Sur d’autres sites (8930)

• Date and segment comparison feature

  31 octobre 2019, par Matomo Core Team — Analytics Tips, Development

  Get a clearer picture with the date and segment comparison feature

  What can you do with it ? What are the benefits ?

  Make informed decisions faster by easily comparing different segments and dates with each other.

  Compare report data for multiple segments next to each other

  

  Directly compare the behaviour of visitors from different segments e.g. customers with accounts vs. customers without accounts. Segment comparisons are a powerful way to compare different audience ; learn which ones perform better ; and in what way their actions differ. 

  Compare report data for two time periods next to each other

  

  See how your website performs compared to the previous month/week/year. Including seeing trends over those periods. Say, your business always picks up at the same times within a year, or there’s a sag in business for every user segment over this year and the last except one.

  By being able to compare date ranges you are able to get a quick overview of trends and period to period performance. Has a campaign worked better in September than in October ? Get an instant look by having the side-by-side comparison in Matomo.

  What is it capable of ?

  It lets you ask the question, “What is different ?”

  If you look at reports you’ll only see how people behave overall and if you look at specific segments you’ll see how they behave at face value, however, if you compare data together you’ll be quickly informed on what makes them unique. This data is still there when you don’t use the comparison feature, it’s just buried. Comparing data highlights discrepancies and leads to important questions and answers.

  For example, perhaps some class of users have very low engagement on a specific day compared to the rest of your visitors, and perhaps those users are responsible for an outsized proportion of churn. 

  Who could benefit from it, and why ?

  Everyone can benefit from using it (and probably should use it). It’s yours to experiment with ! You shouldn’t feel restricted to only comparing between the current and last period, or having questions before you start comparing. Follow your instincts and see what pops out when data from different segments is laid out next to each other.

  Where can you find it in Matomo ?

  • Segment comparison is activated by the new icon in the segment selector

  

  • Date comparison can be found in the calendar section of Matomo

  

  • The list of active comparisons is visible at the top of the page for all pages that support comparison
  • Comparisons are visible in every report that supports comparing data, and reports that do not support it will display a message saying so

  How do you use it ?

  • To compare segments, click the icon in the segment selector
  • To compare periods, click the ‘compare’ checkbox in the period selector, then select what period you want to compare it against in the dropdown (previous period, previous year, or a custom range)
  • When comparisons are active, view your reports as normal

  Take it away !

  The comparison feature is a new tool from Matomo 3.12.0 that highlights discrepancies and differences in data that can lead to more clarity and understanding, so we’d encourage everyone to use it. 

  Try it out today in your Matomo and see the power behind this new data comparison mode !

• On-premise analytics demand grows as Google Analytics GDPR uncertainties continue

  7 janvier 2020, par Jake Thornton — Privacy

  The Google Analytics GDPR relationship is a complicated one. Website owners in states like Berlin in Germany are now required to ask users for consent to collect their data. This doesn’t make for the friendliest user-experience and often the website visitor will simply click “no.”

  The problem Google Analytics now presents website owners in the EU is with more visitors clicking “no”, the less accurate your data will become.

  Why do you need to ask your visitors for consent ?

  At this stage it’s simply because Google Analytics collects data for its own purposes. An example of this is using your visitor’s personal data for retargeting purposes across their advertising platforms like Google Ads and YouTube. 

  Google’s Privacy & Terms states : “when you visit a website that uses advertising services like AdSense, including analytics tools like Google Analytics, or embeds video content from YouTube, your web browser automatically sends certain information to Google. This includes the URL of the page you’re visiting and your IP address. We may also set cookies on your browser or read cookies that are already there. Apps that use Google advertising services also share information with Google, such as the name of the app and a unique identifier for advertising.”

  

  The rise of hosting web analytics on-premise

  Managing Google Analytics and GDPR can quickly become complicated, so there’s been an increase in website owners switching from cloud-hosted web analytics platforms, like Google Analytics, to more GDPR compliant alternatives, where you can host web analytics software on your own servers. This is called hosting web analytics on-premise.

  Hosting web analytics on your own servers means :

  No third-parties are involved

  The visitor data your website collects is stored on your own internal infrastructure. This means no third-parties are involved and there’s no risk of personal data being used in the way Google Analytics uses it e.g. sending personal data to its advertising platforms. 

  When you sign up with Google Analytics you sign away control of your user’s personal data. With on-premise website analytics, you own your data and are in full control.

  NOTE : Though Google Analytics uses personal data for its own purposes, not all cloud hosted web analytics platforms do this. As an example, Matomo Analytics Cloud hosted solution states that all personal data collected is not used for its own purposes and that Matomo has no rights in accessing or using this personal data. 

  

  You control where in the world your personal data is stored

  Google Analytics servers are based out of USA, Europe and Asia, so where your personal data will end up is uncertain and you don’t have the option to choose which location it goes to when using free Google Analytics.

  Different countries have different laws when it comes to accessing personal data. When you choose to host your web analytics on-premise, you can choose the location of your servers and where the personal data is stored.

  More flexibility

  With self-hosted web analytics platforms like Matomo On-Premise, you can extend the platform to do anything you want without the restrictions that cloud hosted platforms impose.

  You can :

  • Get full access to the source code of open-source solutions, like Matomo
  • Extend the platform however you want for your business
  • Get access to APIs
  • Have no data limitations or restrictions
  • Get RAW data access
  • Have control over security

  >> Read more about on-premise flexibility for web analytics here

  

  So what does the future look like for Google Analytics and GDPR ?

  It’s difficult to assess this right now. How exactly GDPR is enforced is still quite unclear. 

  What is clear however, is now website owners in Berlin using Google Analytics are lawfully required to ask their visitors for consent to collect personal data. It has been reported that Google Analytics has already received 200,000 complaints in Germany alone and it appears this trend is likely to continue across much of the EU.

  When using Google Analytics in the EU you must also ensure your privacy policy is updated so website visitors are aware that data is being collected through Google Analytics for its own purposes.

  Moving to a web analytics on-premise platform

  Matomo Analytics is the #1 open-source web analytics platform in the world and has been rated as an exceptional alternative to Google Analytics. Check the reviews on Capterra.

  Choosing Matomo On-Premise means you can control exactly where your data is stored, you have full flexibility to customise the platform to do what you want and it’s FREE.

  Matomo’s mission is to give control back to website owners and the team has designed the platform so that moving away from Google Analytics is seamless. Matomo offers most of your favourite Google Analytics features, a leaner interface to navigate, and the option to add free and paid premium features that Google Analytics can’t even offer you.

  And now you can import your historical Google Analytics data directly into your Matomo with the Google Analytics Importer plugin.

  DOWNLOAD MATOMO (FREE)

  And if you can’t host web analytics on your own servers ...

  Hosting web analytics on-premise is not an option for all businesses as you do need the internal infrastructure and technical knowledge to host your own platform.

  If you can’t self-host, then Matomo has a Cloud hosted solution you can easily install and operate like Google Analytics, which is hosted on Matomo’s servers in the EU. 

  The GDPR advantages of choosing Matomo Cloud over Google Analytics are :

  • Servers are secure and based in the EU (strict laws forbid outside access)
  • 100% data ownership – we never use data for our own purposes
  • You can export your data anytime and switch to Matomo On-Premise whenever you like
  • User-privacy protection
  • Advanced GDPR Manager and data anonymisation features which GA doesn’t offer

  

  Interested to learn more ?

  If you are wanting to learn more about why users are making the move from Google Analytics to Matomo, check out our Matomo Analytics vs Google Analytics comparison page.

  >> Matomo Analytics vs Google Analytics

• Error installing package in anaconda : Attempted to make prefix record for unknown package type

  25 janvier 2020, par ashwinids

  I’m getting the error below for doing any operation install, update or uninstall

  ERROR conda.core.link:_execute(700) : An error occurred while
  uninstalling package ’::ffmpeg-3.2.4-2’. Rolling back
  transaction : done

  ValueError(’Attempted to make prefix record for unknown package type :
  ffmpeg-3.2.4-2’,)

  Details about the environment :
  OS : ubuntu 18.04
  python version : intelpython3

  Conda info

       active environment : base
  
      active env location : /home/p****/intelpython3
  
              shell level : 1
  
         user config file : /home/p****/.condarc
  
   populated config files : /home/p****/.condarc
  
            conda version : 4.7.12
  
      conda-build version : not installed
  
           python version : 3.6.8.final.0
  
         virtual packages : __cuda=10.1
  
         base environment : /home/p****/intelpython3  (writable)
  
             channel URLs : https://conda.anaconda.org/intel/linux-64
  
                            https://conda.anaconda.org/intel/noarch
  
                            https://repo.anaconda.com/pkgs/main/linux-64
  
                            https://repo.anaconda.com/pkgs/main/noarch
  
                            https://repo.anaconda.com/pkgs/r/linux-64
  
                            https://repo.anaconda.com/pkgs/r/noarch
  
            package cache : /home/p****/intelpython3/pkgs
  
                            /home/p****/.conda/pkgs
  
         envs directories : /home/p****/intelpython3/envs
  
                            /home/p****/.conda/envs
  
                 platform : linux-64
  
               user-agent : conda/4.7.12 requests/2.20.1 CPython/3.6.8 Linux/5.0.0-36-generic ubuntu/18.04.3 glibc/2.27
  
                  UID:GID : 1000:1000
  
               netrc file : None
  
             offline mode : False

  Conda list

  # packages in environment at /home/p****/intelpython3:
  
  #
  
  # Name                    Version                   Build  Channel
  
  _tflow_select             2.1.0                       gpu    anaconda
  
  absl-py                   0.8.0                    py36_0    anaconda
  
  affine                    2.3.0                    pypi_0    pypi
  
  asn1crypto                0.24.0                   py36_3    intel
  
  astor                     0.8.0                    py36_0    anaconda
  
  atomicwrites              1.3.0                    pypi_0    pypi
  
  attrs                     19.3.0                   pypi_0    pypi
  
  audioread                 2.1.6                    py36_0    <unknown>
  
  awscli                    1.16.292                 pypi_0    pypi
  
  backcall                  0.1.0                    py36_2    <unknown>
  
  backports                 1.0                      py36_9    <unknown>
  
  bayesian-optimization     1.0.1                    pypi_0    pypi
  
  bleach                    2.1.3                    py36_2    <unknown>
  
  boto3                     1.10.19                  pypi_0    pypi
  
  botocore                  1.13.28                  pypi_0    pypi
  
  bzip2                     1.0.6                        17    intel
  
  c-ares                    1.15.0            h7b6447c_1001    anaconda
  
  causalgraphicalmodels     0.0.4                    pypi_0    pypi
  
  certifi                   2018.1.18                py36_2    intel
  
  cffi                      1.11.5                   py36_3    intel
  
  chardet                   3.0.4                    py36_3    intel
  
  click                     7.0                      pypi_0    pypi
  
  click-plugins             1.1.1                    pypi_0    pypi
  
  cligj                     0.5.0                    pypi_0    pypi
  
  colorama                  0.4.1                    pypi_0    pypi
  
  conda                     4.7.12                   py36_0  
  
  conda-env                 2.6.0                         1  
  
  conda-package-handling    1.6.0            py36h7b6447c_0    anaconda
  
  cryptography              2.3                      py36_1    intel
  
  cudatoolkit               10.1.243             h6bb024c_0  
  
  cudnn                     7.6.0                cuda10.1_0    anaconda
  
  cupti                     10.1.168                      0    anaconda
  
  cvxopt                    1.2.3                    pypi_0    pypi
  
  cycler                    0.10.0                   py36_7    intel
  
  cython                    0.29.6           py36h7b7c402_0    intel
  
  daal                      2019.4                intel_243    <unknown>
  
  daal4py                   2019.4           py36h7b7c402_0    intel
  
  dbus                      1.13.12              h746ee38_0  
  
  decorator                 4.3.0                    py36_3    <unknown>
  
  descartes                 1.1.0                    pypi_0    pypi
  
  docutils                  0.15.2                   pypi_0    pypi
  
  dowhy                     0.1.1                    pypi_0    pypi
  
  entrypoints               0.2.3                    py36_2    <unknown>
  
  expat                     2.2.6                he6710b0_0  
  
  ffmpeg                    3.2.4                         2    <unknown>
  
  fiona                     1.8.11                   pypi_0    pypi
  
  fontconfig                2.12.6               h49f89f6_0  
  
  freetype                  2.8                  hab7d2ae_1  
  
  funcsigs                  1.0.2                    py36_7    intel
  
  gast                      0.3.2                      py_0    anaconda
  
  geopandas                 0.6.2                    pypi_0    pypi
  
  get_terminal_size         1.0.0                    py36_7    <unknown>
  
  glib                      2.63.1               h5a9c865_0  
  
  google-pasta              0.1.7                      py_0    anaconda
  
  grpcio                    1.14.1           py36h9ba97e2_0    anaconda
  
  gst-plugins-base          1.12.4               h33fb286_0  
  
  gstreamer                 1.12.4               hb53b477_0  
  
  h5py                      2.9.0            py36h7918eee_0    anaconda
  
  hdf5                      1.10.4               hb1b8bf9_0    anaconda
  
  html5lib                  1.0.1                    py36_4    <unknown>
  
  icc_rt                    2019.4                intel_243    <unknown>
  
  icu                       58.2                 h9c2bf20_1  
  
  idna                      2.6                      py36_3    intel
  
  imageio                   2.6.1                    pypi_0    pypi
  
  imgaug                    0.2.6                    pypi_0    pypi
  
  impi_rt                   2019.4                intel_243    <unknown>
  
  importlib-metadata        0.23                     pypi_0    pypi
  
  intel-openmp              2019.4                intel_243    <unknown>
  
  intelpython               2019.4                        0    intel
  
  ipp                       2019.4                intel_243    <unknown>
  
  ipykernel                 4.6.1                    py36_2    <unknown>
  
  ipython                   6.3.1                    py36_3    <unknown>
  
  ipython_genutils          0.2.0                    py36_2    <unknown>
  
  jedi                      0.12.0                   py36_2    <unknown>
  
  jinja2                    2.10.3                   pypi_0    pypi
  
  jmespath                  0.9.4                    pypi_0    pypi
  
  joblib                    0.13.2                   pypi_0    pypi
  
  jpeg                      9b                   h024ee3a_2  
  
  json5                     0.8.5                    pypi_0    pypi
  
  jsonschema                3.2.0                    pypi_0    pypi
  
  jupyter                   1.0.0                    py36_7    intel
  
  jupyter_client            5.1.0                    py36_5    <unknown>
  
  jupyter_console           5.1.0                    py36_2    <unknown>
  
  jupyter_core              4.4.0                    py36_6    <unknown>
  
  jupyterlab                1.2.3                    pypi_0    pypi
  
  jupyterlab-server         1.0.6                    pypi_0    pypi
  
  keras                     2.3.1                    pypi_0    pypi
  
  keras-applications        1.0.8                      py_0    anaconda
  
  keras-bert                0.80.0                   pypi_0    pypi
  
  keras-embed-sim           0.7.0                    pypi_0    pypi
  
  keras-layer-normalization 0.14.0                   pypi_0    pypi
  
  keras-multi-head          0.22.0                   pypi_0    pypi
  
  keras-pos-embd            0.11.0                   pypi_0    pypi
  
  keras-position-wise-feed-forward 0.6.0                    pypi_0    pypi
  
  keras-preprocessing       1.1.0                      py_1    anaconda
  
  keras-rectified-adam      0.17.0                   pypi_0    pypi
  
  keras-self-attention      0.41.0                   pypi_0    pypi
  
  keras-transformer         0.31.0                   pypi_0    pypi
  
  kiwisolver                1.0.1                    py36_2    intel
  
  libffi                    3.2.1                        11    intel
  
  libgcc-ng                 9.1.0                hdf63c60_0    anaconda
  
  libgfortran-ng            7.3.0                hdf63c60_0    anaconda
  
  libiconv                  1.14                          4    <unknown>
  
  libpng                    1.6.36                        2    intel
  
  libprotobuf               3.9.2                hd408876_0    anaconda
  
  librosa                   0.6.3                    pypi_0    pypi
  
  libsodium                 1.0.16                        3    <unknown>
  
  libstdcxx-ng              9.1.0                hdf63c60_0    anaconda
  
  libtiff                   4.0.9                he85c1e1_1  
  
  libxcb                    1.13                 h1bed415_1  
  
  libxml2                   2.9.8                hf84eae3_0  
  
  lightgbm                  2.3.1                    pypi_0    pypi
  
  llvmlite                  0.27.1                   py36_0    intel
  
  markdown                  3.1.1                    py36_0    anaconda
  
  markupsafe                1.0                      py36_3    <unknown>
  
  matplotlib                2.1.0            py36hba5de38_0  
  
  mercantile                1.1.2                    pypi_0    pypi
  
  metaflow                  2.0.0                    pypi_0    pypi
  
  mistune                   0.8.3                    py36_2    <unknown>
  
  mkl                       2019.4                intel_243    <unknown>
  
  mkl-service               1.0.0           py36h7b7c402_11    intel
  
  mkl_fft                   1.0.11           py36h7b7c402_2    intel
  
  mkl_random                1.0.2            py36h7b7c402_4    intel
  
  more-itertools            7.2.0                    pypi_0    pypi
  
  mpi4py                    3.0.0                    py36_3    intel
  
  mpmath                    1.1.0                    pypi_0    pypi
  
  munch                     2.5.0                    pypi_0    pypi
  
  nbconvert                 5.2.1                    py36_2    <unknown>
  
  nbformat                  4.4.0                    py36_2    <unknown>
  
  networkx                  2.4                      pypi_0    pypi
  
  ninja                     1.9.0            py36hfd86e86_0  
  
  noisyopt                  0.2.2                    pypi_0    pypi
  
  notebook                  5.2.2                    py36_1    intel
  
  numba                     0.42.1              np116py36_2    intel
  
  numexpr                   2.6.8                    py36_2    intel
  
  numpy                     1.16.2           py36h7b7c402_0    intel
  
  numpy-base                1.16.2                   py36_0    intel
  
  oauthlib                  3.1.0                    pypi_0    pypi
  
  olefile                   0.46                       py_0  
  
  openssl                   1.0.2r                        2    intel
  
  packaging                 19.2                     pypi_0    pypi
  
  pandas                    0.24.1                   py36_3    intel
  
  pandocfilters             1.4.1                    py36_2    <unknown>
  
  parso                     0.2.0                    py36_2    <unknown>
  
  path.py                   11.0.1                   py36_2    <unknown>
  
  pcre                      8.43                 he6710b0_0  
  
  pexpect                   4.2.1                    py36_4    <unknown>
  
  pickleshare               0.7.4                    py36_3    <unknown>
  
  pillow                    6.2.1                    pypi_0    pypi
  
  pip                       19.3.1                   pypi_0    pypi
  
  pluggy                    0.13.1                   pypi_0    pypi
  
  prompt_toolkit            1.0.15                   py36_2    <unknown>
  
  protobuf                  3.9.2            py36he6710b0_0    anaconda
  
  ptyprocess                0.5.2                    py36_2    <unknown>
  
  pulp                      2.0                      pypi_0    pypi
  
  py                        1.8.0                    pypi_0    pypi
  
  pyasn1                    0.4.8                    pypi_0    pypi
  
  pycosat                   0.6.3                    py36_3    intel
  
  pycparser                 2.18                     py36_2    intel
  
  pydot                     1.4.1                    pypi_0    pypi
  
  pyeditline                2.0.0                    py36_0    intel
  
  pygments                  2.2.0                    py36_5    <unknown>
  
  pygmy                     0.2.0                    pypi_0    pypi
  
  pyopenssl                 17.5.0                   py36_2    intel
  
  pyparsing                 2.2.0                    py36_2    intel
  
  pyportfolioopt            0.4.3                    pypi_0    pypi
  
  pyproj                    2.4.2.post1              pypi_0    pypi
  
  pyqt                      5.6.0            py36h22d08a2_6  
  
  pyrsistent                0.15.6                   pypi_0    pypi
  
  pysocks                   1.6.7                    py36_1    intel
  
  pytesseract               0.3.0                    pypi_0    pypi
  
  pytest                    4.6.6                    pypi_0    pypi
  
  python                    3.6.8                         7    intel
  
  python-dateutil           2.6.0                   py36_12    intel
  
  python-graphviz           0.13                     pypi_0    pypi
  
  pytorch                   1.3.1           py3.6_cuda10.1.243_cudnn7.6.3_0    pytorch
  
  pytz                      2018.4                   py36_3    intel
  
  pywavelets                1.1.1                    pypi_0    pypi
  
  pyyaml                    4.1                      py36_3    intel
  
  pyzmq                     16.0.2                   py36_6    <unknown>
  
  qt                        5.6.2               hd25b39d_14  
  
  rasterio                  1.1.1                    pypi_0    pypi
  
  regex                     2019.11.1                pypi_0    pypi
  
  requests                  2.20.1                   py36_1    intel
  
  requests-oauthlib         1.3.0                    pypi_0    pypi
  
  resampy                   0.2.1                    pypi_0    pypi
  
  rio-cogeo                 1.1.6                    pypi_0    pypi
  
  rsa                       3.4.2                    pypi_0    pypi
  
  ruamel_yaml               0.11.14                  py36_4    intel
  
  s3transfer                0.2.1                    pypi_0    pypi
  
  sacremoses                0.0.35                   pypi_0    pypi
  
  scikit-image              0.16.2                   pypi_0    pypi
  
  scikit-learn              0.20.3           py36h7b7c402_5    intel
  
  scipy                     1.3.3                    pypi_0    pypi
  
  seaborn                   0.9.0                    pypi_0    pypi
  
  sentencepiece             0.1.83                   pypi_0    pypi
  
  setuptools                39.0.1                   py36_0    intel
  
  shapely                   1.6.4.post2              pypi_0    pypi
  
  simplegeneric             0.8.1                    py36_7    <unknown>
  
  sip                       4.18.1           py36hf484d3e_2  
  
  six                       1.11.0                   py36_3    intel
  
  smp                       0.1.4                    py36_0    intel
  
  snuggs                    1.4.7                    pypi_0    pypi
  
  sqlite                    3.27.2                        4    intel
  
  supermercado              0.0.5                    pypi_0    pypi
  
  sympy                     1.4                      pypi_0    pypi
  
  tbb                       2019.6                intel_243    <unknown>
  
  tbb4py                    2019.6             py36_intel_0    <unknown>
  
  tcl                       8.6.4                        24    intel
  
  tensorboard               1.14.0           py36hf484d3e_0    anaconda
  
  tensorflow                1.14.0          gpu_py36h3fb9ad6_0    anaconda
  
  tensorflow-base           1.14.0          gpu_py36he45bfe2_0    anaconda
  
  tensorflow-estimator      1.14.0                     py_0    anaconda
  
  tensorflow-gpu            1.14.0               h0d30ee6_0    anaconda
  
  termcolor                 1.1.0                    py36_1    anaconda
  
  terminado                 0.8.1                    py36_2    <unknown>
  
  testpath                  0.3.1                    py36_2    <unknown>
  
  tk                        8.6.4                        29    intel
  
  torchvision               0.4.2                py36_cu101    pytorch
  
  tornado                   4.5.2                    py36_5    <unknown>
  
  tqdm                      4.36.1                     py_0    anaconda
  
  traitlets                 4.3.2                    py36_3    <unknown>
  
  transformers              2.1.1                    pypi_0    pypi
  
  tweepy                    3.8.0                    pypi_0    pypi
  
  urllib3                   1.22                     pypi_0    pypi
  
  wcwidth                   0.1.7                    py36_6    <unknown>
  
  webencodings              0.5.1                    py36_0    <unknown>
  
  werkzeug                  0.16.0                     py_0    anaconda
  
  wheel                     0.31.0                   py36_3    intel
  
  widgetsnbextension        3.2.0                    py36_1    <unknown>
  
  wrapt                     1.11.2           py36h7b6447c_0    anaconda
  
  x264                      20131218                      0    <unknown>
  
  xgboost                   0.81                     py36_0    intel
  
  xz                        5.2.3                         2    intel
  
  yaml                      0.1.7                         2    intel
  
  zipp                      0.6.0                    pypi_0    pypi
  
  zlib                      1.2.11                        5    intel
  
  </unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown></unknown>