Recherche avancée

Sur d’autres sites (7647)

• Web Analytics Reports : 10 Key Types and How to Use Them

  29 janvier 2024, par Erin

  You can’t optimise your website to drive better results if you don’t know how visitors are engaging with your site.

  But how do you correctly analyse data and identify patterns ? With the right platform, you can use a wide range of web analytics reports to dive deep into the data.

  In this article, we’ll discuss what website analytics reports are, different types, why you need them, and how to use reports to find the insights you need.

  What is web analytics ?

  Website analytics is the process of gathering, processing, and analysing data that shows what users are doing when they visit your website. 

  You typically achieve this with web analytics tools by adding a tracking code that shares data with the analytics platform when someone visits the site.

  

  The visitors trigger the tracking code, which collects data on how they act while on your site and then sends that information to the analytics platform. You can then see the data in your analytics solution and create reports based on this data.

  While there are a lot of web analytics solutions available, this article will specifically demonstrate reports using Matomo.

  What are web analytics reports ?

  Web analytics reports are analyses that focus on specific data points within your analytics platform. 

  For example, this channel report in Matomo shows the top referring channels of a website.

  

  Your marketing team can use this report to determine which channels drive the best results. In the example above, organic search drives almost double the visits and actions of social campaigns. 

  If you’re investing the same amount of money, you’d want to move more of your budget from social to search.

  Why you need to get familiar with specific web analytics reports

  The default web analytics dashboard offers an overview of high-level trends in performance. However, it usually does not give you specific insights that can help you optimise your marketing campaigns.

  For example, you can see that your conversions are down month over month. But, at a glance, you do not understand why that is.

  To understand why, you need to go granular and wider — looking into qualifying data that separates different types of visitors from each other.

  Gartner predicts that 70% of organisations will focus on “small and wide” data by 2025 over “big data.” Most companies lack the data volume to simply let big data and algorithms handle the optimising.

  What you can do instead is dive deep into each visitor. Figure out how they engage with your site, and then you can adjust your campaigns and page content accordingly.

  Common types of web analytics reports

  There are dozens of different web analytics reports, but they usually fall into four separate categories :

  

  • Referral sources : These reports show where your visitors come from. They range from channel reports — search, social media — to specific campaigns and ads.
  • Engagement (on-site actions) : These reports dive into what visitors are doing on your site. They break down clicks, scrolling, completed conversion goals, and more.
  • E-commerce performance : These reports show the performance of your e-commerce store. They’ll help you dive into the sales of individual products, trends in cart abandonment and more.
  • Demographics : These reports help you understand more about your visitors — where they’re visiting from, their browser language, device, and more.

  You can even combine insights across all four using audience segmentation and custom reports. (We’ll cover this in more detail later.)

  How to use 10 important website analytics reports

  The first step is to install the website analytics code on your website. (We include more detailed information in our guide on how to track website visitors.)

  Then, you need to wait until you have a few days (or, if you have limited traffic, a few weeks) of data. Without sufficient website visitor data, none of the reports will be meaningful.

  Visitor Overview report

  First, let’s take a look at the Visitor Overview report. It’s a general report that breaks down the visits over a given time period.

  

  What this report shows :

  • Trends in unique visits month over month
  • Basic engagement trends like the average visit length and bounce rate
  • The number of actions taken per page

  In general, this report is more of a high-level indicator you can use to explore certain areas more thoroughly. For example, if most of your traffic comes from organic traffic or social media, you can dive deeper into those channels.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Location report

  Next up, we have the most basic type of demographic report — the Location report. It shows where your visitors tend to access your website from.

  

  What this report shows :

  • The country, state or city your visitors access your website from

  This report is most useful for identifying regional trends. You may notice that your site is growing in popularity in a country. You can take advantage of this by creating a regional campaign to double down on a high performing audience.

  Device report

  Next, we have the Device report, which breaks down your visitors’ devices.

  

  What this report shows :

  • Overall device types used by your visitors
  • Specific device models used

  Today, most websites are responsive or use mobile-first design. So, just seeing that many people access your site through smartphones probably isn’t all that surprising.

  But you should ensure your responsive design doesn’t break down on popular devices. The design may not work effectively because many phones have different screen resolutions. 

  Users Flow report

  The Users Flow report dives deeper into visitor engagement — how your visitors act on your site. It shows common landing pages — the first page visitors land on — and how they usually navigate your site from there.

  

  What this report shows :

  • Popular landing pages
  • How your visitors most commonly navigate your site

  You can use this report to determine which intermediary pages are crucial to keeping visitors engaged. For example, you can prioritise optimisation and rewriting for case study pages that don’t get a lot of direct search or campaign traffic.

  Improving this flow can improve conversion rates and the impact of your marketing efforts.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Exit Pages report

  The Exit Pages report complements the Users Flow report well. It highlights the most common pages visitors leave your website from.

  

  What this report shows :

  • The most common exit pages on your website
  • The exit rates of these pages

  Pages with high exit rates fall into two categories. The first are pages where it makes sense that visitors leave, like a post-purchase thank-you page. The second are pages where you’d want your visitors to stay and keep flowing down the funnel. When the rates are unusually high on product pages, category pages, or case study pages, you may have found a problem.

  By combining insights from the Users Flow and Exit Pages reports, you can find valuable candidates for optimisation. This is a key aspect of effective conversion rate optimisation.

  Traffic Acquisition Channel report

  The Acquisition Channels report highlights the channels that drive the most visitors to your site.

  

  What this report shows :

  • Top referring traffic sources by channel type
  • The average time on site, bounce rates, and actions taken by the source

  Because of increasingly privacy-sensitive browsers and apps, the best way to reliably track traffic sources is to use campaign tracking URL. Matomo offers an easy-to-use campaign tracking URL builder to simplify this process.

  Search Engines and Keywords report

  The Search Engines and Keywords report shows which keywords are driving the most organic search traffic and from what search engines.

  

  What this report shows :

  • Search engine keywords that drive traffic
  • The different search engines that refer visitors

  One of the best ways to use this report is to identify low-hanging fruit. You want to find keywords driving some traffic where your page isn’t ranked in the top three results. If the keyword has high traffic potential, you should then work to optimise that page to rank higher and get more traffic. This technique is an efficient way to improve your SEO performance.

  Ecommerce Products report

  If you sell products directly on your website, the Ecommerce Products report is a lifesaver. It shows you exactly how all your products are performing.

  

  What this report shows :

  • How your products are selling
  • The average sale price (with coupons) and quantity

  This report could help an online retailer identify top-selling items, adjust pricing based on average sale prices, and strategically allocate resources to promote or restock high-performing products for maximum profitability.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Ecommerce Log report

  If you want to explore every single ecommerce interaction, the Ecommerce Log report is for you. It breaks down the actions of visitors who add products to their cart in real time.

  

  What this report shows :

  • The full journey of completed purchases and abandoned carts
  • The exact actions your potential customers take and how long their journeys last

  If you suspect that the user experience of your online store isn’t perfect, this report helps you confirm or deny that suspicion. By closely examining individual interactions, you can identify common exit pages or other issues.

• Amplification of recorded audio in flutter app using FFMPEG not working correctly

  20 mai 2024, par Noman khanbhai

  In my app I need to record audio and send it to server, server then sends the file to a hardware using mqtt and then file gets played on the hardware. I am using flutter to build app and using record 5.0.5 package for audio recording and for amplification ffmpeg_kit_flutter 6.0.3 package to do the amplification.

  


  The issue is it doesnt seems like there is much change in amplitude, I used different values for amplification factor but audio remains same.

  


  Here is the code for amplification

  


  Future<string>? amplifyAudio(&#xA;      String inputPath, String outputPath) async {&#xA;&#xA;    // Build FFmpeg command to amplify audio&#xA;    outputPath = await modifyOutputPath(inputPath)!;&#xA;    String audioFilter = &#x27;volume=${amplificationFactor}dB&#x27;; &#xA;    //-c:a aac&#xA;    String command = &#x27;-i $inputPath -af $audioFilter $outputPath&#x27;;&#xA;&#xA;    // Execute FFmpeg command&#xA;    await FFmpegKit.executeAsync(command).then((session) async {&#xA;      debugPrint("After executeAsync session ${session.toString()}");&#xA;      debugPrint(&#xA;          "After executeAsync returncode ${await session.getReturnCode()}");&#xA;      debugPrint("After executeAsync command ${session.getCommand()}");&#xA;      log("After executeAsync alllogs ${await session.getAllLogs()}");&#xA;      log("After executeAsync alllogstring ${await session.getAllLogsAsString()}");&#xA;      log("After executeAsync failStackTrace ${await session.getFailStackTrace()}");&#xA;    }).onError((error, stackTrace) {&#xA;      debugPrint("After executeAsync error ${error.toString()}");&#xA;    });&#xA;&#xA;    return outputPath;&#xA;  }&#xA;&#xA;</string>

  


  This are the logs when above method gets executed.

  


  FFMpeg command -> `-i /data/user/0/com.orgname.flutter.appname/app_flutter/1716209206469.aac -af volume=10.0dB /storage/emulated/0/Download/1716209213238_amplified.aac`

> Logs
> After executeAsync alllogstring ffmpeg version n6.0 Copyright (c) 2000-2023 the FFmpeg developers
> built with Android (7155654, based on r399163b1) clang version 11.0.5 (https://android.googlesource.com/toolchain/llvm-project 87f1315dfbea7c137aa2e6d362dbb457e388158d)
> configuration: --cross-prefix=aarch64-linux-android- --sysroot=/Users/sue/Library/Android/sdk/ndk/22.1.7171670/toolchains/llvm/prebuilt/darwin-x86_64/sysroot --prefix=/Users/sue/Projects/arthenica/ffmpeg-kit/prebuilt/android-arm64/ffmpeg --pkg-config=/opt/homebrew/bin/pkg-config --enable-version3 --arch=aarch64 --cpu=armv8-a --target-os=android --enable-neon --enable-asm --enable-inline-asm --ar=aarch64-linux-android-ar --cc=aarch64-linux-android24-clang --cxx=aarch64-linux-android24-clang++ --ranlib=aarch64-linux-android-ranlib --strip=aarch64-linux-android-strip --nm=aarch64-linux-android-nm --extra-libs='-L/Users/sue/Projects/arthenica/ffmpeg-kit/prebuilt/android-arm64/cpu-features/lib -lndk_compat' --disable-autodetect --enable-cross-compile --enable-pic --enable-jni --enable-optimizations --enable-swscale --disable-static --enable-shared --enable-pthreads --enable-v4l2-m2m --disable-outdev=fbdev --disable-indev=fbdev --enable-small --disable-xmm-clobber-test --disable-debug --enable-lto --disable-neon-clobber-test --disable-programs --disable-postproc --disable-doc --disable-htmlpages --disable-manpages --disable-podpages --disable-txtpages --disable-sndio --disable-schannel --disable-securetransport --disable-xlib --disable-cuda --disable-cuvid --disable-nvenc --disable-vaapi --disable-vdpau --disable-videotoolbox --disable-audiotoolbox --disable-appkit --disable-alsa --disable-cuda --disable-cuvid --disable-nvenc --disable-vaapi --disable-vdpau --enable-gmp --enable-gnutls --enable-iconv --disable-sdl2 --disable-openssl --enable-zlib --enable-mediacodec
> libavutil      58.  2.100 / 58.  2.100
> libavcodec     60.  3.100 / 60.  3.100
> libavformat    60.  3.100 / 60.  3.100
> libavdevice    60.  1.100 / 60.  1.100
> libavfilter     9.  3.100 /  9.  3.100
> libswscale      7.  1.100 /  7.  1.100
> libswresample   4. 10.100 /  4. 10.100
> Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/data/user/0/com.orgname.flutter.appname/app_flutter/1716209206469.aac':
> Metadata:
> major_brand     : mp42
> minor_version   : 0
> compatible_brands: isommp42
> creation_time   : 2024-05-20T12:46:52.000000Z
> com.android.version: 12
> Duration: 00:00:04.76, start: 0.000000, bitrate: 131 kb/s
> Stream #0:0[0x1](eng): Audio: aac (mp4a / 0x6134706D), 44100 Hz, stereo, fltp, 128 kb/s (default)
> Metadata:
> creation_time   : 2024-05-20T12:46:52.000000Z
> handler_name    : SoundHandle
> vendor_id       : [0][0][0][0]
> Stream mapping:
> Stream #0:0 -> #0:0 (aac (native) -> aac (native))
> Press [q] to stop, [?] for help


  


  Note - I am also playing the audio after recording and before amplification in app, and also saving in download. to make sure audio file is correct.

  


  Amplified file also gets saved but there is almost no difference.

  


  I have also searched/googled/ and also done chatgpt to resolve issue. but nothing worked.

  


• ffprobe newer version detect audio codec incorrectly

  16 janvier, par alancc

  I find a strange problem.

  


  I have a test video with h264 video codec and aac audio codec. It is at https://drive.google.com/file/d/1YAyz5cO0kb9r0MgahCpISR4bZ_1_n8PL/view?usp=sharing

  


  I build a ffmpeg version by myself, its version is :

  


  ffprobe version 7.0.2 Copyright (c) 2007-2024 the FFmpeg developers
  built with gcc 14.1.0 (Rev3, Built by MSYS2 project)
  configuration: --enable-shared
  libavutil      59.  8.100 / 59.  8.100
  libavcodec     61.  3.100 / 61.  3.100
  libavformat    61.  1.100 / 61.  1.100
  libavdevice    61.  1.100 / 61.  1.100
  libavfilter    10.  1.100 / 10.  1.100
  libswscale      8.  1.100 /  8.  1.100
  libswresample   5.  1.100 /  5.  1.100


  


  I then use ffprobe to get its info :

  


  ffprobe -v quiet -print_format ini -show_streams -show_packets test_h264.mp4 > test_h264.ini


  


  Then I get an ini file which shows the audio codec as MP2 :

  


  [streams.stream.0]
index=0
codec_name=mp2
codec_long_name=MP2 (MPEG audio layer 2)
profile=unknown
codec_type=audio
codec_tag_string=mp4a
codec_tag=0x6134706d
sample_fmt=fltp
sample_rate=44100
channels=2
channel_layout=stereo
bits_per_sample=0
initial_padding=0
id=0x1
r_frame_rate=0/0
avg_frame_rate=0/0
time_base=1/44100
start_pts=2788
start_time=0.063220
duration_ts=435455
duration=9.874263
bit_rate=127706
max_bit_rate=N/A
bits_per_raw_sample=N/A
nb_frames=378
nb_read_frames=N/A
nb_read_packets=378


  


  Another developer he uses his version of ffprobe :

  


  ffprobe version 2023-02-22-git-d5cc7acff1-full_build-www.gyan.dev Copyright (c) 2007-2023 the FFmpeg developers  


  


  Based on the year, my version(2024) should be newer than his(2023), but his version of ffprobe can get the audio codec properly :

  


  [streams.stream.1]
index=1
codec_name=aac
codec_long_name=AAC (Advanced Audio Coding)
profile=LC
codec_type=audio
codec_tag_string=mp4a
codec_tag=0x6134706d
sample_fmt=fltp
sample_rate=44100
channels=2
channel_layout=stereo
bits_per_sample=0
initial_padding=0
id=0x2
r_frame_rate=0/0
avg_frame_rate=0/0
time_base=1/44100
start_pts=1764
start_time=0.040000
duration_ts=436480
duration=9.897506
bit_rate=111733
max_bit_rate=N/A
bits_per_raw_sample=N/A
nb_frames=427
nb_read_frames=N/A
nb_read_packets=427
extradata_size=5


  


  Why ?

  


  I also tried a ffprobe version on ubuntu with the following version :

  


  ffprobe version 6.1.1-3ubuntu5 Copyright (c) 2007-2023 the FFmpeg developers
  built with gcc 13 (Ubuntu 13.2.0-23ubuntu3)
  configuration: --prefix=/usr --extra-version=3ubuntu5 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --disable-omx --enable-gnutls --enable-libaom --enable-libass --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libglslang --enable-libgme --enable-libgsm --enable-libharfbuzz --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-openal --enable-opencl --enable-opengl --disable-sndio --enable-libvpl --disable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-ladspa --enable-libbluray --enable-libjack --enable-libpulse --enable-librabbitmq --enable-librist --enable-libsrt --enable-libssh --enable-libsvtav1 --enable-libx264 --enable-libzmq --enable-libzvbi --enable-lv2 --enable-sdl2 --enable-libplacebo --enable-librav1e --enable-pocketsphinx --enable-librsvg --enable-libjxl --enable-shared
  libavutil      58. 29.100 / 58. 29.100
  libavcodec     60. 31.102 / 60. 31.102
  libavformat    60. 16.100 / 60. 16.100
  libavdevice    60.  3.100 / 60.  3.100
  libavfilter     9. 12.100 /  9. 12.100
  libswscale      7.  5.100 /  7.  5.100
  libswresample   4. 12.100 /  4. 12.100
  libpostproc    57.  3.100 / 57.  3.100


  


  It will detect the audio as aac properly, but with different parameters, for example, bit_rate is 111733(developer) but 110399(ubuntu). But this parameter comes from the same file so should be the same.

  


  [streams.stream.1]
index=1
codec_name=aac
codec_long_name=AAC (Advanced Audio Coding)
profile=LC
codec_type=audio
codec_tag_string=mp4a
codec_tag=0x6134706d
sample_fmt=fltp
sample_rate=44100
channels=2
channel_layout=stereo
bits_per_sample=0
initial_padding=0
id=0x2
r_frame_rate=0/0
avg_frame_rate=0/0
time_base=1/44100
start_pts=0
start_time=0.000000
duration_ts=441353
duration=10.008005
bit_rate=110399
max_bit_rate=N/A
bits_per_raw_sample=N/A
nb_frames=432
nb_read_frames=N/A
nb_read_packets=432
extradata_size=5