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• When I use ffmpeg to go from a video to frames, and then back to video, the duration is different between the videos

  24 février 2024, par bluepanda

  I am trying to use ffmpeg to convert from a .mp4 (or .mov) video into individual frames, do some processing on those frames, and then convert back to .mp4. The problem is that the resulting video I create is a different duration than the input - I can see this visually when I play the two videos side by side. The difference is not large (i.e. 00:00:00.50 for the input video and 00:00:00.52 for the output video), but when the videos are looped next to each other they get out of sync.

  


  Here is information about the input video retrieved using fluent-ffmpeg's ffmpeg.ffprobe(videoPath) :

  


  metadata {
  streams: [
    {
      index: 0,
      codec_name: 'h264',
      codec_long_name: 'H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10',
      profile: 'High',
      codec_type: 'video',
      codec_tag_string: 'avc1',
      codec_tag: '0x31637661',
      width: 1080,
      height: 1920,
      coded_width: 1080,
      coded_height: 1920,
      closed_captions: 0,
      has_b_frames: 2,
      sample_aspect_ratio: 'N/A',
      display_aspect_ratio: 'N/A',
      pix_fmt: 'yuv420p',
      level: 40,
      color_range: 'tv',
      color_space: 'bt709',
      color_transfer: 'bt709',
      color_primaries: 'bt709',
      chroma_location: 'left',
      field_order: 'unknown',
      refs: 1,
      is_avc: 'true',
      nal_length_size: 4,
      id: 'N/A',
      r_frame_rate: '30000/1001',
      avg_frame_rate: '27000/1001',
      time_base: '1/30000',
      start_pts: 0,
      start_time: 0,
      duration_ts: 15100,
      duration: 0.503333,
      bit_rate: 5660223,
      max_bit_rate: 'N/A',
      bits_per_raw_sample: 8,
      nb_frames: 36,
      nb_read_frames: 'N/A',
      nb_read_packets: 'N/A',
      tags: [Object],
      disposition: [Object]
    },
    {
      index: 1,
      codec_name: 'aac',
      codec_long_name: 'AAC (Advanced Audio Coding)',
      profile: 'LC',
      codec_type: 'audio',
      codec_tag_string: 'mp4a',
      codec_tag: '0x6134706d',
      sample_fmt: 'fltp',
      sample_rate: 48000,
      channels: 2,
      channel_layout: 'stereo',
      bits_per_sample: 0,
      id: 'N/A',
      r_frame_rate: '0/0',
      avg_frame_rate: '0/0',
      time_base: '1/48000',
      start_pts: 0,
      start_time: 0,
      duration_ts: 24160,
      duration: 0.503333,
      bit_rate: 248416,
      max_bit_rate: 'N/A',
      bits_per_raw_sample: 'N/A',
      nb_frames: 27,
      nb_read_frames: 'N/A',
      nb_read_packets: 'N/A',
      tags: [Object],
      disposition: [Object]
    }
  ],
  format: {
    filename: '/Users/name/images/input.mp4',
    nb_streams: 2,
    nb_programs: 0,
    format_name: 'mov,mp4,m4a,3gp,3g2,mj2',
    format_long_name: 'QuickTime / MOV',
    start_time: 0,
    duration: 0.503333,
    size: 963879,
    bit_rate: 15319941,
    probe_score: 100,
    tags: {
      major_brand: 'mp42',
      minor_version: '1',
      compatible_brands: 'isommp41mp42',
      creation_time: '2024-02-14T01:21:12.000000Z'
    }
  },
  chapters: []
}


  


  and here is from running ffprobe directly :

  


  ffprobe '/Users/name/images/input.mp4'
ffprobe version 6.1.1 Copyright (c) 2007-2023 the FFmpeg developers
  built with Apple clang version 15.0.0 (clang-1500.1.0.2.5)
  configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/6.1.1_2 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libharfbuzz --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libssh --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopenvino --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon
  libavutil      58. 29.100 / 58. 29.100
  libavcodec     60. 31.102 / 60. 31.102
  libavformat    60. 16.100 / 60. 16.100
  libavdevice    60.  3.100 / 60.  3.100
  libavfilter     9. 12.100 /  9. 12.100
  libswscale      7.  5.100 /  7.  5.100
  libswresample   4. 12.100 /  4. 12.100
  libpostproc    57.  3.100 / 57.  3.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/Users/name/images/input.mp4':
  Metadata:
    major_brand     : mp42
    minor_version   : 1
    compatible_brands: isommp41mp42
    creation_time   : 2024-02-14T01:21:12.000000Z
  Duration: 00:00:00.50, start: 0.000000, bitrate: 15319 kb/s
  Stream #0:0[0x1](und): Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv, bt709, progressive), 1080x1920, 5660 kb/s, 26.97 fps, 29.97 tbr, 30k tbn (default)
    Metadata:
      creation_time   : 2024-02-14T01:21:12.000000Z
      handler_name    : Core Media Video
      vendor_id       : [0][0][0][0]
      encoder         : AVC Coding
  Stream #0:1[0x2](und): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 248 kb/s (default)
    Metadata:
      creation_time   : 2024-02-14T01:21:12.000000Z
      handler_name    : Core Media Audio
      vendor_id       : [0][0][0][0]


  


  And this is my command to go from video to frames :

  


  ffmpeg -i /Users/name/images/input.mp4 -y -f image2 /Users/name/images/frames/%d.png


  


  After which I convert the frames back to video with this - note that I get by seeing avg_frame_rate is 27000/1001 = 26.97302697 :

  


  ffmpeg -r 26.973026973026972 -i /Users/name/images/frames/%d.png -y -r 26.973026973026972 -b:v 5660223k -f mp4 -pix_fmt yuv420p -t 0.503333 /Users/name/images/output.mp4


  


  And if I then run fluent-ffmpeg's ffmpeg.ffprobe(videoPath) I get :

  


  metadata {
  streams: [
    {
      index: 0,
      codec_name: 'h264',
      codec_long_name: 'H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10',
      profile: 'High',
      codec_type: 'video',
      codec_tag_string: 'avc1',
      codec_tag: '0x31637661',
      width: 1080,
      height: 1920,
      coded_width: 1080,
      coded_height: 1920,
      closed_captions: 0,
      has_b_frames: 2,
      sample_aspect_ratio: '1:1',
      display_aspect_ratio: '9:16',
      pix_fmt: 'yuv420p',
      level: 62,
      color_range: 'unknown',
      color_space: 'unknown',
      color_transfer: 'unknown',
      color_primaries: 'unknown',
      chroma_location: 'left',
      field_order: 'unknown',
      refs: 1,
      is_avc: 'true',
      nal_length_size: 4,
      id: 'N/A',
      r_frame_rate: '27000/1001',
      avg_frame_rate: '27000/1001',
      time_base: '1/27000',
      start_pts: 0,
      start_time: 0,
      duration_ts: 14014,
      duration: 0.519037,
      bit_rate: 52138429,
      max_bit_rate: 'N/A',
      bits_per_raw_sample: 8,
      nb_frames: 14,
      nb_read_frames: 'N/A',
      nb_read_packets: 'N/A',
      tags: [Object],
      disposition: [Object]
    }
  ],
  format: {
    filename: '/Users/name/images/output.mp4',
    nb_streams: 1,
    nb_programs: 0,
    format_name: 'mov,mp4,m4a,3gp,3g2,mj2',
    format_long_name: 'QuickTime / MOV',
    start_time: 0,
    duration: 0.52,
    size: 3383708,
    bit_rate: 52057046,
    probe_score: 100,
    tags: {
      major_brand: 'isom',
      minor_version: '512',
      compatible_brands: 'isomiso2avc1mp41',
      encoder: 'Lavf60.3.100'
    }
  },
  chapters: []
}


  


  and here is from running ffprobe directly :

  


  ffprobe '/Users/name/images/output.mp4'
ffprobe version 6.1.1 Copyright (c) 2007-2023 the FFmpeg developers
  built with Apple clang version 15.0.0 (clang-1500.1.0.2.5)
  configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/6.1.1_2 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libharfbuzz --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libssh --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopenvino --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon
  libavutil      58. 29.100 / 58. 29.100
  libavcodec     60. 31.102 / 60. 31.102
  libavformat    60. 16.100 / 60. 16.100
  libavdevice    60.  3.100 / 60.  3.100
  libavfilter     9. 12.100 /  9. 12.100
  libswscale      7.  5.100 /  7.  5.100
  libswresample   4. 12.100 /  4. 12.100
  libpostproc    57.  3.100 / 57.  3.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/Users/name/images/output.mp4':
  Metadata:
    major_brand     : isom
    minor_version   : 512
    compatible_brands: isomiso2avc1mp41
    encoder         : Lavf60.3.100
  Duration: 00:00:00.52, start: 0.000000, bitrate: 52153 kb/s
  Stream #0:0[0x1](und): Video: h264 (High) (avc1 / 0x31637661), yuv420p(progressive), 1080x1920 [SAR 1:1 DAR 9:16], 52138 kb/s, 26.97 fps, 26.97 tbr, 27k tbn (default)
    Metadata:
      handler_name    : VideoHandler
      vendor_id       : [0][0][0][0]
      encoder         : Lavc60.3.100 libx264


  


  This seems like it should be a fairly common scenario, but I have not been able to find examples of this, and the other questions about incorrect durations on Stack Overflow are about bigger differences (i.e. 3 seconds instead of 10 seconds : Wrong video duration when recording with ffmpeg).

  


  Some other details :

  


  

  • I am running this through a Node.js script with fluent-ffmpeg, but I have also tried running the commands directly in the terminal and the result is the same.

  


  • I am fine with the output frames being .png / .jpg / other formats.

  


  • I am fine with setting this to a different frame rate than the original as long as the two output videos end up with the same duration.

  


  • One suspicious thing is that I set -t 0.503333 when creating the video, but it doesn't seem to work as the result video shows duration: 0.519037 / 00:00:00.52.

  


  


  Thank you for any help !

  


• Linear Attribution Model : What Is It and How Does It Work ?

  16 février 2024, par Erin

  Want a more in-depth way to understand the effectiveness of your marketing campaigns ? Then, the linear attribution model could be the answer.

  Although you can choose from several different attribution models, a linear model is ideal for giving value to every touchpoint along the customer journey. It can help you identify your most effective marketing channels and optimise your campaigns. 

  So, without further ado, let’s explore what a linear attribution model is, when you should use it and how you can get started. 

  What is a linear attribution model ?

  A linear attribution model is a multi-touch method of marketing attribution where equal credit is given to each touchpoint. Every marketing channel used across the entire customer journey gets credit, and each is considered equally important. 

  So, if a potential customer has four interactions before converting, each channel gets 25% of the credit.

  

  Let’s look at how linear attribution works in practice using a hypothetical example of a marketing manager, Sally, who is looking for an alternative to Google Analytics. 

  Sally starts her conversion path by reading a Matomo article comparing Matomo to Google Analytics she finds when searching on Google. A few days later she signs up for a webinar she saw on Matomo’s LinkedIn page. Two weeks later, Sally gets a sign-off from her boss and decides to go ahead with Matomo. She visits the website and starts a free trial by clicking on one of the paid Google Ads. 

  Using a linear attribution model, we credit each of the channels Sally uses (organic traffic, organic social, and paid ads), ensuring no channel is overlooked in our marketing analysis. 

  Are there other types of attribution models ?

  Absolutely. There are several common types of attribution models marketing managers can use to measure the impact of channels in different ways. 

  

  • First interaction : Also called a first-touch attribution model, this method gives all the credit to the first channel in the customer journey. This model is great for optimising the top of your sales funnel.
  • Last interaction : Also called a last-touch attribution model, this approach gives all the credit to the last channel the customer interacts with. It’s a great model for optimising the bottom of your marketing funnel. 
  • Last non-direct interaction : This attribution model excludes direct traffic and credits the previous touchpoint. This is a fantastic alternative to a last-touch attribution model, especially if most customers visit your website before converting. 
  • Time decay attribution model : This model adjusts credit according to the order of the touchpoints. Those nearest the conversion get weighted the highest. 
  • Position-based attribution model : This model allocates 40% of the credit to the first and last touchpoints and splits the remaining 20% evenly between every other interaction.

  Why use a linear attribution model ?

  Marketing attribution is vital if you want to understand which parts of your marketing strategy are working. All of the attribution models described above can help you achieve this to some degree, but there are several reasons to choose a linear attribution model in particular. 

  It uses multi-touch attribution

  Unlike single-touch attribution models like first and last interaction, linear attribution is a multi-touch attribution model that considers every touchpoint. This is vital to get a complete picture of the modern customer journey, where customers interact with companies between 20 and 500 times. 

  Single-touch attribution models can be misleading by giving conversion credit to a single channel, especially if it was the customer’s last use. In our example above, Sally’s last interaction with our brand was through a paid ad, but it was hardly the most important. 

  It’s easy to understand

  Attribution models can be complicated, but linear attribution is easy to understand. Every touchpoint gets the same credit, allowing you to see how your entire marketing function works. This simplicity also makes it easy for marketers to take action. 

  It’s great for identifying effective marketing channels

  Because linear attribution is one of the few models that provides a complete view of the customer journey, it’s easy to identify your most common and influential touchpoints. 

  It accounts for the top and bottom of your funnel, so you can also categorise your marketing channels more effectively and make more informed decisions. For example, PPC ads may be a more common bottom-of-the-full touchpoint and should, therefore, not be used to target broad, top-of-funnel search terms.

  Are there any reasons not to use linear attribution ?

  Linear attribution isn’t perfect. Like all attribution models, it has its weaknesses. Specifically, linear attribution can be too simple, dilute conversion credit and unsuitable for long sales cycles.

  

  It can be too simple

  Linear attribution lacks nuance. It only considers touchpoints while ignoring other factors like brand image and your competitors. This is true for most attribution models, but it’s still important to point it out. 

  It can dilute conversion credit

  In reality, not every touchpoint impacts conversions to the same extent. In the example above, the social media post promoting the webinar may have been the most effective touchpoint, but we have no way of measuring this. 

  The risk with using a linear model is that credit can be underestimated and overestimated — especially if you have a long sales cycle. 

  It’s unsuitable for very long sales cycles

  Speaking of long sales cycles, linear attribution models won’t add much value if your customer journey contains dozens of different touchpoints. Credit will get diluted to the point where analysis becomes impossible, and the model will also struggle to measure the precise ways certain touchpoints impact conversions. 

  Should you use a linear attribution model ?

  A linear attribution model is a great choice for any company with shorter sales cycles or a reasonably straightforward customer journey that uses multiple marketing channels. In these cases, it helps you understand the contribution of each touchpoint and find your best channels. 

  It’s also a practical choice for small businesses and startups that don’t have a team of data scientists on staff or the budget to hire outside help. Because it’s so easy to set up and understand, anyone can start generating insights using this model. 

  How to set up a linear attribution model

  Are you sold on the idea of using a linear attribution model ? Then follow the steps below to get started :

  

  Choose a marketing attribution tool

  Given the market is worth $3.1 billion, you won’t be surprised to learn there are plenty of tools to choose from. But choose carefully. The tool you pick can significantly impact your success with attribution modelling. 

  Take Google Analytics, for instance. While GA4 offers several marketing attribution models for free, including linear attribution, it lacks accuracy due to cookie consent rejection and data sampling. 

  Accurate marketing attribution is included as a feature in Matomo Cloud and is available as a plugin for Matomo On-Premise users. We support a full range of attribution models that use 100% accurate data because we don’t use data sampling, and cookie consent isn’t an issue (with the exception of Germany and the UK). That means you can trust our insights.

  Matomo’s marketing attribution is available out of the box, and we also provide access to raw data, allowing you to develop your custom attribution model. 

  Collect data

  The quality of your marketing attribution also depends on the quality and quantity of your data. It’s why you need to avoid a platform that uses data sampling. 

  This should include :

  • General data from your analytics platform, like pages visited and forms filled
  • Goals and conversions, which we’ll discuss in more detail in the next step
  • Campaign tracking data so you can monitor the behaviour of traffic from different referral channels
  • Behavioural data from features like Heatmaps or Session Recordings

  Set up goals and conversions

  You can’t assign conversion values to customer journey touchpoints if you don’t have conversion goals in place. That’s why the next step of the process is to set up conversion tracking in your web analytics platform. 

  Depending on your type of business and the product you sell, conversions could take one of the following forms :

  • A product purchase
  • Signing up for a webinar
  • Downloading an ebook
  • Filling in a form
  • Starting a free trial

  Setting up these kinds of goals is easy if you use Matomo. 

  Just head to the Goals section of the dashboard, click Manage Goals and then click the green Add A New Goal button. 

  Fill in the screen below, and add a Goal Revenue at the bottom of the page. Doing so will mean Matomo can automatically calculate the value of each touchpoint when using your attribution model. 

  

  If your analytics platform allows it, make sure you also set up Event Tracking, which will allow you to analyse how many users start to take a desired action (like filling in a form) but never complete the task. 

  Try Matomo for Free

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  Test and validate

  As we’ve explained, linear attribution is a great model in some scenarios, but it can fall short if you have a long or complex sales funnel. Even if you’re sure it’s the right model for your company, testing and validating is important. 

  Ideally, your chosen attribution tool should make this process pretty straightforward. For example, Matomo’s Marketing Attribution feature makes comparing and contrasting three different attribution models easy. 

  Here we compare the performance of three attribution models—linear, first-touch, and last-non-direct—in Matomo’s Marketing Attribution dashboard, providing straightforward analysis.

  

  If you think linear attribution accurately reflects the value of your channels, you can start to analyse the insights it generates. If not, then consider using another attribution model.

  Don’t forget to take action from your marketing efforts, either. Linear attribution helps you spot the channels that contribute most to conversions, so allocate more resources to those channels and see if you can improve your conversion rate or boost your ROI. 

  Make the most of marketing attribution with Matomo

  A linear attribution model lets you measure every touchpoint in your customer journey. It’s an easy attribution model to start with and lets you identify and optimise your most effective marketing channels. 

  However, accurate data is essential if you want to benefit the most from marketing attribution data. If your web analytics solution doesn’t play nicely with cookies or uses sampled data, then your linear model isn’t going to tell you the whole story. 

  That’s why over 1 million sites trust Matomo’s privacy-focused web analytics, ensuring accurate data for a comprehensive understanding of customer journeys.

  Now you know what linear attribution modelling is, start employing the model today by signing up for a free 21-day trial, no credit card required. 

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• 9 Form Optimisation Tips to Convert More Visitors

  15 février 2024, par Erin

  Forms might seem boring — that is, until you realise how powerful they are.

  No forms mean no leads.

  No leads mean no sales.

  No sales means you’ll run out of business.

  So, what do you do ?

  Optimise forms to land more leads.

  They’re a critical part of the sales funnel.

  Forms have many different purposes and can be used to :

  • Contact a company
  • Sign up for a newsletter
  • Request a demo
  • Start a free trial
  • And more

  If you want to get more leads (and ultimately more sales), then you need to optimise your forms.

  This guide will show you exactly how to do that (so you can start getting more conversions today). 

  What is form optimisation ?

  Before we dive into form optimisation, let’s back up a bit.

  Form conversion is our primary focus.

  Your form conversion rate is the percentage of visitors who submit a form divided by the total number of visitors who started the form times one hundred.

  For example, if 5,000 people started filling out your form this month and 350 submitted the form, the conversion rate would be : 

  350 / 5,000 x 100 = 7%

  So, what’s form optimisation ?

  

  It’s simply improving your forms to increase conversion rates.

  For most people, form conversion is all about increasing leads.

  Before you begin optimising your forms, it’s important you understand what’s good (and what’s not good) when it comes to form conversions.

  The average form conversion rate across all industries is 2.9%.

  This means you should expect about 3 out of every 100 visitors who start your form to submit it.

  If your form conversion is lower — or hovering around this number — then it’s important to start optimising now.

  With Matomo, you can track your form conversions with Matomo Form Analytics. Gain powerful insights into how your visitors interact with your forms with our intuitive dashboard.

  Why it’s important to optimise your forms

  Most people hear the word “forms” and think it’s boring.

  But forms are the doorway to leads.

  If you want to generate more sales, then you need to generate great forms.

  Here are five reasons you need to optimise your forms today :

  

  1. Improve conversions

  Form optimisation is really just conversion optimisation.

  But, instead of optimising and improving your site to directly improve sales conversions, you’re increasing lead conversions.

  Every smart website owner uses forms to draw people in further.

  The reality is that most of your website visitors will never return to your site.

  This means you need to do everything you can to grab their contact information so you can continue marketing to them day in and day out.

  Otherwise, you’ll lose them forever.

  When you know how to optimise your forms, you’ll be able to get a higher percentage of form viewers to fill it out.

  Higher conversions mean you get more leads, more customers, and ultimately more revenue.

  2. Capture more leads

  When you can increase your form conversion rate from 1% to 2%, it may seem insignificant.

  What’s a measly percentage point in conversions ?

  It’s a lot.

  When you’re dealing with traffic in the tens or hundreds of thousands each month, an increase in conversion rate by a whole percentile is massive.

  Let’s say you take your conversion rate from 2% to 3% on your form, and you have 70,000 visitors view the form each month.

  Well, if 1,400 people used to sign up to your email list each month at a 2% conversion rate, then at a 3% conversion rate, you’d get 2,100 new email signups every month.

  That’s a major difference.

  When you can improve your signup forms, you improve your lead generation (which is conversion rate optimisation). And the more leads you have, the more sales you’ll make in the long run.

  3. Get the most out of your traffic

  If your forms don’t perform well, then you’re wasting your time (and your traffic).

  By analysing your form data, you can quickly see what’s working and what’s not so you can optimise and improve the user experience (and your forms).

  For most people, this means getting more form viewers to fill out the form with their email and name.

  If 50,000 people visit your site each month, but only 1% of them fill out your form, you’re only getting 500 email signups per month.

  Rather than paying money to generate more traffic, why not just work on improving your website by implementing a better form ?

  If you can increase your form conversion rate to 2%, you will immediately go from 500 new subscribers per month to 1,000 per month.

  4. Spend less on acquisition

  If you’re able to get more form signups without having to generate more traffic, you just solved a pricey problem : acquisition costs.

  If you can now get 1,000 of your 50,000 visitors to sign up to your email list through a better form, then you doubled your signups.

  But that’s not all. You just cut your acquisition costs in half.

  If you spend $2,000 per month on acquisition but you’re able to get twice as many leads, then your acquisition costs are at 50% of what they used to be.

  This means you can pay the same amount but get twice as many leads.

  Or, you can pour even more money into acquisition since it’s now twice as effective so you can fuel growth even more.

  5. Grow revenue

  Forms generate revenue. It may not be direct (although, in some cases, it is). 

  But, forms will lead to sales.

  By placing optimised forms throughout your website at the right places, you will be able to capture a percentage of your visitors as leads, which means you’ll eventually make more sales.

  13 tips to optimise your forms for more conversions

  Now that you know what forms can do and why they’re important to grow your business, it’s time to dive into the best practices.

  Follow these 13 tips to ensure you’re getting the most out of your forms :

  

  1. Set form goals

  Your forms are hopeless without a goal.

  Before you set up a form on your website, ask yourself, “What am I trying to accomplish with this form ?”

  It could be :

  • Encouraging customers to reach out through a contact form
  • To get visitors to leave feedback on your product/service
  • Convert visitors into leads by giving you their email

  No matter what your goal is, make sure you’re clear on it ; otherwise, you won’t be as targeted and specific with your forms.

  Matomo Goals helps you set specific objectives for your marketing campaigns so you’re able to easily track conversions. Whether you’re looking to capture feedback or generate leads, you can leverage Matomo to see what’s working and what’s not in seconds.

  2. Remove or improve fields with high average time spent and high drop-off rates

  Delving into your Form Analytics provides invaluable insights into individual field performance. A crucial metric to focus on is the Average Time Spent. 

  If a field stands out with a significantly higher average time spent and experiences a high drop-off rate compared to others in the form, it’s a clear indicator that it’s causing frustration or confusion for your visitors.

  To address this, consider improving the field by converting it into a dropdown menu for easier completion or providing helpful text prompts. Alternatively, if the field isn’t essential, you might opt to remove it altogether.

  When you cut down on time spent and drop-offs, you’ll see your conversion rates go up.

  

  Here’s a standout example from Matomo’s Form Analytics feature : the “Overview of your needs” field is taking on average 1 minute and 37 seconds to complete. 

  To streamline this, we might want to consider a simple fix like converting it into a dropdown menu. This change would offer visitors a clearer and quicker way to select from options.

  

  Likewise, we observe that the “Overview of your needs” field experiences the highest drop-off rate, totaling 1,732 drop-offs. 

  With Form Analytics, it becomes clear what is needed to optimise forms and increase conversions.

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  3. Start with the CTA

  When crafting and optimising your forms, you need to start with the end in mind. That’s why you need to start with your business goals.

  What are you trying to do with this form ? If you want to capture more emails, then make sure that’s very clear with the call to action (CTA).

  Start building your form by beginning with the CTA.

  For example : “Sign Up Now.”

  Once you have the action you want your potential customers to take, place it on the form. Then, you can work towards crafting the rest of the form.

  4. Put it above the fold

  If your visitors can’t find your form, they won’t fill it out. It’s plain and simple.

  You need to make sure your form is visible above the fold. This is the part of the screen that’s visible to your visitors once they land on your site (without needing to scroll down).

  Always remember to test this out on both desktop and mobile to ensure anyone (using laptops or a mobile device) will see your form upon landing on your site or page.

  Don’t forget about your mobile users. More people view mobile forms than desktop forms. 

  5. Put a CTA in the headline

  Your form needs to be clear.

  You have 1-3 seconds to communicate with your site visitors what your form is all about.

  For example, if you’re trying to get email signups with a lead magnet, then tell them the benefit quickly and concisely with a CTA in the headline, like this one :

  “Subscribe to Save 10% On Your Next Order”

  This is a great example of a headline-CTA combo that tells the visitor what to do and what they get out of it.

  Matomo’s behaviour analytics features like Session Recordings let you see where visitors are clicking and spending time. For example, if people are reading the headline, but not scrolling down to read the form, it’s probably a sign you need to test a different headline.

  6. Ensure you have the right fields

  Your form fields matter.

  What information are you trying to capture from your audience ?

  One beginner mistake people make is requiring too much information and including many fields in a form.

  You want to get as much data on your audience as possible, right ? Wrong.

  If you ask for too much information, people won’t fill it out, and it will harm the user experience. You need to make it super easy.

  If you want more emails to grow your list, then stick with someone’s email (and possibly their name as well). One line for a name. One line for an email address. Keep it simple.

  If you’re after SMS as well, don’t include it on the form. Instead, create a two-step form that pops up an SMS form after someone fills out the email form.

  Multi-step forms enable you to capture those emails easily (and still get a percentage to fill out the second form) without making it seem like too much work for your audience.

  Another path is to include optional fields (that users don’t have to fill out to click submit).

  Just keep in mind that shorter forms perform better than longer ones.

  If you make them too long, it feels like work for the user and will lead to lower completion rates.

  7. Always capture email address

  If you’re unsure of what information to capture (i.e. name, number, email, occupation, age, etc.), always stick to email.

  Email is used by over 4 billion people every single day, and it’s not going away anytime soon.

  When determining which fields to include, start with email.

  

  8. Test different buttons and copy

  You need to track your form performance if you want to get the best conversions.

  One of the best form elements to start testing is your button copy.

  In most cases, form completion buttons will have the word “submit” on them.

  But you don’t have to stick with this word.

  You can (and should) experiment with different submit button copy.

  Here are a few examples of replacement words for your action button :

  • Complete
  • Sign Up
  • Join now
  • Get started

  Remember to experiment with your action button. Try a different copy. Just keep it short.

  You can also try A/B testing your form by experimenting with different colours, copy, and more.

  

  In the example above from Matomo’s A/B testing feature, we found that changing the wording of our call to action made a big difference. The new “Apply Now” button performed much better, with a 3.6% conversion rate compared to just 1.7% for the original one.

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  9. Test static vs. popup

  There are various types of online forms.

  The most common is the static form that just sits in one place and is always there.

  Another popular form type is the popup.

  This is where a form will appear based on a certain trigger like :

  • A certain amount of time on page
  • A certain distance scrolling down the page
  • If someone is a new or returning visitor

  Depending on the form software you use, you may be able to add conditional logic.

  Start tracking your form conversions

  Form optimisation is all about conversion rate optimisation.

  If you want to increase your conversions and generate more revenue, then you need to test out different forms and know how to optimise them.

  With Matomo, you can easily track, manage, and A/B test your forms so you can improve your conversions. 

  Try Matomo free for 21 days. No credit card required.

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