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• Why Matomo is a serious alternative to Google Analytics 360

  12 décembre 2018, par Jake Thornton — Marketing
  There’s no doubt about it, the free version of Google Analytics offers great value when it comes to making data-driven decisions for your business. But as your business starts to grow, so does the need for a more powerful web analytics tool.

  Why would I need to use a different web analytics tool ? It’s because Google Analytics (free version) is very limited when it comes to meeting the needs of a fast growing business whose website plays a pivotal role in converting its customers.

  This is where the Google Analytics 360 suite comes in, which is designed to meet the needs of businesses looking to get more accurate and insightful metrics.

  So what’s holding a growing business back from using Google Analytics 360 ?

  While GA360 sounds like a great option when upgrading your web analytics platform, we have found there are three core reasons holding businesses back from taking the leap :

  • Businesses can’t bear to swallow the US$150,000+ price tag (per year !) that comes with upgrading
  • Businesses can’t rely on GA360 to give them all the insights they need
  • Businesses want more control and ownership of their data

  Thankfully there are (only a few) alternatives and as the leading open-source alternative to Google Analytics, we hope to share insights on why Matomo Analytics can be the perfect solution for anyone at this crossroads in their web analytics journey.

  First, what does Google Analytics 360 offer that Google Analytics (free) doesn’t ?

  There’s no doubt about it, the GA360 suite is designed for larger sized businesses with demanding data limits, big budgets to use across the Google Marketing Platform (Google Adwords, DoubleClick etc.) and to get more advanced reporting visualisations and options.
  

  Data Sampling

  Data sampling is the elephant in the room when it comes to comparing GA360 with the freemium version. This is an entire article in its own right but at a basic level, Google Analytics samples your data (makes assumptions based on patterns) once the number of traffic visiting your website reaches a certain limit.

  Google Analytics provides the following information :

  Ad-hoc queries of your data are subject to the following general thresholds for sampling :

  Analytics Standard : 500k sessions at the property level for the date range you are using

  Analytics 360 : 100M sessions at the view level for the date range you are using

  In short, sampled data means inaccurate data. This is why as businesses grow, GA360 becomes a more attractive prospect because there’s no point making data-driven business decisions based on inaccurate data. This is a key weapon Google uses when selling to large businesses, however, this may not seem as concerning if you’re a small business within the sampled data range. For small businesses though, make sure you know the full extent of how this can affect your metrics, for example, your ecommerce data could be sampled, hence your GA reporting not matching your CRM/Ecommerce store data.

  Benefit of using Matomo : There is no data sampling anywhere in Matomo Analytics, that’s why we say 100% Accurate Data reporting across all plans.

  

  Integration with the Google Marketing Platform

  Yes ok, we’ll admit it, GA does a great job at integrating seamlessly with its own products like Google Ads, Google Optimize etc. with a touch of Salesforce integration ; while GA360 takes this to another level compared to it’s freemium version (integration with Google Search 360, Google Display & Video 360 etc.)

  But… what about non-Google advertising platforms ? Well with Google being a dominant leader as a search engine, web browser, email provider, social media channel ; sometimes Google needs to keep its best interests at heart.

  Google is an online advertising giant and a bonus of Google Search 360 is that you can integrate your Bing Ads, Baidu and Yahoo Japan Search campaigns but that’s about it when it comes to integrations from its direct competitors. 

  Benefit of using Matomo : No biased treatment. You can integrate your Google, Yahoo and Bing search consoles for accurate search engine reporting, and in early 2019, Matomo will be releasing a Google Ads, Bing Ads and Facebook Ads Manager integration feature.

  Roll-Up Reporting
  

  Roll-up reporting lets you combine multiple accounts and properties into one view. This is a great benefit when upgrading from GA freemium to GA360. For example, if you’re a digital agency with multiple clients or you manage multiple websites under the one account, the roll-up reporting feature is wonderful when you need to combine data and reporting, instantly.

  Benefit of using Matomo : Matomo’s got this covered ! Roll-up reporting is available in the Matomo Business package (starting at $29 per month) for cloud hosting or you can purchase as a Premium Feature for On-Premise starting at $99 per year.

  Staying in full control of your data

  Who would have thought that one of biggest reasons people choose Matomo isn’t because of anything that leads to a higher ROI, but for the fact that users want more control of their data.
  

  Matomo’s philosophy around data ownership is simple, you own your data, no one else. If you choose to host Matomo Analytics On-Premise then you are in complete control because your data is stored on your own servers where no one can gain access to it in whichever country you choose.

  So what about when you cloud host Matomo ? For users who don’t have the technical knowledge to host Matomo On-Premise, you can still have 100% data ownership and fully respect your user’s privacy when choosing to host Matomo Analytics through our cloud service.

  The difference between cloud hosting Matomo Analytics vs Google Analytics is that when you choose Matomo, we acknowledge you own the data and we have no right to access it. This means we can’t on-sell it to third-parties, we can’t claim ownership of it, you can export your data at anytime (how awesome is that !) and you can migrate between cloud hosting and hosting on-premise for ultimate flexibility whenever you want.

  Matomo also prides itself in allowing its users to be GDPR compliant with ease with a powerful GDPR Manager.

  Businesses can’t rely on Google Analytics 360 to give them all the insights they need

  Unlike Google Analytics 360, Matomo blends its Premium Web Analytics platform with Conversion Optimization features to allow its users to fully evaluate the user-experience on your website.

  Matomo is designed to be a complete analytics platform, meaning you have everything you need all in the one place which gives you greater insights and better business outcomes.

  
  These features include :

  Premium Web Analytics – You can still (accurately) measure all the basic metrics you love and are familiar with in Google Analytics like Location, Referrer traffic, Multi Attribution, Campaign Tracking and Ecommerce etc.

  Conversion Optimization – Eliminate the need for multiple analytics tools to get what Google Analytics doesn’t offer. These features include Heatmaps, Session Recordings, Form Analytics and more – giving you the best chance possible to convert more traffic by evaluating the user-experience.

  By having one tool for all your features you can integrate metrics, have one single view for all your data and it’s easy to use.

  Enhanced SEO – Get more insights into the performance of your search campaigns with unbiased search engine reporting, keyword ranking positions, integration with multiple search consoles and crawling stats. Google Analytics offers limited features to help with your SEO campaigns and only integrates with Google products.

  Visitor Profiles – Get a detailed life-time evaluation of every user who visits your website.

  Tag Manager – A powerful open-source Tag Manager tool to embed your third-party marketing tags. By being open-source and with our commitment to giving you 100% data ownership, you can always ensure you are in full control.

  Full Matomo vs Google Analytics 360 Comparison Table

  Just putting it out there ...

  Google leads the market with its freemium tool which offers great insights for businesses (fyi – Matomo has a forever free analytics tool too !), but when it comes to upgrading to get accurate reporting (kind of a big deal), owning your own data (a huge deal !) and having a complete range of features to excel ROI for your business, Matomo Analytics is often a preferred option to the Google Analytics 360 suite.

  Matomo is designed to be easy to use, is fully flexible and gives users full peace of mind by respecting user privacy. Want to learn more about the benefits of Matomo ?

• Can google cloud dataflow (apache beam) use ffmpeg to process video or image data

  12 février 2016, par Michael

  Can a dataflow process use ffmpeg to process video or images and if so what would a sample workflow look like

• Google Speech - Streaming Request Returns EOF

  9 octobre 2017, par Josh

  Using Go, I’m taking a RTMP stream, transcoding it to FLAC (using ffmpeg) and attempting to stream to Google’s Speech API to transcribe the audio. However, I keep getting EOF errors when sending the data. I can’t find any information on this error in the docs so I’m not exactly sure what’s causing it.

  I’m chunking the received data into 3s clips (length isn’t relevant as long as it’s less than the maximum length of a streaming recognition request).

  Here is the core of my code :

  func main() {
  
  
  
      done := make(chan os.Signal)
  
      received := make(chan []byte)
  
  
  
      go receive(received)
  
      go transcribe(received)
  
  
  
      signal.Notify(done, os.Interrupt, syscall.SIGTERM)
  
  
  
      select {
  
      case <-done:
  
          os.Exit(0)
  
      }
  
  }
  
  
  
  func receive(received chan<- []byte) {
  
      var b bytes.Buffer
  
      stdout := bufio.NewWriter(&b)
  
  
  
      cmd := exec.Command("ffmpeg", "-i", "rtmp://127.0.0.1:1935/live/key", "-f", "flac", "-ar", "16000", "-")
  
      cmd.Stdout = stdout
  
  
  
      if err := cmd.Start(); err != nil {
  
          log.Fatal(err)
  
      }
  
  
  
      duration, _ := time.ParseDuration("3s")
  
      ticker := time.NewTicker(duration)
  
  
  
      for {
  
          select {
  
          case <-ticker.C:
  
              stdout.Flush()
  
              log.Printf("Received %d bytes", b.Len())
  
              received <- b.Bytes()
  
              b.Reset()
  
          }
  
      }
  
  }
  
  
  
  func transcribe(received <-chan []byte) {
  
      ctx := context.TODO()
  
  
  
      client, err := speech.NewClient(ctx)
  
      if err != nil {
  
          log.Fatal(err)
  
      }
  
  
  
      stream, err := client.StreamingRecognize(ctx)
  
      if err != nil {
  
          log.Fatal(err)
  
      }
  
  
  
      // Send the initial configuration message.
  
      if err = stream.Send(&speechpb.StreamingRecognizeRequest{
  
          StreamingRequest: &speechpb.StreamingRecognizeRequest_StreamingConfig{
  
              StreamingConfig: &speechpb.StreamingRecognitionConfig{
  
                  Config: &speechpb.RecognitionConfig{
  
                      Encoding:        speechpb.RecognitionConfig_FLAC,
  
                      LanguageCode:    "en-GB",
  
                      SampleRateHertz: 16000,
  
                  },
  
              },
  
          },
  
      }); err != nil {
  
          log.Fatal(err)
  
      }
  
  
  
      for {
  
          select {
  
          case data := <-received:
  
              if len(data) > 0 {
  
                  log.Printf("Sending %d bytes", len(data))
  
                  if err := stream.Send(&speechpb.StreamingRecognizeRequest{
  
                      StreamingRequest: &speechpb.StreamingRecognizeRequest_AudioContent{
  
                          AudioContent: data,
  
                      },
  
                  }); err != nil {
  
                      log.Printf("Could not send audio: %v", err)
  
                  }
  
              }
  
          }
  
      }
  
  }

  Running this code gives this output :

  2017/10/09 16:05:00 Received 191704 bytes
  
  2017/10/09 16:05:00 Saving 191704 bytes
  
  2017/10/09 16:05:00 Sending 191704 bytes
  
  2017/10/09 16:05:00 Could not send audio: EOF
  
  
  
  2017/10/09 16:05:03 Received 193192 bytes
  
  2017/10/09 16:05:03 Saving 193192 bytes
  
  2017/10/09 16:05:03 Sending 193192 bytes
  
  2017/10/09 16:05:03 Could not send audio: EOF
  
  
  
  2017/10/09 16:05:06 Received 193188 bytes
  
  2017/10/09 16:05:06 Saving 193188 bytes
  
  2017/10/09 16:05:06 Sending 193188 bytes // Notice that this doesn't error
  
  
  
  2017/10/09 16:05:09 Received 191704 bytes
  
  2017/10/09 16:05:09 Saving 191704 bytes
  
  2017/10/09 16:05:09 Sending 191704 bytes
  
  2017/10/09 16:05:09 Could not send audio: EOF

  Notice that not all of the Sends fail.

  Could anyone point me in the right direction here ? Is it something to do with the FLAC headers or something ? I also wonder if maybe resetting the buffer causes some of the data to be dropped (i.e. it’s a non-trivial operation that actually takes some time to complete) and it doesn’t like this missing information ?

  Any help would be really appreciated.