop engaging with your content if they find the layout unpleasant. Thankfully, digital marketers can access data that can be harnessed to optimise websites and turn those “no thank you’s” into “absolutely’s.”

  So, how can we transform raw data into valuable insights that pay off ? The key is web analytics tools that can help you make sense of it all while collecting data ethically. In this article, we’ll equip you with ways to take your digital marketing strategy to the next level with the power of web analytics.

  What are the different types of digital marketing analytics ?

  Digital marketing analytics are like a cipher into the complex behaviour of your buyers. Digital marketing analytics help collect, analyse and interpret data from any touchpoint you interact with your buyers online. Whether you’re trying to gauge the effectiveness of a new email marketing campaign or improve your mobile app layout, there’s a way for you to make use of the insights you gain.

  

  As we go through the eight commonly known types of digital marketing analytics, please note we’ll primarily focus on what falls under the umbrella of web analytics. 

  1. Web analytics help you better understand how users interact with your website. Good web analytics tools will help you understand user behaviour while securely handling user data. 
  2. Learn more about the effectiveness of your organisation’s social media platforms with social media analytics. Social media analytics include user engagement, post reach and audience demographics. 
  3. Email marketing analytics help you see how email campaigns are being engaged with.
  4. Search engine optimisation (SEO) analytics help you understand your website’s visibility in search engine results pages (SERPs). 
  5. Pay-per-click (PPC) or campaign analytics measure the performance of paid advertising campaigns.
  6. Content marketing analytics focus on how your content is performing with your audience. 
  7. Customer analytics helps organisations identify and examine buyer behaviour to retain the biggest spenders. 
  8. Mobile app analytics track user interactions within mobile applications. 

  Choosing which digital marketing analytics tools are the best fit for your organisation is not an easy task. When making these decisions, it’s critical to remember the ethical implications of data collection. Although data insights can be invaluable to your organisation, they won’t be of much use if you lose the trust of your users. 

  Tips and best practices for developing robust digital marketing analytics 

  So, what separates top-notch, robust digital marketing analytics from the rest ? We’ve already touched on it, but a big part involves respecting user privacy and ethically handling data. Data security should be on your list of priorities, alongside conversion rate optimisation when developing a digital marketing strategy. In this section, we will examine best practices for using digital marketing analytics while retaining user trust.

  

  Clear objectives

  Before comparing digital marketing analytics tools, you should define clear and measurable goals. Try asking yourself what you need your digital marketing analytics strategy to accomplish. Do you want to improve conversion rates while remaining data compliant ? Maybe you’ve noticed users are not engaging with your platform and want to fix that. Save yourself time and energy by focusing on the most relevant pain points and areas of improvement.

  Choose the right tools for the job

  Don’t just base your decision on what other people tell you. Take the tool for a test drive — free trials allow you to test features and user interfaces and learn more about the platform before committing. When choosing digital marketing analytics tools, look for ones that ensure data accuracy as well as compliance with privacy laws like GDPR.

  Don’t overlook data compliance

  GDPR ensures organisations prioritise data protection and privacy. You could be fined up to €20 million, or 4% of the previous year’s revenue for violations. Without data compliance practices, you can say goodbye to the time and money spent on digital marketing strategies. 

  Don’t sacrifice data quality and accuracy

  Inaccurate and low-quality data can taint your analysis, making it hard to glean valuable insights from your digital marketing analytics efforts. Many analytics tools only show sampled data or use AI and ML to fill data gaps, potentially compromising the accuracy and completeness of your analytics. 

  When your analytics are based on incomplete or inaccurate data, it’s like trying to assemble a puzzle with missing pieces—you might get a glimpse of the whole picture, but it’s never quite clear. Accurate data isn’t just helpful—it’s the backbone of smart marketing strategies. It lets you make confident decisions and enables precise targeting for greater impact.

  Communicate your findings

  Having insights is one thing ; effectively communicating complex data findings is just as important. Customise dashboards to display key metrics aligned with your objectives. Make sure to automate reports, allowing stakeholders to stay updated without manual intervention. 

  Understand the user journey

  To optimise your conversion rates, you need to understand the user journey. Start by analysing visitors interactions with your website — this will help you identify conversion bottlenecks in your sales or lead generation processes. Implement A/B testing for landing page optimisation, refining elements like call-to-action buttons or copy, and leverage Form Analytics to make informed, data-driven improvements to your forms.

  Continuous improvement

  Learn from the data insights you gain, and iterate your marketing strategies based on the findings. Stay updated with evolving web analytics trends and technologies to leverage new growth opportunities. 

  Why you need web analytics to support your digital marketing analytics toolbox

  You wouldn’t set out on a roadtrip without a map, right ? Digital marketing analytics without insights into how users interact with your website are just as useless. Used ethically, web analytics tools can be an invaluable addition to your digital marketing analytics toolbox. 

  The data collected via web analytics reveals user interactions with your website. These could include anything from how long visitors stay on your page to their actions while browsing your website. Web analytics tools help you gather and understand this data so you can better understand buyer preferences. It’s like a domino effect : the more you understand your buyers and user behaviour, the better you can assess the effectiveness of your digital content and campaigns. 

  Web analytics reveal user behaviour, highlighting navigation patterns and drop-off points. Understanding these patterns helps you refine website layout and content, improving engagement and conversions for a seamless user experience.

  

  Concrete CMS harnessed the power of web analytics, specifically Matomo’s Form Analytics, to uncover crucial insights within their user onboarding process. Their data revealed a significant issue : the “address” input field was causing visitors to drop off and not complete the form, severely impacting the overall onboarding experience and conversion rate.

  Armed with these insights, Concrete CMS made targeted optimisations to the form, resulting in a substantial transformation. By addressing the specific issue identified through Form Analytics, they achieved an impressive outcome – a threefold increase in lead generation.

  This case is a great example of how web analytics can uncover customer needs and preferences and positively impact conversion rates. 

  Ethical implications of digital marketing analytics

  As we’ve touched on, digital marketing analytics are a powerful tool to help better understand online user behaviour. With great power comes great responsibility, however, and it’s a legal and ethical obligation for organisations to protect individual privacy rights. Let’s get into the benefits of practising ethical digital marketing analytics and the potential risks of not respecting user privacy : 

  • If someone uses your digital platform and then opens their email one day to find it filled with random targeted ad campaigns, they won’t be happy. Avoid losing user trust — and facing a potential lawsuit — by informing users what their data will be used for. Give them the option to consent to opt-in or opt-out of letting you use their personal information. If users are also assured you’ll safeguard personal information against unauthorised access, they’ll be more likely to trust you to handle their data securely.
  • Protecting data against breaches means investing in technology that will let you end-to-end encrypt and securely store data. Other important data-security best practices include access control, backing up data regularly and network and physical security of assets.

  A fine line separates digital marketing analytics and misusing user data — many companies have gotten into big trouble for crossing it. (By big trouble, we mean millions of dollars in fines.) When it comes to digital marketing analytics, you should never cut corners when it comes to user privacy and data security. This balance involves understanding what data can be collected and what should be collected and respecting user boundaries and preferences.

  

  Learn more 

  We discussed a lot of facets of digital marketing analytics, namely how to develop a robust digital marketing strategy while prioritising data compliance. With Matomo, you can protect user data and respect user privacy while gaining invaluable insights into user behaviour with 100% accurate data. Save your organisation time and money by investing in a web analytics solution that gives you the best of both worlds. 

  If you’re ready to begin using ethical and robust digital marketing analytics on your website, try Matomo. Start your 21-day free trial now — no credit card required.

• issue after video rotation how fix

  2 avril 2015, par Vahagn

  I have next code for rotate video

  OpenCVFrameConverter.ToIplImage converter2 = new OpenCVFrameConverter.ToIplImage() ;

  for (int i = firstIndex; i <= lastIndex; i++) {
  
      long t = timestamps[i % timestamps.length] - startTime;
  
      if (t >= 0) {
  
          if (t > recorder.getTimestamp()) {
  
              recorder.setTimestamp(t);
  
          }
  
          Frame g = converter2.convert(rotate(converter2.convertToIplImage(images[i % images.length]),9 0));
  
      recorder.record(g);
  
      }
  
  }

  images[i] - Frame in JavaCV
  after in video have green lines

  

  UPDATE
  Convertation function

  /*
  
   * Copyright (C) 2015 Samuel Audet
  
   *
  
   * This file is part of JavaCV.
  
   *
  
   * JavaCV is free software: you can redistribute it and/or modify
  
   * it under the terms of the GNU General Public License as published by
  
   * the Free Software Foundation, either version 2 of the License, or
  
   * (at your option) any later version (subject to the "Classpath" exception
  
   * as provided in the LICENSE.txt file that accompanied this code).
  
   *
  
   * JavaCV is distributed in the hope that it will be useful,
  
   * but WITHOUT ANY WARRANTY; without even the implied warranty of
  
   * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  
   * GNU General Public License for more details.
  
   *
  
   * You should have received a copy of the GNU General Public License
  
   * along with JavaCV.  If not, see /www.gnu.org/licenses/>.
  
   */
  
  
  
  package com.example.vvardanyan.ffmpeg;
  
  
  
  import org.bytedeco.javacpp.BytePointer;
  
  import org.bytedeco.javacpp.Pointer;
  
  
  
  import java.nio.Buffer;
  
  
  
  import static org.bytedeco.javacpp.opencv_core.CV_16S;
  
  import static org.bytedeco.javacpp.opencv_core.CV_16U;
  
  import static org.bytedeco.javacpp.opencv_core.CV_32F;
  
  import static org.bytedeco.javacpp.opencv_core.CV_32S;
  
  import static org.bytedeco.javacpp.opencv_core.CV_64F;
  
  import static org.bytedeco.javacpp.opencv_core.CV_8S;
  
  import static org.bytedeco.javacpp.opencv_core.CV_8U;
  
  import static org.bytedeco.javacpp.opencv_core.CV_MAKETYPE;
  
  import static org.bytedeco.javacpp.opencv_core.IPL_DEPTH_16S;
  
  import static org.bytedeco.javacpp.opencv_core.IPL_DEPTH_16U;
  
  import static org.bytedeco.javacpp.opencv_core.IPL_DEPTH_32F;
  
  import static org.bytedeco.javacpp.opencv_core.IPL_DEPTH_32S;
  
  import static org.bytedeco.javacpp.opencv_core.IPL_DEPTH_64F;
  
  import static org.bytedeco.javacpp.opencv_core.IPL_DEPTH_8S;
  
  import static org.bytedeco.javacpp.opencv_core.IPL_DEPTH_8U;
  
  import static org.bytedeco.javacpp.opencv_core.IplImage;
  
  import static org.bytedeco.javacpp.opencv_core.Mat;
  
  
  
  /**
  
   * A utility class to map data between {@link Frame} and {@link IplImage} or {@link Mat}.
  
   * Since this is an abstract class, one must choose between two concrete classes:
  
   * {@link ToIplImage} or {@link ToMat}.
  
   *
  
   * @author Samuel Audet
  
   */
  
  public abstract class OpenCVFrameConverter<f> extends FrameConverter<f> {
  
      IplImage img;
  
      Mat mat;
  
  
  
      public static class ToIplImage extends OpenCVFrameConverter<iplimage> {
  
          @Override public IplImage convert(Frame frame) { return convertToIplImage(frame); }
  
      }
  
  
  
      public static class ToMat extends OpenCVFrameConverter<mat> {
  
          @Override public Mat convert(Frame frame) { return convertToMat(frame); }
  
      }
  
  
  
      public static int getFrameDepth(int depth) {
  
          switch (depth) {
  
              case IPL_DEPTH_8U:  case CV_8U:  return Frame.DEPTH_UBYTE;
  
              case IPL_DEPTH_8S:  case CV_8S:  return Frame.DEPTH_BYTE;
  
              case IPL_DEPTH_16U: case CV_16U: return Frame.DEPTH_USHORT;
  
              case IPL_DEPTH_16S: case CV_16S: return Frame.DEPTH_SHORT;
  
              case IPL_DEPTH_32F: case CV_32F: return Frame.DEPTH_FLOAT;
  
              case IPL_DEPTH_32S: case CV_32S: return Frame.DEPTH_INT;
  
              case IPL_DEPTH_64F: case CV_64F: return Frame.DEPTH_DOUBLE;
  
              default: return -1;
  
          }
  
      }
  
  
  
      public static int getIplImageDepth(Frame frame) {
  
          switch (frame.imageDepth) {
  
              case Frame.DEPTH_UBYTE:  return IPL_DEPTH_8U;
  
              case Frame.DEPTH_BYTE:   return IPL_DEPTH_8S;
  
              case Frame.DEPTH_USHORT: return IPL_DEPTH_16U;
  
              case Frame.DEPTH_SHORT:  return IPL_DEPTH_16S;
  
              case Frame.DEPTH_FLOAT:  return IPL_DEPTH_32F;
  
              case Frame.DEPTH_INT:    return IPL_DEPTH_32S;
  
              case Frame.DEPTH_DOUBLE: return IPL_DEPTH_64F;
  
              default:  return -1;
  
          }
  
      }
  
      static boolean isEqual(Frame frame, IplImage img) {
  
          return img != null &amp;&amp; frame != null &amp;&amp; frame.image != null &amp;&amp; frame.image.length > 0
  
                  &amp;&amp; frame.imageWidth == img.width() &amp;&amp; frame.imageHeight == img.height()
  
                  &amp;&amp; frame.imageChannels == img.nChannels() &amp;&amp; getIplImageDepth(frame) == img.depth()
  
                  &amp;&amp; new Pointer(frame.image[0]).address() == img.imageData().address()
  
                  &amp;&amp; frame.imageStride * Math.abs(frame.imageDepth) / 8 == img.widthStep();
  
      }
  
      public IplImage convertToIplImage(Frame frame) {
  
          if (frame == null) {
  
              return null;
  
          } else if (frame.opaque instanceof IplImage) {
  
              return (IplImage)frame.opaque;
  
          } else if (!isEqual(frame, img)) {
  
              int depth = getIplImageDepth(frame);
  
              img = depth &lt; 0 ? null : IplImage.createHeader(frame.imageWidth, frame.imageHeight, depth, frame.imageChannels)
  
                      .imageData(new BytePointer(new Pointer(frame.image[0].position(0)))).widthStep(frame.imageStride * Math.abs(frame.imageDepth) / 8);
  
          }
  
          return img;
  
      }
  
      public Frame convert(IplImage img) {
  
          if (img == null) {
  
              return null;
  
          } else if (!isEqual(frame, img)) {
  
              frame = new Frame();
  
              frame.imageWidth = img.width();
  
              frame.imageHeight = img.height();
  
              frame.imageDepth = getFrameDepth(img.depth());
  
              frame.imageChannels = img.nChannels();
  
              frame.imageStride = img.widthStep() * 8 / Math.abs(frame.imageDepth);
  
              frame.image = new Buffer[] { img.createBuffer() };
  
              frame.opaque = img;
  
          }
  
          return frame;
  
      }
  
  
  
      public static int getMatDepth(Frame frame) {
  
          switch (frame.imageDepth) {
  
              case Frame.DEPTH_UBYTE:  return CV_8U;
  
              case Frame.DEPTH_BYTE:   return CV_8S;
  
              case Frame.DEPTH_USHORT: return CV_16U;
  
              case Frame.DEPTH_SHORT:  return CV_16S;
  
              case Frame.DEPTH_FLOAT:  return CV_32F;
  
              case Frame.DEPTH_INT:    return CV_32S;
  
              case Frame.DEPTH_DOUBLE: return CV_64F;
  
              default:  return -1;
  
          }
  
      }
  
      static boolean isEqual(Frame frame, Mat mat) {
  
          return mat != null &amp;&amp; frame != null &amp;&amp; frame.image != null &amp;&amp; frame.image.length > 0
  
                  &amp;&amp; frame.imageWidth == mat.cols() &amp;&amp; frame.imageHeight == mat.rows()
  
                  &amp;&amp; frame.imageChannels == mat.channels() &amp;&amp; getMatDepth(frame) == mat.depth()
  
                  &amp;&amp; new Pointer(frame.image[0]).address() == mat.data().address()
  
                  &amp;&amp; frame.imageStride * Math.abs(frame.imageDepth) / 8 == (int)mat.step();
  
      }
  
      public Mat convertToMat(Frame frame) {
  
          if (frame == null) {
  
              return null;
  
          } else if (frame.opaque instanceof Mat) {
  
              return (Mat)frame.opaque;
  
          } else if (!isEqual(frame, mat)) {
  
              int depth = getMatDepth(frame);
  
              mat = depth &lt; 0 ? null : new Mat(frame.imageHeight, frame.imageWidth, CV_MAKETYPE(depth, frame.imageChannels),
  
                      new Pointer(frame.image[0].position(0)), frame.imageStride * Math.abs(frame.imageDepth) / 8);
  
          }
  
          return mat;
  
      }
  
      public Frame convert(Mat mat) {
  
          if (mat == null) {
  
              return null;
  
          } else if (!isEqual(frame, mat)) {
  
              frame = new Frame();
  
              frame.imageWidth = mat.cols();
  
              frame.imageHeight = mat.rows();
  
              frame.imageDepth = getFrameDepth(mat.depth());
  
              frame.imageChannels = mat.channels();
  
              frame.imageStride = (int)mat.step() * 8 / Math.abs(frame.imageDepth);
  
              frame.image = new Buffer[] { mat.createBuffer() };
  
              frame.opaque = mat;
  
          }
  
          return frame;
  
      }
  
  }
  
  </mat></iplimage></f></f>

• FFmpeg transcoding video H.264 -> AV1 leads to distorted image

  21 juin 2023, par user1584149

  I'm reading video from stdin via pipe similar to this one Python gets stuck at pipe.stdin.write(image.tostring())

  


  FFmpeg is using libsvtav1 codec with options according to documentation

  


  ffmpeg -y -f rawvideo -i pipe:0 -s {frame_width}x{frame_height} -r {frame_rate} -c:a copy -c:v libsvtav1 -preset 6 -crf 30 -svtav1-params "color-format=1:film-grain-denoise=0:mbr=2M" {output_file} 


  


  Here's couple of details about used FFmpeg version as well as input video

  


  ffmpeg version n5.1.3-14-ge5b5dd6653-20230621 Copyright (c) 2000-2022 the FFmpeg developers
  built with gcc 13.1.0 (crosstool-NG 1.25.0.196_227d99d)
  configuration: --prefix=/ffbuild/prefix --pkg-config-flags=--static --pkg-config=pkg-config --cross-prefix=x86_64-ffbuild-linux-gnu- --arch=x86_64 --target-os=linux --enable-gpl --enable-version3 --disable-debug --enable-iconv --enable-libxml2 --enable-zlib --enable-libfreetype --enable-libfribidi --enable-gmp --enable-openssl --enable-lzma --enable-fontconfig --enable-libvorbis --enable-opencl --enable-libpulse --enable-libvmaf --enable-libxcb --enable-xlib --enable-amf --enable-libaom --enable-libaribb24 --enable-avisynth --disable-chromaprint --enable-libdav1d --enable-libdavs2 --disable-libfdk-aac --enable-ffnvcodec --enable-cuda-llvm --enable-frei0r --enable-libgme --enable-libkvazaar --enable-libass --enable-libbluray --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librist --enable-libssh --enable-libtheora --enable-libvpx --enable-libwebp --enable-lv2 --disable-openal --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenh264 --enable-libopenjpeg --enable-libopenmpt --enable-librav1e --enable-librubberband --disable-schannel --enable-sdl2 --enable-libsoxr --enable-libsrt --enable-libsvtav1 --enable-libtwolame --enable-libuavs3d --enable-libdrm --enable-vaapi --enable-libvidstab --enable-vulkan --enable-libshaderc --disable-libplacebo --enable-libx264 --enable-libx265 --enable-libxavs2 --enable-libxvid --enable-libzimg --enable-libzvbi --extra-cflags=-DLIBTWOLAME_STATIC --extra-cxxflags= --extra-ldflags=-pthread --extra-ldexeflags=-pie --extra-libs='-ldl -lgomp' --extra-version=20230621
  libavutil      57. 28.100 / 57. 28.100
  libavcodec     59. 37.100 / 59. 37.100
  libavformat    59. 27.100 / 59. 27.100
  libavdevice    59.  7.100 / 59.  7.100
  libavfilter     8. 44.100 /  8. 44.100
  libswscale      6.  7.100 /  6.  7.100
  libswresample   4.  7.100 /  4.  7.100
  libpostproc    56.  6.100 / 56.  6.100
Input #0, rawvideo, from 'pipe:0':
  Duration: N/A, start: 0.000000, bitrate: 331776 kb/s
  Stream #0:0: Video: rawvideo (I420 / 0x30323449), yuv420p, 1280x720, 331776 kb/s, 30 tbr, 30 tbn
Stream mapping:
  Stream #0:0 -> #0:0 (rawvideo (native) -> av1 (libsvtav1))
Svt[info]: -------------------------------------------
Svt[info]: SVT [version]:   SVT-AV1 Encoder Lib v1.5.0-12-g0f8b3a81
Svt[info]: SVT [build]  :   GCC 13.1.0   64 bit
Svt[info]: LIB Build date: Jun 20 2023 23:48:14
Svt[info]: -------------------------------------------


  


  The output video transcoded by SVT-AV1 codec is blemished as you can see on the images below. Normally I would say it could be caused by wrong pixel format, but input stream has yuv420 format what is the same as encoder's pixel format parameter —color-format.

  


  Please share your experience or ideas how to get it transcoding correctly.

  


  Thanks in advance.