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  • Multilang : améliorer l’interface pour les blocs multilingues

    18 février 2011, par

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    5 mars 2010, par

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    8 février 2011, par

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  • What is last click attribution ? A beginner’s guide

    10 mars 2024, par Erin

    Imagine you just finished a successful marketing campaign. You reached new highs in campaign revenue. Your conversion was higher than ever. And you did it without dramatically increasing your marketing budget.

    So, you start planning your next campaign with a bigger budget.

    But what do you do ? Where do you invest the extra money ?

    You used several marketing tactics and channels in the last campaign. To solve this problem, you need to track marketing attribution — where you give conversion credit to a channel (or channels) that acted as a touchpoint along the buyer’s journey.

    One of the most popular attribution models is last click attribution.

    In this article, we’ll break down what last click attribution is, its advantages and disadvantages, and examples of how you can use it to gain insights into the marketing strategies driving your growth.

    What is last click attribution ?

    Last click, or last interaction, is a marketing attribution model that seeks to give all credit for a conversion to the final touchpoint in the buyer’s journey. It assumes the customer’s last interaction with your brand (before the sale) was the most influential marketing channel for the conversion decision.

    What is last click attribution?

    Example of last click attribution

    Let’s say a woman named Jill stumbles across a fitness equipment website through an Instagram ad. She explores the website, looking at a few fitness bands and equipment, but she doesn’t buy anything.

    A few days later, Jill was doing a workout but wished she had equipment to use.

    So, she Googles the name of the company she checked out earlier to take a look at the fitness bands it offers. She’s not sure which one to get, but she signs up for a 10% discount by entering her email.

    A few days later, she sees an ad on Facebook and visits the site but exits before purchasing. 

    The next day, Jill gets an email from the store stating that her discount code is expiring. She clicks on the link, plugs in the discount code, and buys a fitness band for $49.99.

    Under the last click attribution model, the fitness company would attribute full credit for the sale to their email campaign while ignoring all other touchpoints (the Instagram ad, Jill’s organic Google search, and the Facebook ad).

    3 advantages of last click attribution

    Last click attribution is one of the most popular methods to credit a conversion. Here are the primary advantages of using it to measure your marketing efforts :

    Advantages of Last Click Attribution

    1. Easiest attribution method for beginners

    If something’s too complicated, many people simply won’t touch it.

    So, when you start diving into attribution, you might want to keep it simple. Fortunately, last click attribution is a wonderful method for beginner marketers to try out. And when you first begin tracking your marketing efforts, it’s one of the easiest methods to grasp. 

    2. It can have more impact on revenue

    Attribution and conversions go hand in hand. But conversions aren’t just about making a sale or generating more revenue. We often need to track the conversions that take place before a sale.

    This could include gaining a new follower on Instagram or capturing an email subscriber with a new lead magnet.

    If you’re trying to attribute why someone converted into a follower or lead, you may want to ditch last click for something else.

    But when you’re looking strictly at revenue-generating conversions, last click can be one of the most impactful methods for giving credit to a conversion.

    3. It helps you understand bottom-of-funnel conversions

    If SEO is your focus, chances are pretty good that you aren’t looking for a direct sale right out of the gate. You likely want to build your authority, inform and educate your audience, and then maybe turn them into a lead.

    However, when your primary focus isn’t generating traffic or leads but turning your leads into customers, then you’re focused on the bottom of your sales funnel.

    Last click can be helpful to use in bottom-of-funnel (BoFu) conversions since it often means following a paid ad or sales email that allows you to convert your warm audience member.

    If you’re strictly after revenue, you may not need to pay as much attention to the person who reads your latest blog post. After they read the article, they may have seen a social media post. And then, maybe they saw your email with a discount to buy now — which converted them into a paying customer.

    3 challenges of last click attribution

    Last click attribution is a simple way to start analysing the channels that impact your conversions. But it’s not perfect.

    Here are a few challenges of last click attribution you should keep in mind :

    Challenges of last click attribution.

    1. It ignores all other touchpoints

    Last click attribution is a single-touch attribution model. This type of model declares that a single channel gets 100% of the credit for a sale.

    But this can overlook impactful contributions from other channels.

    Multi-touch attribution seeks to give credit to multiple channels for each conversion. This is a more holistic approach.

    2. It fragments the customer journey

    Most customers need a few touchpoints before they’ll make a purchase.

    Maybe it’s reading a blog post via Google, checking out a social media post on Instagram, and receiving a nurture email.

    If you look only at the last touchpoint before a sale, then you ignore the impact of the other channels. This leads to a fragmented customer journey. 

    Imagine this : You tell your marketing leaders that Facebook ads are responsible for your success because they were the last touch for 65% of conversions. So, you pour your entire budget into Facebook ads.

    What happens ?

    Your sales drop by 60% in one month. This happens because you ignored the traffic you were generating from SEO blog posts that led to that conversion — the nurturing that took place in email marketing.

    3. Say goodbye to brand awareness marketing

    Without a brand, you can’t have a sustainable business.

    Some marketing activities, like brand awareness campaigns, are meant to fuel brand awareness to build a business that lasts for years.

    But if you’re going to use last click attribution to measure the effectiveness of your marketing efforts, then you’re going to diminish the impact of brand awareness.

    Your brand, as a whole, has the ability to generate multiples of your current revenue by simply reaching more people and creating unique brand experiences with new audiences.

    Last click attribution can’t easily measure brand awareness activities, which means their importance is often ignored.

    Last click attribution vs. other attribution models

    Last click attribution is just one type of attribution model. Here are five other common marketing attribution models you might want to consider :

    Image of six different attribution models

    First interaction

    We’ve already touched on last click interaction as a marketing attribution model. But one of the most common models does the opposite.

    First interaction, or first touch, gives full credit to the first channel that brought a lead in. 

    First interaction is best used for top-of-funnel (ToFU) conversions, like user acquisition.

    Last non-direct interaction

    A similar model to last click attribution is one called last non-direct interaction. But one major difference is that it excludes all direct traffic from the calculation. Instead, it assigns full conversion credit to the channel that precedes it.

    For instance, let’s say you see someone comes to your website via a Facebook ad but doesn’t purchase. Then one week later, they go directly to your website through a bookmark they saved and they complete a purchase. Instead of giving attribution to the direct traffic touchpoint (entering your site through a saved bookmark), you attribute the conversion to the previous channel.

    In this case, the Facebook ad gets the credit.

    Last non-direct attribution is best used for BoFu conversions.

    Linear

    Another common attribution model is called linear attribution. Here, you split the credit for a conversion equally across every single touchpoint.

    This means if someone clicks on your blog post in Google, TikTok post, email, and a Facebook ad, then the credit for the conversion is equally split between each of these channels.

    This model is helpful for looking at both BoFu and ToFu activities.

    Time decay

    Time decay is an attribution model that more accurately credits conversions across different touchpoints. This means the closer a channel is to a conversion, the more weight is given to it.

    The time decay model assumes that the closer a channel is to a conversion, the greater that channel’s impact is on a sale.

    Position based

    Position-based, also called U-shaped attribution, is an interesting model that gives multiple channels credit for a conversion.

    But it doesn’t give equal credit to channels or weighted credit to the channels closest to the conversion.

    Instead, it gives the most credit to the first and last interactions.

    In other words, it emphasises the conversion of someone to a lead and, eventually, a customer.

    It gives the first and last interaction 40% of the credit for a conversion and then splits the remaining 20% across the other touchpoints in the customer journey.

    If you’re ever unsure about which attribution model to use, with Matomo, you can compare them to determine the one that best aligns with your goals and accurately reflects conversion paths. 

    Matomo comparing linear, first click, and last click attribution models in the marketing attribution dashboard

    In the above screenshot from Matomo, you can see how last-click compares to first-click and linear models to understand their respective impacts on conversions.

    Try Matomo for Free

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

    No credit card required

    Use Matomo to track last click attribution

    If you want to improve your marketing, you need to start tracking your efforts. Without marketing attribution, you will never be certain which marketing activities are pushing your business forward.

    Last click attribution is one of the most popular ways to get started with attribution since it, very simply, gives full credit to the last interaction for a conversion.

    If you want to start tracking last click attribution (or any other previously mentioned attribution model), sign up for Matomo’s 21-day free trial today. No credit card required.

  • Processing h264 video/audio stream

    1er mars 2024, par Dinamo

    I have separate audio and video streams from a camera that I'm trying to merge to a single file.

    


    Video processing

    


    I have JVT NAL sequence, H.264 video, main @ L 31 data, I had the frames separated and I appended (concat) the frames to one file.

    


    here is the ffprobe output of the data :

    


    ffprobe version 4.2.7-0ubuntu0.1 Copyright (c) 2007-2022 the FFmpeg developers
  built with gcc 9 (Ubuntu 9.4.0-1ubuntu1~20.04.1)
  configuration: --prefix=/usr --extra-version=0ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-nvenc --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared
  libavutil      56. 31.100 / 56. 31.100
  libavcodec     58. 54.100 / 58. 54.100
  libavformat    58. 29.100 / 58. 29.100
  libavdevice    58.  8.100 / 58.  8.100
  libavfilter     7. 57.100 /  7. 57.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  5.100 /  5.  5.100
  libswresample   3.  5.100 /  3.  5.100
  libpostproc    55.  5.100 / 55.  5.100
Input #0, h264, from 'frame_data.h264':
  Duration: N/A, bitrate: N/A
    Stream #0:0: Video: h264 (Main), yuvj420p(pc, bt709, progressive), 1280x720, 25 fps, 25 tbr, 1200k tbn, 50 tbc


    


    the file is being played on vlc, however the video is played like it is on fast forward (every 2 seconds of the video should be about 1 second)

    


    The video should run at 15fps (not sure about that because of the mentioned avi file)

    


    here is ffprobe output of working avi file that contain the video stream :

    


    Input #0, avi, from 't.avi':
  Duration: 00:03:29.00, start: 0.000000, bitrate: 1116 kb/s
    Stream #0:0: Video: h264 (Main) (H264 / 0x34363248), yuvj420p(pc, bt709, progressive), 1280x720, 849 kb/s, 30 fps, 15 tbr, 30 tbn, 60 tbc


    


    I tried this command ffmpeg -i frame_data.h264 -filter:v fps=15 test.h264 but the video is still playing like its on fast forward

    


    vlc data before changing fps to 15

    


    enter image description here
enter image description here

    


    vlc data after changing fps to 15

    


    enter image description here
enter image description here

    


    frames info (raw)

    


    [FRAME]
media_type=video
stream_index=0
key_frame=1
pkt_pts=N/A
pkt_pts_time=N/A
-> pkt_dts=N/A
-> pkt_dts_time=N/A
best_effort_timestamp=N/A
best_effort_timestamp_time=N/A
-> pkt_duration=48000
-> pkt_duration_time=0.040000
pkt_pos=1476573
pkt_size=57677
width=1280
height=720
pix_fmt=yuvj420p
sample_aspect_ratio=N/A
pict_type=I
coded_picture_number=189
display_picture_number=0
interlaced_frame=0
top_field_first=0
repeat_pict=0
color_range=pc
color_space=bt709
color_primaries=bt709
color_transfer=bt709
chroma_location=left
[/FRAME]
[FRAME]
media_type=video
stream_index=0
key_frame=0
pkt_pts=N/A
pkt_pts_time=N/A
-> pkt_dts=N/A
-> pkt_dts_time=N/A
best_effort_timestamp=N/A
best_effort_timestamp_time=N/A
-> pkt_duration=48000
-> pkt_duration_time=0.040000
pkt_pos=1534250
pkt_size=3928
width=1280
height=720
pix_fmt=yuvj420p
sample_aspect_ratio=N/A
pict_type=P
coded_picture_number=190
display_picture_number=0
interlaced_frame=0
top_field_first=0
repeat_pict=0
color_range=pc
color_space=bt709
color_primaries=bt709
color_transfer=bt709
chroma_location=left
[/FRAME]


    


    frame info from working (processed) avi

    


    [FRAME]
media_type=video
stream_index=0
key_frame=0
pkt_pts=N/A
pkt_pts_time=N/A
-> pkt_dts=500
-> pkt_dts_time=16.666667
best_effort_timestamp=500
best_effort_timestamp_time=16.666667
-> pkt_duration=1
-> pkt_duration_time=0.033333
pkt_pos=1772182
pkt_size=3070
width=1280
height=720
pix_fmt=yuvj420p
sample_aspect_ratio=N/A
pict_type=P
coded_picture_number=191
display_picture_number=0
interlaced_frame=0
top_field_first=0
repeat_pict=0
color_range=pc
color_space=bt709
color_primaries=bt709
color_transfer=bt709
chroma_location=left
[/FRAME]


    


    pkt_pts and pkt_dts are missing in the raw data, maybe that is the reason the video plays on fast forward ? in the working (processed) avi pkt_dts, pkt_dts_time, pkt_duration_time are not missing.
pkt_duration_time is always 0.033333
pkt_dts always jumps by 2 (there is no odd pkt_dts)

    


    Audio processing

    


    I have raw pcm audio of the video :

    


    here is an output of ffplay -f s16le -ar 16k -ac 1 frame_data2.h264 on the raw data

    


    enter image description here

    


    The raw audio does not playing well using this command.

    


    I guessed the parameters (incorrectly ?) from working avi file that contains the pcm data :

    


    Stream #0:1: Audio: pcm_s16le ([1][0][0][0] / 0x0001), 16000 Hz, 1 channels, s16, 256 kb/s


    


    here is frame info from working (processed) avi file

    


    [FRAME]
media_type=audio
stream_index=1
key_frame=1
pkt_pts=4320
pkt_pts_time=0.270000
pkt_dts=4320
pkt_dts_time=0.270000
best_effort_timestamp=4320
best_effort_timestamp_time=0.270000
pkt_duration=480
pkt_duration_time=0.030000
pkt_pos=11670
pkt_size=960
sample_fmt=s16
nb_samples=480
channels=1
channel_layout=unknown
[/FRAME]


    


    I'm trying to understand how should I process the video and the audio so that they will play well (merge them myself with the right av processing to avi/mp4 file)

    


    I also find this extra data that was included for each frame :
I suspect the first column is a sequence number maybe related to dts somehow, second column is a timestamp (milliseconds ?) (maybe you can help me parse it)

    


    600 0xd96533 (audio)
601 0xd9e1dd (audio)
602 0xda4f52 (audio)
603 0xda5a63 (video)
604 0xdacc4b (audio)
605 0xdb39a3 (audio)
606 0xdb5ee9 (video)
607 0xdbb6d8 (audio)
608 0xdc23fe (audio)
609 0xdcb255 (audio)
610 0xdd0e69 (audio)
611 0xdd8b96 (audio)
612 0xdd67d0 (video)
613 0xddf8bd (audio)
614 0xde75fe (audio)
615 0xde6c28 (video)
616 0xdee328 (audio)
617 0xdf6012 (audio)
618 0xdfcd9d (audio)
619 0xe04a7d (audio)
620 0xe07523 (video)
621 0xe0b80c (audio)
622 0xe134db (audio)
623 0xe1798b (video)
624 0xe1a251 (audio)
625 0xe21f5c (audio)
626 0xe28ce1 (audio)
627 0xe27df7 (video)
628 0xe309a7 (audio)
629 0xe376fe (audio)
630 0xe3826e (video)
631 0xe3f3fd (audio)
632 0xe46154 (audio)
633 0xe486e9 (video)
634 0xe4de79 (audio)
635 0xe54bbe (audio)
636 0xe58b79 (video)
637 0xe5c8cb (audio)
638 0xe6361e (audio)
639 0xe6b35b (audio)
640 0xe68fb7 (video)
641 0xe72093 (audio)
642 0xe79db1 (audio)
643 0xe7942f (video)
644 0xe80b09 (audio)
645 0xe887ed (audio)
646 0xe8f546 (audio)
647 0xe97256 (audio)
648 0xe99d2c (video)
649 0xe9dfbd (audio)
650 0xea5ca8 (audio)


    


    Thanks.

    


  • 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.

    What is 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.

    No credit card required

    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 :

    Why attribution tracking is important.

    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.

    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 :

    Pros and cons of different marketing attribution models.

    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. 

    What is a marketing attribution tool?

    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.