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  • ffmpeg - convert MP4 to Panasonic Lumix playable MJPEG [closed]

    21 août 2024, par Maro Natts

    I'm new to ffmpeg and ffprobe, I started using it to convert videos to show on 3DS and DSi for an art project.

    


    Now I want to show my own videos on a Panasonic LUMIX digicam (DMC-FT2)(JPN), but have had trouble getting the device to play the video.

    


    The digi takes videos in AVCHD Lite and Motion JPEG.

    


    I've tried online converting mp4 to the respective formats + changing file name, but the device only recognises that it's there — refuses to/can't play it.

    


    I also tried using this code to convert to MJPEG :
ffmpeg -i input.mp4 -c:v mjpeg -q:v 2 -an output.mjpeg

    


    But no luck ! Changed the filename to match the others, the camera recognised the file is there, but can't play it.

    


    So I used this code to get the information of a MJPEG video taken on the digi :
/opt/ffmpeg/ffprobe file.mp4 -show_streams  -select_streams v  -print_format json

    


    and got the following, is it possible to convert my own video (mp4) to these settings ? So that it can play on the device ? If so how ?

    


    Thanks !

    


      Metadata:
    major_brand     : qt  
    minor_version   : 537331972
    compatible_brands: qt  pana
    creation_time   : 2024-08-21T21:54:59.000000Z
  Duration: 00:00:06.00, start: 0.000000, bitrate: 12287 kb/s
  Stream #0:0[0x1](eng): Video: mjpeg (Baseline) (jpeg / 0x6765706A), yuvj420p(pc, bt470bg/unknown/unknown), 640x480, 11083 kb/s, 30 fps, 30 tbr, 30 tbn (default)
      Metadata:
        creation_time   : 2024-08-21T21:54:59.000000Z
        vendor_id       : pana
        encoder         : Photo - JPEG
  Stream #0:1[0x2](eng): Audio: pcm_s16be (twos / 0x736F7774), 16000 Hz, 1 channels, s16, 256 kb/s (default)
      Metadata:
        creation_time   : 2024-08-21T21:54:59.000000Z
        vendor_id       : pana
    "streams": [
        {
            "index": 0,
            "codec_name": "mjpeg",
            "codec_long_name": "Motion JPEG",
            "profile": "Baseline",
            "codec_type": "video",
            "codec_tag_string": "jpeg",
            "codec_tag": "0x6765706a",
            "width": 640,
            "height": 480,
            "coded_width": 640,
            "coded_height": 480,
            "closed_captions": 0,
            "film_grain": 0,
            "has_b_frames": 0,
            "pix_fmt": "yuvj420p",
            "level": -99,
            "color_range": "pc",
            "color_space": "bt470bg",
            "chroma_location": "center",
            "refs": 1,
            "id": "0x1",
            "r_frame_rate": "30/1",
            "avg_frame_rate": "30/1",
            "time_base": "1/30",
            "start_pts": 0,
            "start_time": "0.000000",
            "duration_ts": 180,
            "duration": "6.000000",
            "bit_rate": "11083093",
            "bits_per_raw_sample": "8",
            "nb_frames": "180",
            "disposition": {
                "default": 1,
                "dub": 0,
                "original": 0,
                "comment": 0,
                "lyrics": 0,
                "karaoke": 0,
                "forced": 0,
                "hearing_impaired": 0,
                "visual_impaired": 0,
                "clean_effects": 0,
                "attached_pic": 0,
                "timed_thumbnails": 0,
                "non_diegetic": 0,
                "captions": 0,
                "descriptions": 0,
                "metadata": 0,
                "dependent": 0,
                "still_image": 0
            },
            "tags": {
                "creation_time": "2024-08-21T21:54:59.000000Z",
                "language": "eng",
                "vendor_id": "pana",
                "encoder": "Photo - JPEG"
            }
        }
    ]
}



    


  • Unable to stream video file from MediaMTX media server to browser via WebRTC

    8 juin 2024, par thegreatjedi

    I took over a repository at work. It's a working demo comprising a web server which receives video and camera feeds from a media server (built from the rtsp-simple-server Docker image) via a RTSP relay server and streams the feeds to the client, all deployed via Docker Compose.

    


    I'm trying to switch over to use WebRTC instead. rtsp-simple-server has upgraded into MediaMTX since the time the demo was created 2 years ago. This is the relevant section of the updated Docker Compose configuration :

    


      media-server:
    image: bluenviron/mediamtx:latest-ffmpeg
    expose:
      - 8889
    init: true
    ports:
      - 8889:8889
    restart: unless-stopped
    volumes:
      - type: bind
        source: ./demo/vids
        target: /vids
      - type: bind
        source: ./demo/mediamtx.yml
        target: /mediamtx.yml


    


    Relevant part of the MediaMTX custom configuration in mediamtx.yml :

    


    ###############################################
# Path settings

# Settings in "paths" are applied to specific paths, and the map key
# is the name of the path.
# Any setting in "pathDefaults" can be overridden here.
# It's possible to use regular expressions by using a tilde as prefix,
# for example "~^(test1|test2)$" will match both "test1" and "test2",
# for example "~^prefix" will match all paths that start with "prefix".
paths:
  # example:
  # my_camera:
  #   source: rtsp://my_camera
  ~^demo\d+$:
    runOnDemand: ffmpeg -re -stream_loop -1 -i /vids/$MTX_PATH.mp4 -c:v libvpx -b:v 0 -crf 18 -qmin 18 -qmax 18 -f webm http://localhost:8889/$MTX_PATH/whip

  # Settings under path "all_others" are applied to all paths that
  # do not match another entry.
  all_others:


    


    I've absolutely no experience with WebRTC. This is my first time hearing of this protocol, let alone working with it. From what I understand, I need to convert my demo mp4 videos (which were successfully streaming via RTSP in the previous implementation) to a compatible video codec, so I've opted for VP8.

    


    Before trying to stream the videos into my web server, I tested the stream directly in the browser (tried with both the latest versions of Chrome and Edge). I went to http://localhost:8889/demo0 (which should convert demo0.mp4 to VP8 and then stream it over WebRTC). The video player loaded in the browser but no video data was received and nothing played. After several seconds, the screen displayed "Error : bad status code 400, retrying in some seconds". In the browser console, it showed :

    


    Failed to load resource : the server responded with a status of 400 (Bad Request)

    


    Inside the MediaMTX container's runtime logs, this is what's displayed :

    


    2024-04-02 14:53:08 ffmpeg version 6.1.1 Copyright (c) 2000-2023 the FFmpeg developers
2024-04-02 14:53:08   built with gcc 13.2.1 (Alpine 13.2.1_git20231014) 20231014
2024-04-02 14:53:08   configuration: --prefix=/usr --disable-librtmp --disable-lzma --disable-static --disable-stripping --enable-avfilter --enable-gpl --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libdav1d --enable-libdrm --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libharfbuzz --enable-libmp3lame --enable-libopenmpt --enable-libopus --enable-libplacebo --enable-libpulse --enable-librav1e --enable-librist --enable-libsoxr --enable-libsrt --enable-libssh --enable-libtheora --enable-libv4l2 --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxcb --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-lto=auto --enable-lv2 --enable-openssl --enable-pic --enable-postproc --enable-pthreads --enable-shared --enable-vaapi --enable-vdpau --enable-version3 --enable-vulkan --optflags=-O3 --enable-libjxl --enable-libsvtav1 --enable-libvpl
2024-04-02 14:53:08   libavutil      58. 29.100 / 58. 29.100
2024-04-02 14:53:08   libavcodec     60. 31.102 / 60. 31.102
2024-04-02 14:53:08   libavformat    60. 16.100 / 60. 16.100
2024-04-02 14:53:08   libavdevice    60.  3.100 / 60.  3.100
2024-04-02 14:53:08   libavfilter     9. 12.100 /  9. 12.100
2024-04-02 14:53:08   libswscale      7.  5.100 /  7.  5.100
2024-04-02 14:53:08   libswresample   5.  0.100 /  5.  0.100
2024-04-02 14:53:08   libpostproc    57.  3.100 / 57.  3.100
2024-04-02 14:53:08 Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/vids/demo0.mp4':
2024-04-02 14:53:08   Metadata:
2024-04-02 14:53:08     major_brand     : isom
2024-04-02 14:53:08     minor_version   : 512
2024-04-02 14:53:08     compatible_brands: isomiso2mp41
2024-04-02 14:53:08     encoder         : Lavf58.76.100
2024-04-02 14:53:08   Duration: 00:00:03.47, start: 0.000000, bitrate: 1675 kb/s
2024-04-02 14:53:08   Stream #0:0[0x1](und): Video: mpeg1video (mp4v / 0x7634706D), yuv420p(tv, progressive), 640x360 [SAR 1:1 DAR 16:9], 104857 kb/s, 30 fps, 30 tbr, 90k tbn (default)
2024-04-02 14:53:08     Metadata:
2024-04-02 14:53:08       handler_name    : VideoHandler
2024-04-02 14:53:08       vendor_id       : [0][0][0][0]
2024-04-02 14:53:08     Side data:
2024-04-02 14:53:08       cpb: bitrate max/min/avg: 0/0/0 buffer size: 49152 vbv_delay: N/A
2024-04-02 14:53:08 Stream mapping:
2024-04-02 14:53:08   Stream #0:0 -> #0:0 (mpeg1video (native) -> vp8 (libvpx))
2024-04-02 14:53:08 Press [q] to stop, [?] for help
2024-04-02 14:53:08 [libvpx @ 0x7faa8591b8c0] v1.13.1
2024-04-02 14:53:08 [libvpx @ 0x7faa8591b8c0] Bitrate not specified for constrained quality mode, using default of 256kbit/sec
2024-04-02 14:53:08 Output #0, webm, to 'http://localhost:8889/demo0/whip':
2024-04-02 14:53:08   Metadata:
2024-04-02 14:53:08     major_brand     : isom
2024-04-02 14:53:08     minor_version   : 512
2024-04-02 14:53:08     compatible_brands: isomiso2mp41
2024-04-02 14:53:08     encoder         : Lavf60.16.100
2024-04-02 14:53:08   Stream #0:0(und): Video: vp8, yuv420p(tv, progressive), 640x360 [SAR 1:1 DAR 16:9], q=2-31, 256 kb/s, 30 fps, 1k tbn (default)
2024-04-02 14:53:08     Metadata:
2024-04-02 14:53:08       handler_name    : VideoHandler
2024-04-02 14:53:08       vendor_id       : [0][0][0][0]
2024-04-02 14:53:08       encoder         : Lavc60.31.102 libvpx
2024-04-02 14:53:08     Side data:
2024-04-02 14:53:08       cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A
2024-04-02 14:53:18 2024/04/02 06:53:18 INF [path demo0] runOnDemand command stopped: timed out
2024-04-02 14:53:18 2024/04/02 06:53:18 INF [WebRTC] [session 0f460c76] closed: source of path 'demo0' has timed out
[out#0/webm @ 0x7faa859487c0] video:272kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 1.042856%
2024-04-02 14:53:18 frame=  315 fps= 32 q=18.0 Lsize=     275kB time=00:00:10.46 bitrate= 215.1kbits/s speed=1.05x    
2024-04-02 14:53:18 Exiting normally, received signal 2.


    


    I'm not sure what this is supposed to mean ? Why isn't the server able to stream this 3-second, 709kb video even once ? The browser connected to the server and the URL successfully, but no data was being transferred.

    


    Just in case, I decided to manually convert all of my mp4 files to webm using ffmpeg, and verified with Window's media player that the webm videos work. Then, I modified MediaMTX's configuration to stream the webm videos directly :

    


    paths:
  # example:
  # my_camera:
  #   source: rtsp://my_camera
  ~^demo\d+$:
    runOnDemand: ffmpeg -re -stream_loop -1 -i /vids/$MTX_PATH.webm -c copy -f webm http://localhost:8889/$MTX_PATH/whip


    


    However, the error persists :

    


    2024-04-02 15:03:58 ffmpeg version 6.1.1 Copyright (c) 2000-2023 the FFmpeg developers
2024-04-02 15:03:58   built with gcc 13.2.1 (Alpine 13.2.1_git20231014) 20231014
2024-04-02 15:03:58   configuration: --prefix=/usr --disable-librtmp --disable-lzma --disable-static --disable-stripping --enable-avfilter --enable-gpl --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libdav1d --enable-libdrm --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libharfbuzz --enable-libmp3lame --enable-libopenmpt --enable-libopus --enable-libplacebo --enable-libpulse --enable-librav1e --enable-librist --enable-libsoxr --enable-libsrt --enable-libssh --enable-libtheora --enable-libv4l2 --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxcb --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-lto=auto --enable-lv2 --enable-openssl --enable-pic --enable-postproc --enable-pthreads --enable-shared --enable-vaapi --enable-vdpau --enable-version3 --enable-vulkan --optflags=-O3 --enable-libjxl --enable-libsvtav1 --enable-libvpl
2024-04-02 15:03:58   libavutil      58. 29.100 / 58. 29.100
2024-04-02 15:03:58   libavcodec     60. 31.102 / 60. 31.102
2024-04-02 15:03:58   libavformat    60. 16.100 / 60. 16.100
2024-04-02 15:03:58   libavdevice    60.  3.100 / 60.  3.100
2024-04-02 15:03:58   libavfilter     9. 12.100 /  9. 12.100
2024-04-02 15:03:58   libswscale      7.  5.100 /  7.  5.100
2024-04-02 15:03:58   libswresample   5.  0.100 /  5.  0.100
2024-04-02 15:03:58   libpostproc    57.  3.100 / 57.  3.100
2024-04-02 15:03:58 Input #0, matroska,webm, from '/vids/demo0.webm':
2024-04-02 15:03:58   Metadata:
2024-04-02 15:03:58     COMPATIBLE_BRANDS: isomiso2mp41
2024-04-02 15:03:58     MAJOR_BRAND     : isom
2024-04-02 15:03:58     MINOR_VERSION   : 512
2024-04-02 15:03:58     ENCODER         : Lavf60.16.100
2024-04-02 15:03:58   Duration: 00:00:03.47, start: 0.000000, bitrate: 217 kb/s
2024-04-02 15:03:58   Stream #0:0: Video: vp8, yuv420p(tv, progressive), 640x360, SAR 1:1 DAR 16:9, 30 fps, 30 tbr, 1k tbn (default)
2024-04-02 15:03:58     Metadata:
2024-04-02 15:03:58       HANDLER_NAME    : VideoHandler
2024-04-02 15:03:58       VENDOR_ID       : [0][0][0][0]
2024-04-02 15:03:58       ENCODER         : Lavc60.31.102 libvpx
2024-04-02 15:03:58       DURATION        : 00:00:03.466000000
2024-04-02 15:03:58 Output #0, webm, to 'http://localhost:8889/demo0/whip':
2024-04-02 15:03:58   Metadata:
2024-04-02 15:03:58     COMPATIBLE_BRANDS: isomiso2mp41
2024-04-02 15:03:58     MAJOR_BRAND     : isom
2024-04-02 15:03:58     MINOR_VERSION   : 512
2024-04-02 15:03:58     encoder         : Lavf60.16.100
2024-04-02 15:03:58   Stream #0:0: Video: vp8, yuv420p(tv, progressive), 640x360 [SAR 1:1 DAR 16:9], q=2-31, 30 fps, 30 tbr, 1k tbn (default)
2024-04-02 15:03:58     Metadata:
2024-04-02 15:03:58       HANDLER_NAME    : VideoHandler
2024-04-02 15:03:58       VENDOR_ID       : [0][0][0][0]
2024-04-02 15:03:58       ENCODER         : Lavc60.31.102 libvpx
2024-04-02 15:03:58       DURATION        : 00:00:03.466000000
2024-04-02 15:03:58 Stream mapping:
2024-04-02 15:03:58   Stream #0:0 -> #0:0 (copy)
2024-04-02 15:03:58 Press [q] to stop, [?] for help
2024-04-02 15:04:08 2024/04/02 07:04:08 INF [path demo0] runOnDemand command stopped: timed out
2024-04-02 15:04:08 2024/04/02 07:04:08 INF [WebRTC] [session 829664cb] closed: source of path 'demo0' has timed out
[out#0/webm @ 0x7f04b00515c0] video:281kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 1.023511%
2024-04-02 15:04:08 size=     284kB time=00:00:10.49 bitrate= 221.3kbits/s speed=1.05x    
2024-04-02 15:04:08 Exiting normally, received signal 2.


    


    This is the same when I try to stream my other videos (demo1.mp4, demo2.mp4 etc.). What am I doing wrong ?

    


  • What Is Incrementality & Why Is It Important in Marketing ?

    26 mars 2024, par Erin

    Imagine this : you just launched your latest campaign and it was a major success.

    You blew last month’s results out of the water.

    You combined a variety of tactics, channels and ad creatives to make it work.

    Now, it’s time to build the next campaign.

    The only issue ?

    You don’t know what made it successful or how much your recent efforts impacted the results.

    You’ve been building your brand for years. You’ve built up a variety of marketing pillars that are working for you. So, how do you know how much of your campaign is from years of effort or a new tactic you just implemented ?

    The key is incrementality.

    This is a way to properly attribute the right weight to your marketing tactics.

    In this article, we break down what incrementality is in marketing, how it differs from traditional attribution and how you can calculate and track it to grow your business.

    What is incrementality in marketing ?

    Incrementality in marketing is growth that can be directly credited to a marketing effort above and beyond the success of the branding.

    It looks at how much a specific tactic positively impacted a campaign on top of overall branding and marketing strategies.

    What is incrementally in marketing?

    For example, this could be how much a specific tactic, campaign or channel helped increase conversions, email sign-ups or organic traffic.

    The primary purpose of incrementally in marketing is to more accurately determine the impact a single marketing variable had on the success of a project.

    It removes every other factor and isolates the specific method to help marketers double down on that strategy or move on to new tactics.

    With Matomo, you can track conversions simply. With our last non-direct channel attribution system, you’ll be able to quickly see what channels are converting (and which aren’t) so you can gain insights into incrementality. 

    See why over 1 million websites choose Matomo today.

    Try Matomo for Free

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

    No credit card required

    How incrementality differs from attribution

    In marketing and advertising, it’s crucial to understand what tactics and activities drive growth.

    Incrementality and attribution help marketers and business owners understand what efforts impact their results.

    But they’re not the same.

    Here’s how they differ :

    Incrementality vs. attribution

    Incrementality explained

    Incrementality measures how much a specific marketing campaign or activity drives additional sales or growth.

    Simply put, it’s analysing the difference between having never implemented the campaign (or tactic or channel) in the first place versus the impact of the activity.

    In other words, how much revenue would you have generated this month without campaign A ?

    And how much additional revenue did you generate directly due to campaign A ?

    The reality is that dozens of factors impact revenue and growth.

    You aren’t just pouring your marketing into one specific channel or campaign at a time.

    Chances are, you’ve got your hands on several marketing initiatives like SEO, PPC, organic social media, paid search, email marketing and more.

    Beyond that, you’ve built a brand with a not-so-tangible impact on your recurring revenue.

    So, the question is, if you took away your new campaign, would you still be generating the same amount of revenue ?

    And, if you add in that campaign, how much additional revenue and growth did it directly create ?

    That is incrementality. It’s how much a campaign went above and beyond to add new revenue that wouldn’t have been there otherwise.

    So, how does attribution play into all of this ?

    Attribution explained

    Attribution is simply the process of assigning credit for a conversion to a particular marketing touchpoint.

    While incrementality is about narrowing down the overall revenue impact from a particular campaign, attribution seeks to point to a specific channel to attribute a sale.

    For example, in any given marketing campaign, you have a few marketing tactics.

    Let’s say you’re launching a limited-time product.

    You might have :

    • Paid ads via Facebook and Instagram
    • A blog post sharing how the product works
    • Organic social media posts on Instagram and TikTok
    • Email waitlist campaign building excitement around the upcoming product
    • SMS campaigns to share a limited-time discount

    So, when the time comes for the sale launch, and you generate $30,000 in revenue, what channel gets the credit ?

    Do you give credit to the paid ads on Facebook ? What about Instagram ? They got people to follow you and got them on the email waitlist.

    Do you give credit to email for reminding people of the upcoming sale ? What about your social media posts that reminded people there ?

    Or do you credit your SMS campaign that shared a limited-time discount ?

    Which channel is responsible for the sale ?

    This is what attribution is all about.

    It’s about giving credit where credit is due.

    The reason you want to attribute credit ? So you know what’s working and can double down your efforts on the high-impact marketing activities and channels.

    Leveraging incrementality and attribution together

    Incrementality and attribution aren’t competing methods of analysing what’s working.

    They’re complementary to one another and go hand in hand.

    You can (and should) use attribution and incrementality in your marketing to help understand what activities, campaigns and channels are making the biggest incremental impact on your business growth.

    Why it’s important to measure incrementality

    Incrementality is crucial to measure if you want to pour your time, money and effort into the right marketing channels and tactics.

    Here are a few reasons why you need to measure incrementality if you want to be successful with your marketing and grow your business :

    1. Accurate data

    If you want to be an effective marketer, you need to be accurate.

    You can’t blindly start marketing campaigns in hopes that you will sell many products or services.

    That’s not how it works.

    Sure, you’ll probably make some sales here and there. But to truly be effective with your work, you must measure your activities and channels correctly.

    Incrementality helps you see how each channel, tactic or campaign made a difference in your marketing.

    Matomo gives you 100% accurate data on your website activities. Unlike Google Analytics, we don’t use data sampling which limits how much data is analysed.

    Screenshot example of the Matomo dashboard

    2. Helps you to best determine the right tactics for success

    How can you plan your marketing strategy if you don’t know what’s working ?

    Think about it.

    You’ll be blindly sailing the seas without a compass telling you where to go.

    Measuring incrementality in your marketing tactics and channels helps you understand the best tactics.

    It shows you what’s moving the needle (and what’s not).

    Once you can see the most impactful tactics and channels, you can forge future campaigns that you know will work.

    3. Allows you to get the most out of your marketing budget

    Since incrementality sheds light on what’s moving your business forward, you can confidently implement your efforts on the right tactics and channels.

    Guess what happens when you start doubling down on the most impactful activities ?

    You start increasing revenue, decreasing ad spend and getting a higher return on investment.

    The result is that you will get more out of your marketing budget.

    Not only will you boost revenue, but you’ll also be able to boost profit margins since you’re not wasting money on ineffective tactics.

    4. Increase traffic

    When you see what’s truly working in your business, you can figure out what channels and tactics you should be working.

    Incrementality helps you understand not only what your best revenue tactics are but also what channels and campaigns are bringing in the most traffic.

    When you can increase traffic, you can increase your overall marketing impact.

    5. Increase revenue

    Finally, with increased traffic, the inevitable result is more conversions.

    More conversions mean more revenue.

    Incrementality gives you a vision of the tactics and channels that are converting the best.

    If you can see that your SMS campaigns are driving the best ROI, then you know that you’ll grow your revenue by pouring more into acquiring SMS leads.

    By calculating incrementality regularly, you can rest assured that you’re only investing time and money into the most impactful activities in terms of revenue generation.

    How to calculate and test incrementality in marketing

    Now that you understand how incrementality works and why it’s important to calculate, the question is : 

    How do you calculate and conduct incrementality tests ?

    Given the ever-changing marketing landscape, it’s crucial to understand how to calculate and test incrementally in your business.

    If you’re not sure how incrementality testing works, then follow these simple steps :

    How to test and analyze incrementality in marketing?

    Your first step to get an incrementality measurement is to conduct what’s referred to as a “holdout test.”

    It’s not a robust test, but it’s an easy way to get the ball rolling with incrementality.

    Here’s how it works :

    1. Choose your target audience.

    With Matomo’s segmentation feature, you can get pretty specific with your target audience, such as :

      • Visitors from the UK
      • Returning visitors
      • Mobile users
      • Visitors who clicked on a specific ad
    1. Split your audience into two groups :
      • Control group (60% of the segment)
      • Test group (40% of the segment)
    1. Target the control group with your marketing tactic (the simpler the tactic, the better).
    1. Target the test group with a different marketing tactic.
    1. Analyse the results. The difference between the control and test groups is the incremental lift in results. The new marketing tactic is either more effective or not.
    1. Repeat the test with a new control group (with an updated tactic) and a new test group (with a new tactic).

    Matomo can help you analyse the results of your campaigns in our Goals feature. Set up business objectives so you can easily track different goals like conversions.

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    Here’s an example of how this incrementality testing could look in real life.

    Imagine a fitness retailer wants to start showing Facebook ads in their marketing mix.

    The marketing manager decided to conduct a holdout test. If we match our example below with the steps above, this is how the holdout test might look.

    1. They choose people who’ve purchased free weights in the past as their target audience (see how that segmentation works ?).
    2. They split this segment into a control group and a test group.
    3. For this test, they direct their regular marketing campaign to the control group (60% of the segment). The campaign includes promoting a 20% off sale on organic social media posts, email marketing, and SMS.
    4. They direct their regular marketing campaign plus Facebook ads to the test group (40% of the segment).
    5. They ran the campaign for three weeks with the goal for sale conversions and noticed :
      • The control group had a 1.5% conversion rate.
      • The test group (with Facebook ads) had a 2.1% conversion rate.
      • In this scenario, they could see the group who saw the Facebook ads convert better.
      • They created the following formula to measure the incremental lift of the Facebook ads :
    Calculation: Incrementality in marketing.
      • Here’s how the calculation works out : (2.1% – 1.5%) / 1.5% = 40%

    The Facebook ads had a positive 40% incremental lift in conversions during the sale.

    Incrementality testing isn’t a one-and-done process, though.

    While this first test is a great sign for the marketing manager, it doesn’t mean they should immediately throw all their money into Facebook ads.

    They should continue conducting tests to verify the initial test.

    Use Matomo to track incrementality today

    Incrementality can give you insights into exactly what’s working in your marketing (and what’s not) so you can design proven strategies to grow your business.

    If you want more help tracking your marketing efforts, try Matomo today.

    Our web analytics and behaviour analytics platform gives you firsthand data on your website visitors you can use to craft effective marketing strategies.

    Matomo provides 100% accurate data. Unlike other major web analytics platforms, we don’t do data sampling. What you see is what’s really going on in your website. That way, you can make more informed decisions for better results.

    At Matomo, we take privacy very seriously and include several advanced privacy protections to ensure you are in full control.

    As a fully compliant web analytics solution, we’re fully compliant with some of the world’s strictest privacy regulations like GDPR. With Matomo, you get peace of mind knowing you can make data-driven decisions while also being compliant. 

    If you’re ready to launch a data-driven marketing strategy today and grow your business, get started with our 21-day free trial now. No credit card required.