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• Your 6-step guide to increasing acquisition

  2 juillet 2019, par Matomo Core Team — Analytics Tips
  Your 6-step guide to increasing acquisition

  Want to save time and money, as well as increase conversions and acquisition ? Matomo Analytics is here to help with that !

  Let’s start by helping you create a website visitors’ acquisition strategy, without it you might be going in blind and missing opportunities that might’ve been easily found in your metrics.

  To help you craft a strategy for your site, check out the steps below !

  Step one : Get familiar with the Acquisition feature

  The easiest way is to start with Matomo’s Acquisition feature itself. Discover and take action on the marketing channels with the biggest ROI for your business. You’ll learn :

  How to get traffic from external websites : Find out who’s helping you succeed from external websites and convince them to do more of it. Get more traffic by proactively asking for : paid sponsorships ; guest blog posts ; or spending more advertising on the particular website.

  

  About Social Networks : Which social media channels are connecting with the audience you want ? Take the guesswork out by using only the ones you need. By finding out which social channels your ideal audience prefers, you can generate shareable, convincing and engaging content to drive shares and traffic through to your site.

  Campaigns : This helps you understand which marketing campaign is working and which isn’t. You can then shift your efforts to effectively gain more visitors with less costs. Keep track of every ad and content piece you show across internal and external channels to see which has the biggest impact on your business objectives.

  Enhanced SEO : Every acquisition plan needs a focus on maximising your Search Engine Optimization (SEO) efforts. When it comes to getting conclusive search engine referrer metrics, you need to be sure you’re getting ALL the insights to drive your SEO strategy. See keyword position rankings, integrate Google, Bing and Yahoo search consoles, and no longer be restricted with “keyword not defined” showing up in your keywords reports.

  >> Watch Acquisition introduction video (playtime : 2.54 minutes)

  Step two : Set your goals and monitor conversion funnels

  Let the Goals feature guide you

  Goals are essential for building your marketing strategy and getting new customers. The more goals you track, the more you learn about behavioural changes and modify pathways to impact acquisitions over time. 

  Are you checking :

  • Which channels are converting the best for your business ?
  • Which cities/countries are most popular ?
  • What devices will attract the most visitors ?
  • How engaged your visitors are before converting ?

  This way you can see if your campaigns (SEO, PPC, signups, blogs etc.) or optimising efforts (A/B Testing, Funnels) have made an impact with the time and investment you’ve put in.

  >> Watch Goals introduction video (playtime : 2.04 minutes)

  The Funnels feature leads you to success

  Conversion funnels give you the big picture on whether your acquisition plans are paying off and where they may be falling short. If the ultimate goal of your site is to drive conversions, then each funnel can tell you how effectively you’re driving traffic through to your desired outcome.

  >> Watch Funnels introduction video (playtime : 2.29 minutes)

  

  Step three : Measure the success of every touchpoint in your customer’s journey

  Multi Attribution feature

  Accurately identify channels where visitors first engage with your business, as well as the final channel they came from, before purchasing your product/service. This helps you make smarter decisions when determining acquisition spend to accurately calculate the Customer Acquisition Cost (CAC). Here you no longer falsely over-estimate investment in failing marketing channels.

  >> Watch Multi Attribution introduction video (playtime : 2.28 minutes)

  Step four : For ecommerce sites, understand who your customers are to increase sales

  Ecommerce feature to significantly increase $ potential

  If your website’s overall purpose is to generate revenue, the Ecommerce feature gives you comprehensive insights into your customer’s purchasing behaviours.

  This heavily reduces your risks when marketing products to potential customers as you’ll understand who to target, what to target them with and where further opportunities exist.

  >> Watch Ecommerce introduction video (playtime : 2.04 minutes)

  

  Step five : Make sure the forms on your website are easy to complete

  Form Analytics feature

  Once you get visitors through the funnel, the forms on your website are the final step to conversion and need special attention. If not done right, you could be missing out on converting a large portion of your visitors.

  Thankfully, you can now identify and fix pain points on the forms that are most important to your business’ success.

  >> Watch Form Analytics introduction video (playtime : 2.39 minutes)

  

  Step six : Discover what a customer journey looks like on a user-by-user basis and bring in key acquisition elements to your strategy

  Visitor Profiles tell you each visitors’ history

  The Profile feature summarises every visit, action and purchase made.

  Better understand :

  • Why your visitors viewed your website.
  • Why your returning visitors continue to view your website.
  • What specifically your visitors are looking for and whether they found it on your website.

  The benefit is being able to see how a combination of acquisition channels play a part in a single buyer’s journey.

  >> Watch Visitors introduction video (playtime : 1.46 minutes)

  

  To summarise

  This guide will set you on a path to creating a well-planned acquisition strategy. It’s the key to attracting and capturing the attention of potential visitors/leads, and successfully driving them through a funnel/buyer’s journey on your website.

  Because of Matomo’s reputation as a trusted analytics platform, the features above can be used to assist you in making smarter data-driven decisions. You can pursue different acquisition avenues with confidence and create a strategy that’s agile and ready for success, all while respecting user privacy.

• Anomalie #4364 : MYSQL 5.7 - Erreurs avec les dates à 0

  2 août 2019, par cedric -

  Mais le problème principal c’est qu’on utilise aussi des dates floues de type 2019-06-00 ou meme 2019-00-00 quand le jour ou le mois ne sont pas connus.
  Ce n’est pas accepté non plus par le mode strict de mySQL mais pour le coup c’est bien plus compliqué à gérer pour ne pas perdre la feature
  Chez moi j’ai changé le sql mode par défaut dans le my.ini (ou équivalent mariaDB)

• ffmpeg avcodec_send_packet/avcodec_receive_frame memory leak

  23 janvier 2019, par G Hamlin

  I’m attempting to decode frames, but memory usage grows with every frame (more specifically, with every call to avcodec_send_packet) until finally the code crashes with a bad_alloc. Here’s the basic decode loop :

  int rfret = 0;
  
  while((rfret = av_read_frame(inctx.get(), &packet)) >= 0){
  
      if (packet.stream_index == vstrm_idx) {
  
  
  
          //std::cout << "Sending Packet" << std::endl;
  
          int ret = avcodec_send_packet(ctx.get(), &packet);
  
          if (ret < 0 || ret == AVERROR(EAGAIN) || ret == AVERROR_EOF) {
  
              std::cout << "avcodec_send_packet: " << ret << std::endl;
  
              break;
  
          }
  
  
  
          while (ret  >= 0) {
  
              //std::cout << "Receiving Frame" << std::endl;
  
              ret = avcodec_receive_frame(ctx.get(), fr);
  
              if (ret == AVERROR(EAGAIN) || ret == AVERROR_EOF) {
  
                  //std::cout << "avcodec_receive_frame: " << ret << std::endl;
  
                  av_frame_unref(fr);
  
                  // av_frame_free(&fr);
  
                  break;
  
              }
  
  
  
              std::cout << "frame: " << ctx->frame_number << std::endl;
  
  
  
              // eventually do something with the frame here...
  
  
  
              av_frame_unref(fr);
  
              // av_frame_free(&fr);
  
          }
  
      }
  
      else {
  
          //std::cout << "Not Video" << std::endl;
  
      }
  
      av_packet_unref(&packet);
  
  }

  Memory usage/leakage seems to scale with the resolution of the video I’m decoding. For example, for a 3840x2160 resolution video, the memory usage in windows task manager consistently jumps up by about 8mb (1 byte per pixel ??) for each received frame. Do I need to do something besides call av_frame_unref to release the memory ?

  (more) complete code below

  ---

  void AVFormatContextDeleter(AVFormatContext* ptr)
  
  {
  
      if (ptr) {
  
          avformat_close_input(&ptr);
  
      }
  
  }
  
  
  
  void AVCodecContextDeleter(AVCodecContext* ptr)
  
  {
  
      if (ptr) {
  
          avcodec_free_context(&ptr);
  
      }
  
  }
  
  
  
  typedef std::unique_ptr AVFormatContextPtr;
  
  typedef std::unique_ptr AVCodecContextPtr;
  
  
  
  AVCodecContextPtr createAvCodecContext(AVCodec *vcodec)
  
  {
  
      AVCodecContextPtr ctx(avcodec_alloc_context3(vcodec), AVCodecContextDeleter);
  
      return ctx;
  
  }
  
  
  
  AVFormatContextPtr createFormatContext(const std::string& filename)
  
  {
  
      AVFormatContext* inctxPtr = nullptr;
  
      int ret = avformat_open_input(&inctxPtr, filename.c_str(), nullptr, nullptr);
  
      //    int ret = avformat_open_input(&inctx, "D:/Videos/test.mp4", nullptr, nullptr);
  
      if (ret != 0) {
  
          inctxPtr = nullptr;
  
      }
  
  
  
      return AVFormatContextPtr(inctxPtr, AVFormatContextDeleter);
  
  }
  
  
  
  int testDecode()
  
  {
  
      // open input file context
  
      AVFormatContextPtr inctx = createFormatContext("D:/Videos/Matt Chapman Hi Greg.MOV");
  
  
  
      if (!inctx) {
  
          // std::cerr << "fail to avforamt_open_input(\"" << infile << "\"): ret=" << ret;
  
          return 1;
  
      }
  
  
  
      // retrieve input stream information
  
      int ret = avformat_find_stream_info(inctx.get(), nullptr);
  
      if (ret < 0) {
  
          //std::cerr << "fail to avformat_find_stream_info: ret=" << ret;
  
          return 2;
  
      }
  
  
  
      // find primary video stream
  
      AVCodec* vcodec = nullptr;
  
      const int vstrm_idx = av_find_best_stream(inctx.get(), AVMEDIA_TYPE_VIDEO, -1, -1, &vcodec, 0);
  
      if (vstrm_idx < 0) {
  
          //std::cerr << "fail to av_find_best_stream: vstrm_idx=" << vstrm_idx;
  
          return 3;
  
      }
  
  
  
      AVCodecParameters* origin_par = inctx->streams[vstrm_idx]->codecpar;
  
      if (vcodec == nullptr) {  // is this even necessary?
  
          vcodec = avcodec_find_decoder(origin_par->codec_id);
  
          if (!vcodec) {
  
              // Can't find decoder
  
              return 4;
  
          }
  
      }
  
  
  
      AVCodecContextPtr ctx = createAvCodecContext(vcodec);
  
      if (!ctx) {
  
          return 5;
  
      }
  
  
  
      ret = avcodec_parameters_to_context(ctx.get(), origin_par);
  
      if (ret) {
  
          return 6;
  
      }
  
  
  
      ret = avcodec_open2(ctx.get(), vcodec, nullptr);
  
      if (ret < 0) {
  
          return 7;
  
      }
  
  
  
      //print input video stream informataion
  
      std::cout
  
              //<< "infile: " << infile << "\n"
  
              << "format: " << inctx->iformat->name << "\n"
  
              << "vcodec: " << vcodec->name << "\n"
  
              << "size:   " << origin_par->width << 'x' << origin_par->height << "\n"
  
              << "fps:    " << av_q2d(ctx->framerate) << " [fps]\n"
  
              << "length: " << av_rescale_q(inctx->duration, ctx->time_base, {1,1000}) / 1000. << " [sec]\n"
  
              << "pixfmt: " << av_get_pix_fmt_name(ctx->pix_fmt) << "\n"
  
              << "frame:  " << inctx->streams[vstrm_idx]->nb_frames << "\n"
  
              << std::flush;
  
  
  
  
  
      AVPacket packet;
  
  
  
      av_init_packet(&packet);
  
      packet.data = nullptr;
  
      packet.size = 0;
  
  
  
      AVFrame *fr = av_frame_alloc();
  
      if (!fr) {
  
          return 8;
  
      }
  
  
  
      int rfret = 0;
  
      while((rfret = av_read_frame(inctx.get(), &packet)) >= 0){
  
          if (packet.stream_index == vstrm_idx) {
  
  
  
              //std::cout << "Sending Packet" << std::endl;
  
              int ret = avcodec_send_packet(ctx.get(), &packet);
  
              if (ret < 0 || ret == AVERROR(EAGAIN) || ret == AVERROR_EOF) {
  
                  std::cout << "avcodec_send_packet: " << ret << std::endl;
  
                  break;
  
              }
  
  
  
              while (ret  >= 0) {
  
                  //std::cout << "Receiving Frame" << std::endl;
  
                  ret = avcodec_receive_frame(ctx.get(), fr);
  
                  if (ret == AVERROR(EAGAIN) || ret == AVERROR_EOF) {
  
                      //std::cout << "avcodec_receive_frame: " << ret << std::endl;
  
                      av_frame_unref(fr);
  
                      // av_frame_free(&fr);
  
                      break;
  
                  }
  
  
  
                  std::cout << "frame: " << ctx->frame_number << std::endl;
  
  
  
                  // do something with the frame here...
  
  
  
                  av_frame_unref(fr);
  
                  // av_frame_free(&fr);
  
              }
  
          }
  
          else {
  
              //std::cout << "Not Video" << std::endl;
  
          }
  
          av_packet_unref(&packet);
  
      }
  
  
  
      std::cout << "RFRET = " << rfret << std::endl;
  
  
  
      return 0;
  
  }

  Update 1 : (1/21/2019) Compiling on a different machine and running with different video files I am not seeing the memory usage growing without bound. I’ll try to narrow down where the difference lies (compiler ?, ffmpeg version ?, or video encoding ?)

  Update 2 : (1/21/2019) Ok, it looks like there is some interaction occurring between ffmpeg and Qt’s QCamera. In my application, I’m using Qt to manage the webcam, but decided to use ffmpeg libraries to handle decoding/encoding since Qt doesn’t have as comprehensive support for different codecs. If I have the camera turned on (through Qt), ffmpeg decoding memory consumption grows without bound. If the camera is off, ffmpeg behaves fine. I’ve tried this both with a physical camera (Logitech C920) and with a virtual camera using OBS-Virtualcam, with the same result. So far I’m baffled as to how the two systems are interacting...