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• RaspberryPi HQ camera not working with FFMPEG [closed]

  12 mars 2024, par GeeTee

  I just want to prefix this by saying I'm still quite fresh to linux so please bare with me as I don't always know exactly what I'm looking at.

  


  Hardware : Raspberry Pi 5 4GB / Pi HQ camera (connected with adapter cable)
OS : Debain V12 (bookworm)
FFMPEG : ffmpeg version 5.1.4-0+rpt3+deb12u1
I2C = Enabled
X / Wayland : Wayland (had to use this for VNC)

  


  I know the camera works as : when I use rpicam-vid -t 0 I have a working preview without issue (albeit slightly stuttery)

  


  When I try to enter ffmpeg -f v4l2 -i /dev/video0 I get the following :
(with the goal of having some video in a preview window)

  


  [video4linux2,v4l2 @ 0x5555a0811a20] ioctl(VIDIOC_G_PARM): Inappropriate ioctl for device
[video4linux2,v4l2 @ 0x5555a0811a20] Time per frame unknown
[video4linux2,v4l2 @ 0x5555a0811a20] ioctl(VIDIOC_STREAMON): Invalid argument
/dev/video0: Invalid argument


  


  I have also tried ffplay -f v4l2 -i /dev/video0 and get the same error as above.

  


  Following other forums I've tried (I'm not sure this is all necessary but to cover all bases, and save time) :

  


  Prompt : ffmpeg -sources device /dev/video0
Out : none (as in libpostproc    56.  6.100 / 56.  6.100 is the last line)

  


  Promt : v4l2-ctl --list-devices
Out :

  


  pispbe (platform:1000880000.pisp_be):
    /dev/video20
    /dev/video21
    /dev/video22
    /dev/video23
    /dev/video24
    /dev/video25
    /dev/video26
    /dev/video27
    /dev/video28
    /dev/video29
    /dev/video30
    /dev/video31
    /dev/video32
    /dev/video33
    /dev/video34
    /dev/video35
    /dev/video36
    /dev/video37
    /dev/media1
    /dev/media2

rp1-cfe (platform:1f00110000.csi):
    /dev/video0
    /dev/video1
    /dev/video2
    /dev/video3
    /dev/video4
    /dev/video5
    /dev/video6
    /dev/video7
    /dev/media0

rpivid (platform:rpivid):
    /dev/video19
    /dev/media3


  


  (seems to me rp1-cfe is what I want / need ? which is good that it shows up ?)

  


  Prompt : strace cat /dev/video0
Out :

  


  execve("/usr/bin/cat", ["cat", "/dev/video0"], 0x7fffc4c80c38 /* 41 vars */) = 0
brk(NULL)                               = 0x55567d41c000
faccessat(AT_FDCWD, "/etc/ld.so.preload", R_OK) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/etc/ld.so.cache", O_RDONLY|O_CLOEXEC) = 3
newfstatat(3, "", {st_mode=S_IFREG|0644, st_size=80471, ...}, AT_EMPTY_PATH) = 0
mmap(NULL, 80471, PROT_READ, MAP_PRIVATE, 3, 0) = 0x7fff59df4000
close(3)                                = 0
openat(AT_FDCWD, "/lib/aarch64-linux-gnu/libc.so.6", O_RDONLY|O_CLOEXEC) = 3
read(3, "\177ELF\2\1\1\3\0\0\0\0\0\0\0\0\3\0\267\0\1\0\0\0py\2\0\0\0\0\0"..., 832) = 832
newfstatat(3, "", {st_mode=S_IFREG|0755, st_size=1651472, ...}, AT_EMPTY_PATH) = 0
mmap(NULL, 1826976, PROT_NONE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x7fff59c34000
mmap(0x7fff59c40000, 1761440, PROT_READ|PROT_EXEC, MAP_PRIVATE|MAP_FIXED|MAP_DENYWRITE, 3, 0) = 0x7fff59c40000
munmap(0x7fff59c34000, 49152)           = 0
munmap(0x7fff59df0000, 8352)            = 0
mprotect(0x7fff59dc8000, 81920, PROT_NONE) = 0
mmap(0x7fff59ddc000, 32768, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_FIXED|MAP_DENYWRITE, 3, 0x18c000) = 0x7fff59ddc000
mmap(0x7fff59de4000, 41120, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_FIXED|MAP_ANONYMOUS, -1, 0) = 0x7fff59de4000
close(3)                                = 0
set_tid_address(0x7fff59e4b010)         = 1526021
set_robust_list(0x7fff59e4b020, 24)     = 0
rseq(0x7fff59e4b660, 0x20, 0, 0xd428bc00) = 0
mprotect(0x7fff59ddc000, 16384, PROT_READ) = 0
mprotect(0x5556410fc000, 16384, PROT_READ) = 0
mprotect(0x7fff59e44000, 16384, PROT_READ) = 0
prlimit64(0, RLIMIT_STACK, NULL, {rlim_cur=8192*1024, rlim_max=RLIM64_INFINITY}) = 0
munmap(0x7fff59df4000, 80471)           = 0
getrandom("\x5c\x96\x77\x22\xd2\x25\xd3\x23", 8, GRND_NONBLOCK) = 8
brk(NULL)                               = 0x55567d41c000
brk(0x55567d440000)                     = 0x55567d440000
openat(AT_FDCWD, "/usr/lib/locale/locale-archive", O_RDONLY|O_CLOEXEC) = 3
newfstatat(3, "", {st_mode=S_IFREG|0644, st_size=3048976, ...}, AT_EMPTY_PATH) = 0
mmap(NULL, 3048976, PROT_READ, MAP_PRIVATE, 3, 0) = 0x7fff59954000
close(3)                                = 0
newfstatat(1, "", {st_mode=S_IFCHR|0620, st_rdev=makedev(0x88, 0x1), ...}, AT_EMPTY_PATH) = 0
openat(AT_FDCWD, "/dev/video0", O_RDONLY) = 3
newfstatat(3, "", {st_mode=S_IFCHR|0660, st_rdev=makedev(0x51, 0x13), ...}, AT_EMPTY_PATH) = 0
fadvise64(3, 0, 0, POSIX_FADV_SEQUENTIAL) = 0
mmap(NULL, 163840, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x7fff5992c000
read(3, 0x7fff59930000, 131072)         = -1 EINVAL (Invalid argument)
write(2, "cat: ", 5cat: )                    = 5
write(2, "/dev/video0", 11/dev/video0)             = 11
openat(AT_FDCWD, "/usr/share/locale/locale.alias", O_RDONLY|O_CLOEXEC) = 4
newfstatat(4, "", {st_mode=S_IFREG|0644, st_size=2996, ...}, AT_EMPTY_PATH) = 0
read(4, "# Locale name alias data base.\n#"..., 4096) = 2996
read(4, "", 4096)                       = 0
close(4)                                = 0
openat(AT_FDCWD, "/usr/share/locale/en_GB.UTF-8/LC_MESSAGES/libc.mo", O_RDONLY) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/share/locale/en_GB.utf8/LC_MESSAGES/libc.mo", O_RDONLY) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/share/locale/en_GB/LC_MESSAGES/libc.mo", O_RDONLY) = 4
newfstatat(4, "", {st_mode=S_IFREG|0644, st_size=1433, ...}, AT_EMPTY_PATH) = 0
mmap(NULL, 1433, PROT_READ, MAP_PRIVATE, 4, 0) = 0x7fff59e34000
close(4)                                = 0
openat(AT_FDCWD, "/usr/share/locale/en.UTF-8/LC_MESSAGES/libc.mo", O_RDONLY) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/share/locale/en.utf8/LC_MESSAGES/libc.mo", O_RDONLY) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/share/locale/en/LC_MESSAGES/libc.mo", O_RDONLY) = -1 ENOENT (No such file or directory)
write(2, ": Invalid argument", 18: Invalid argument)      = 18
write(2, "\n", 1
)                       = 1
munmap(0x7fff5992c000, 163840)          = 0
close(3)                                = 0
close(1)                                = 0
close(2)                                = 0
exit_group(1)                           = ?
+++ exited with 1 +++


  


  (no idea what I'm reading here and if it's good or bad so I included it all)

  


  Prompt : ffmpeg -f v4l2 -list_formats all -i /dev/video0
Out :

  


  [video4linux2,v4l2 @ 0x55561cd9da20] Raw       :     yuyv422 :           YUYV 4:2:2 : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       :     uyvy422 :           UYVY 4:2:2 : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported :           YVYU 4:2:2 : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported :           VYUY 4:2:2 : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       :    rgb565le :     16-bit RGB 5-6-5 : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       :    rgb565be :  16-bit RGB 5-6-5 BE : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       :    rgb555le : 16-bit A/XRGB 1-5-5-5 : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       :    rgb555be : 16-bit A/XRGB 1-5-5-5 BE : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       :       rgb24 :     24-bit RGB 8-8-8 : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       :       bgr24 :     24-bit BGR 8-8-8 : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       :        0rgb : 32-bit A/XRGB 8-8-8-8 : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : bayer_bggr8 : 8-bit Bayer BGBG/GRGR : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : bayer_gbrg8 : 8-bit Bayer GBGB/RGRG : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : bayer_grbg8 : 8-bit Bayer GRGR/BGBG : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : bayer_rggb8 : 8-bit Bayer RGRG/GBGB : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 10-bit Bayer BGBG/GRGR Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 10-bit Bayer GBGB/RGRG Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 10-bit Bayer GRGR/BGBG Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 10-bit Bayer RGRG/GBGB Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 12-bit Bayer BGBG/GRGR Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 12-bit Bayer GBGB/RGRG Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 12-bit Bayer GRGR/BGBG Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 12-bit Bayer RGRG/GBGB Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 14-bit Bayer BGBG/GRGR Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 14-bit Bayer GBGB/RGRG Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 14-bit Bayer GRGR/BGBG Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 14-bit Bayer RGRG/GBGB Packed : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 16-bit Bayer BGBG/GRGR : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 16-bit Bayer GBGB/RGRG : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 16-bit Bayer GRGR/BGBG : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 16-bit Bayer RGRG/GBGB : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Compressed: Unsupported : PiSP Bayer Compressed Format : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Compressed: Unsupported : PiSP Bayer Compressed Format : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Compressed: Unsupported : PiSP Bayer Compressed Format : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Compressed: Unsupported : PiSP Bayer Compressed Format : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       :        gray :      8-bit Greyscale : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 10-bit Greyscale (MIPI Packed) : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 12-bit Greyscale (MIPI Packed) : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       : Unsupported : 14-bit Greyscale (MIPI Packed) : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Raw       :    gray16le :     16-bit Greyscale : {16-16384, 2}x{16-16384, 1}
[video4linux2,v4l2 @ 0x55561cd9da20] Compressed: Unsupported : PiSP Bayer Compressed Format : {16-16384, 2}x{16-16384, 1}
/dev/video0: Immediate exit requested


  


  Not sure why so many of these are unsupported, I saw a video on YouTube with the same camera and older Pi and he did not have so many unsupported.

  


  Also, I ran the config file in the ffmpeg directory and I think it generated some additional files (wasn't working before either) are these normal ? (ffmpeg $ ls)

  


  Changelog        COPYING.LGPLv2.1  INSTALL.md   libpostproc    presets
compat           COPYING.LGPLv3    libavcodec   libswresample  README.md
configure        CREDITS           libavdevice  libswscale     RELEASE
CONTRIBUTING.md  doc               libavfilter  LICENSE.md     tests
COPYING.GPLv2    ffbuild           libavformat  MAINTAINERS    tools
COPYING.GPLv3    fftools           libavutil    Makefile


  


  A side question : How do I enable and disable libraries ? I tried entering —enable-pulse for example (with and without spaces and prefixed by ffmpeg) but get an error along the lines of unrecognised option or command not found. (I've tried google but as mentioned prior, I'm a bit lost)

  


  Thanks in advance.

  


• CRO Testing : The 6-Steps for Maximising Conversion Rates

  10 mars 2024, par Erin

  It’s a nightmare every marketing manager faces. Traffic is soaring after you’ve launched new digital marketing campaigns, but conversions have barely moved.

  Sound familiar ?

  The good news is you’re not alone — loads of marketing managers struggle to get potential customers to purchase. The better news is that you can test dozens of strategies to turn around your site’s fortunes. 

  Conversion rate optimisation testing (CRO testing for short) is the name for this kind of experimentation — and it can send conversion rates and revenue soaring.

  In this article, we’ll explain CRO testing and how you can start doing it today using Matomo. 

  What is CRO Testing ? 

  CRO testing is optimising your site’s conversion funnel using a series of experiments designed to improve conversion rates.

  A CRO test can take several forms, but it usually involves changing one or more elements of your landing page. It looks something like this :

  1. You hypothesise what you expect to happen.
  2. You then run an A/B test using a dedicated CRO platform or tool.
  3. This tool will divide your site’s traffic, sending one segment to one variation and the other segment to another.
  4. The CRO tool will measure conversions, track statistical significance, and declare one variation the winner. 

  A CRO tool isn’t the only software you can use to gather data when running tests. There are several other valuable data sources, including :

  • A web analytics platform : to identify issues with your website
  • User surveys : to find out what your target audience thinks about your site
  • Heatmaps : to learn where users focus their attention
  • Session recordings : to discover how visitors browse your site

  Use as many of these features, tools, and methods as you can when brainstorming hypotheses and measuring results. After all, your CRO test is only as good as your data.

  On that note, we need to mention the importance of data accuracy when researching issues with your website and running CRO tests. If you trust a platform like Google Analytics that uses data sampling (where only a subset of data is analysed), then there’s a risk you make business decisions based on inaccurate reports.

  In practice, that could see you overestimate the effectiveness of a landing page, potentially wasting thousands in ad spend on poorly converting pages. 

  That’s why over a million websites rely on Matomo as their web analytics solution—it doesn’t sample data, providing 100% accurate website traffic insights you can trust to make informed decisions.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Types of CRO Testing 

  There are three core types of CRO tests :

  A/B testing

  A/B testing, or split testing, is when you test two versions of the same page against each other. Usually, the two pages have only one difference, such as a new headline or a different CTA. 

  

  In the test above, for example, we test what happens if we remove one of the affiliate links from a page. We hypothesise that conversions won’t change because these links aren’t effective.

  A/B/n testing

  A/B/n testing is when you test multiple variations of the same element on the same page. 

  Rather than just testing one headline against another, for example, you test multiple different headlines at once.

  

  In the test above in Matomo, we’re testing a website’s original header against a wider and smaller version. It turns out the wider header converts significantly better. 

  Multivariate testing

  In a multivariate CRO test, you test multiple different elements at the same time. That could mean testing combining a different headline, CTA button, and image. 

  Multivariate testing can save time because you test multiple elements at once and find the best combination of elements. But you’ll usually need a lot of traffic to find a statistically significant result.

  Why is CRO testing important ?

  Who doesn’t want more conversions, right ? Improving your conversion rate is the core benefit of running a CRO test, but there are a couple of other reasons you should do it, too :

  

  Improve conversion rates

  How well does your website convert visitors ? The average conversion rate of a typical website is 2.35%, but better-performing websites have significantly higher conversion rates. The top 25% of websites across all industries convert at a rate of 5.31% or higher.

  CRO testing is the best way to improve your site’s conversion rate by tweaking elements of your website and implementing the best results. And because it’s based on data, not your intuition, you’re likely to identify changes that move the needle. 

  Optimise the user experience

  CRO tests are also a great way to improve your site’s user experience. The process of CRO testing forces you to understand how users navigate your website using heatmaps and session recordings and fix the issues they face. 

  You could simplify your form fields to make them easier to fill in, for example, or make your pages easier to navigate. In both cases, your actions will also increase conversion rates.

  Decrease acquisition costs

  Improving your conversion rate using CRO testing will usually mean a decrease in customer acquisition costs and other conversion metrics. 

  After all, if the cost of your PPC ads stays the same but you convert more traffic, then each new customer will cost less to acquire.

  How to do CRO testing in 6 steps 

  Ready to get your hands dirty ? Follow these six steps to set up your first CRO test :

  Have a clear goal

  Don’t jump straight into testing. You need to be clear about what you want to achieve ; otherwise, you risk wasting time on irrelevant experiments. 

  If you’re unsure what to focus on, look back through your web analytics data and other tools like heatmaps, form analytics, and session recordings to get a feel for some of your site’s biggest conversion roadblocks. 

  Maybe there’s a page with a much lower conversion rate, for example — or a form that most users fail to complete. 

  If it’s the former, then your goal could be to increase the conversion rate of this specific landing page by 25%, bringing it in line with your site’s average. 

  

  Make sure your new conversion goal is set up properly in your website analytics platform, too. This will ensure you’re tracking conversions accurately. 

  Set a hypothesis

  Now you’ve got a goal, it’s time to create a hypothesis. Based on your available research, a hypothesis is an assumption you make about your conversion rate optimisation test.

  A heatmap of your poorly converting landing page may show that users aren’t focusing on your CTA button because it’s hidden below the fold. 

  You could hypothesise that by placing the CTA button directly under your headline above the fold, your conversion rate should increase. 

  Whatever your goal, you can use the following template to write a hypothesis :

  If we [make this specific change], then [this specific outcome] will occur because [reason].

  Design your test elements

  Most marketing managers won’t be able to run CRO tests independently. A team of talented experts must create the assets you need for a successful experimentation. This includes designers, copywriters, and web developers. 

  Don’t just have them create one new element at a time. Accelerate the process by having your team create dozens of designs simultaneously. That way, you can run a new CRO test as soon as your current test has finished. 

  Create and launch the test

  It’s time to launch your test. Use a CRO tool to automate building your test and tracking results. 

  With Matomo’s A/B Testing feature, it’s as easy as giving your test a name, writing a hypothesis and description, and uploading the URLs of your page variants.

  

  Matomo handles everything else, giving you a detailed breakdown at the end of the test with the winning variant. 

  Try Matomo for Free

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

  Start for free

  No credit card required

  Analyse the results

  You can only review the results of your CRO test once it has reached statistical significance — which means the observed outcome isn’t the result of chance.

  In the same way you wouldn’t say a die is unbiased after three rolls, you need thousands of visitors to see your landing pages and take action before deciding which is better. 

  Luckily, most CRO testing platforms, including Matomo, will highlight when a test reaches statistical significance. That means you only need to look at the result to see if your hypothesis is correct. 

  Implement and repeat

  Was your test a success ? Great, you can implement the results and test a new element. 

  Yep, that’s right. There’s no time to rest on your laurels. Continuous CRO testing is necessary to squeeze every conversion possible from your website. Just like fashion trends, website effectiveness changes over time. What works today might not work tomorrow, making ongoing CRO testing beneficial and necessary.

  That’s why it’s a good idea to choose a CRO testing platform like Matomo with no data limits.

  Try Matomo for Free

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

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  CRO testing examples you can run today 

  There’s no shortage of CRO tests you can run. Here are some experiments to get started with :

  Change your CTA design and copy

  Calls to action (CTAs) are the best elements to optimise during your first CRO test. You can change many things about them ; even the smallest optimisation can have a huge impact. 

  Just take a look at the image below to see how diverse your CTAs could be :

  

  Changing your CTA’s copy is a great place to start, especially if you have generic instructions like “Apply Now.”

  Try a more specific instruction like “Download your free trial” or “Buy now to get 30% off.” Or test benefit-led instructions like “Reduce your ad spend today” or “Take back control of your data.”

  Changing the colour of your CTAs can also yield more conversions. Bright colours are always a good bet. Just make sure your button stands out from the rest of your page. 

  Move the CTA button placement

  The placement of your CTA can be just as important as its copy or colour. If it’s down at the bottom of your page, there’s a good chance most of your visitors will miss it. 

  Try moving it above the fold to see if that makes a difference. Then, test multiple CTA buttons as opposed to just one. 

  Heatmaps and session recordings can identify whether this test is worthwhile. If users rarely focus on your CTA or just don’t scroll far enough to find it, then it’s a good bet you could see an uptick in conversions by moving it. 

  Try different headlines

  Your website’s headlines are another great place to start CRO testing. These are usually the first (and sometimes only) things visitors read, so optimising them as much as possible makes sense. 

  There are entire books written about creating persuasive headlines, but start with one of the following tactics :

  • Include a benefit
    • “Achieve radiant skin—discover the secret !”
  • Add numbers
    • “3 foolproof methods for saving money on your next vacation”
  • Using negative words instead of positive ones
    • “Avoid these 7 mistakes to unlock your potential for personal growth”
  • Shortening or lengthening your headline
    • Shortened : “Crush your fitness goals : Expert tips for success”
    • Lengthened : “Embark on your fitness journey : Learn from experts with proven tips to crush your wellness goals”

  Add more trust signals

  Adding trust signals to your website, such as brand logos, customer reviews, and security badges, can increase your conversion rate.

  We use it at Matomo by adding the logos of well-known clients like the United Nations and Amnesty International underneath our CTAs.

  

  It’s incredibly effective, too. Research by Edelman finds that trust is among the top three most important buying decision factors, above brand likeability.

  Start CRO testing with Matomo

  CRO testing is a data-backed method to improve your site’s conversion rate, making it more user-friendly and decreasing customer acquisition costs. Even a small improvement will be worth the cost of the tools and your time. 

  Fortunately, there’s no need to allocate hundreds of dollars monthly for multiple specialised testing tools. With Matomo, you get a comprehensive platform offering web analytics, user behaviour insights, and CRO testing – all conveniently bundled into one solution. Matomo’s pricing starts from just $19 per month, making it accessible to businesses of all sizes.

  Plus, rest assured knowing that you are GDPR compliant and the data provided is 100% accurate, ethically empowering you to make informed decisions with confidence.

  Take the first step on your CRO testing journey by trying Matomo free for 21 days ; no credit card required.

  Try Matomo for Free

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• Attribution Tracking (What It Is and How It Works)

  23 février 2024, par Erin

  Facebook, TikTok, Google, email, display ads — which one is best to grow your business ? There’s one proven way to figure it out : attribution tracking.

  Marketing attribution allows you to see which channels are producing the best results for your marketing campaigns.

  In this guide, we’ll show you what attribution tracking is, why it’s important and how you can leverage it to accelerate your marketing success.

  What is attribution tracking ?

  By 2026, the global digital marketing industry is projected to reach $786.2 billion.

  With nearly three-quarters of a trillion U.S. dollars being poured into digital marketing every year, there’s no doubt it dominates traditional marketing.

  The question is, though, how do you know which digital channels to use ?

  By measuring your marketing efforts with attribution tracking.

  

  So, what is attribution tracking ?

  Attribution tracking is where you use software to keep track of different channels and campaign efforts to determine which channel you should attribute conversion to.

  In other words, you can (and should) use attribution tracking to analyse which channels are pushing the needle and which ones aren’t.

  By tracking your marketing efforts, you’ll be able to accurately measure the scale of impact each of your channels, campaigns and touchpoints have on a customer’s purchasing decision.

  If you don’t track your attribution, you’ll end up blindly pouring time, money, and effort into activities that may or may not be helpful.

  Attribution tracking simply gives you insight into what you’re doing right as a marketer — and what you’re doing wrong.

  By understanding which efforts and channels are driving conversions and revenue, you’ll be able to properly allocate resources toward winning channels to double down on growth.

  Matomo lets you track attribution across various channels. Whether you’re looking to track your conversions through organic, referral websites, campaigns, direct traffic, or social media, you can see all your conversions in one place.

  Try Matomo for Free

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

  Start for free

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  Why attribution tracking is important

  Attribution tracking is crucial to succeed with your marketing since it shows you your most valuable channels.

  It takes the guesswork out of your efforts.

  You don’t need to scratch your head wondering what made your campaigns a success (or a failure).

  While most tools show you last click attribution by default, using attribution tracking, or marketing attribution, you can track revenue and conversions for each touchpoint.

  For example, a Facebook ad might have no led to a conversion immediately. But, maybe the visitor returned to your website two weeks later through your email campaign. Attribution tracking will give credit over longer periods of time to see the bigger picture of how your marketing channels are impacting your overall performance.

  Here are five reasons you need to be using attribution tracking in your business today :

  

  1. Measure channel performance

  The most obvious way attribution tracking helps is to show you how well each channel performs.

  When you’re using a variety of marketing channels to reach your audience, you have to know what’s actually doing well (and what’s not).

  This means having clarity on the performance of your :

  • Emails
  • Google Ads
  • Facebook Ads
  • Social media marketing
  • Search engine optimisation (SEO)
  • And more

  Attribution tracking allows you to measure each channel’s ROI and identify how much each channel impacted your campaigns.

  It gives you a more accurate picture of the performance of each channel and each campaign.

  With it, you can easily break down your channels by how much they drove sales, conversions, signups, or other actions.

  With this information, you can then understand where to further allocate your resources to fuel growth.

  2. See campaign performance over longer periods of time

  When you start tracking your channel performance with attribution tracking, you’ll gain new insights into how well your channels and campaigns are performing.

  The best part — you don’t just get to see recent performance.

  You get to track your campaign results over weeks or months.

  For example, if someone found you through Google by searching a question that your blog had an answer to, but they didn’t convert, your traditional tracking strategy would discount SEO.

  But, if that same person clicked a TikTok ad you placed three weeks later, came back, and converted — SEO would receive some attribution on the conversion.

  Using an attribution tracking tool like Matomo can help paint a holistic view of how your marketing is really doing from channel to channel over the long run.

  Try Matomo for Free

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

  Start for free

  No credit card required

  3. Increase revenue

  Attribution tracking has one incredible benefit for marketers : optimised marketing spend.

  When you begin looking at how well your campaigns and your channels are performing, you’ll start to see what’s working.

  Attribution tracking gives you clarity into the performance of campaigns since it’s not just looking at the first time someone clicks through to your site. It’s looking at every touchpoint a customer made along the way to a conversion.

  By understanding what channels are most effective, you can pour more resources like time, money and labour into those effective channels.

  By doubling down on the winning channels, you’ll be able to grow like never before.

  Rather than trying to “diversify” your marketing efforts, lean into what’s working.

  This is one of the key strategies of an effective marketer to maximise your campaign returns and experience long-term success in terms of revenue.

  4. Improve profit margins

  The final benefit to attribution tracking is simple : you’ll earn more profit.

  Think about it this way : let’s say you’re putting 50% of your marketing spend into Facebook ads and 50% of your spend into email marketing.

  You do this for one year, allocating $500,000 to Facebook and $500,000 to email.

  Then, you start tracking attribution.

  You find that your Facebook ads are generating $900,000 in revenue. 

  That’s a 1,800% return on your investment.

  Not bad, right ?

  Well, after tracking your attribution, you see what your email revenue is.

  In the past year, you generated $1.7 million in email revenue.

  That’s a 3,400% return on your investment (close to the average return of email marketing across all industries).

  In this scenario, you can see that you’re getting nearly twice as much of a return on your marketing spend with email.

  So, the following year, you decide to go for a 75/25 split.

  Instead of putting $500,000 into both email and Facebook ads and email, you put $750,000 into email and $250,000 into Facebook ads.

  You’re still diversifying, but you’re doubling down on what’s working best.

  The result is that you’ll be able to get more revenue by investing the same amount of money, leaving you with higher profit margins.

  Different types of marketing attribution tracking

  There are several types of attribution tracking models in marketing.

  Depending on your goals, your business and your preferred method, there are a variety of types of attribution tracking you can use.

  Here are the six main types of attribution tracking :

  

  1. Last interaction

  Last interaction attribution model is also called “last touch.”

  It’s one of the most common types of attribution. The way it works is to give 100% of the credit to the final channel a customer interacted with before they converted into a customer.

  This could be through a paid ad, direct traffic, or organic search.

  One potential drawback of last interaction is that it doesn’t factor in other channels that may have assisted in the conversion. However, this model can work really well depending on the business.

  2. First interaction

  This is the opposite of the previous model.

  First interaction, or “first touch,” is all about the first interaction a customer has with your brand.

  It gives 100% of the credit to the channel (i.e. a link clicked from a social media post). And it doesn’t report or attribute anything else to another channel that someone may have interacted with in your marketing mix.

  For example, it won’t attribute the conversion or revenue if the visitor then clicked on an Instagram ad and converted. All credit would be given to the first touch which in this case would be the social media post. 

  The first interaction is a good model to use at the top of your funnel to help establish which channels are bringing leads in from outside your audience.

  3. Last non-direct

  Another model is called the last non-direct attribution model. 

  This model seeks to exclude direct traffic and assigns 100% credit for a conversion to the final channel a customer interacted with before becoming a customer, excluding clicks from direct traffic.

  For instance, if someone first comes to your website from an emai campaignl, and then, a week later, directly visits and buys a product, the email campaign gets all the credit for the sale.

  This attribution model tells a bit more about the whole sales process, shedding some more light on what other channels may have influenced the purchase decision.

  4. Linear

  Another common attribution model is linear.

  This model distributes completely equal credit across every single touchpoint (that’s tracked). 

  Imagine someone comes to your website in different ways : first, they find it through a Google search, then they click a link in an email from your campaign the next day, followed by visiting from a Facebook post a few days later, and finally, a week later, they come from a TikTok ad. 

  Here’s how the attribution is divided among these sources :

  • 25% Organic
  • 25% Email
  • 25% Facebook
  • 25% TikTok ad

  This attirubtion model provides a balanced perspective on the contribution of various sources to a user’s journey on your website.

  5. Position-based

  Position-based attribution is when you give 40% credit to both the first and last touchpoints and 20% credit is spread between the touchpoints in between.

  This model is preferred if you want to identify the initial touchpoint that kickstarted a conversion journey and the final touchpoint that sealed the deal.

  The downside is that you don’t gain much insight into the middle of the customer journey, which can make it hard to make effective decisions.

  For example, someone may have been interacting with your email newsletter for seven weeks, which allowed them to be nurtured and build a relationship with you.

  But that relationship and trust-building effort will be overlooked by the blog post that brought them in and the social media ad that eventually converted them.

  6. Time decay

  The final attribution model is called time decay attribution.

  This is all about giving credit based on the timing of the interactions someone had with your brand.

  For example, the touchpoints that just preceded the sale get the highest score, while the first touchpoints get the lowest score.

  For example, let’s use that scenario from above with the linear model :

  • 25% SEO
  • 25% Email
  • 25% Facebook ad
  • 25% Organic TikTok

  But, instead of splitting credit by 25% to each channel, you weigh the ones closer to the sale with more credit.

  Instead, time decay may look at these same channels like this :

  • 5% SEO (6 weeks ago)
  • 20% Email (3 weeks ago)
  • 30% Facebook ad (1 week ago)
  • 45% Organic TikTok (2 days ago)

  One downside is that it underestimates brand awareness campaigns. And, if you have longer sales cycles, it also isn’t the most accurate, as mid-stage nurturing and relationship building are underlooked. 

  Leverage Matomo : A marketing attribution tool

  Attribution tracking is a crucial part of leading an effective marketing strategy.

  But it’s impossible to do this without the right tools.

  A marketing attribution tool can give you insights into your best-performing channels automatically. 

  

  One of the best marketing attribution tools available is Matomo, a web analytics tool that helps you understand what’s going on with your website and different channels in one easy-to-use dashboard.

  With Matomo, you get marketing attribution as a plug-in or within Matomo On-Premise or for free in Matomo Cloud.

  The best part is it’s all done with crystal-clear data. Matomo gives you 100% accurate data since it doesn’t use data sampling on any plans like Google Analytics.

  To start tracking attribution today, try Matomo’s 21-day free trial. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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