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• What is the proper input format for drawtext's timecode option in fluent-ffmpeg (node.js) ?

  24 janvier 2023, par Gil Dekel

  I am trying to generate short video clips from 3 images with a simple millisecond counter at the top left per user request. So far I was able to generate the clips using the videoshow npm lib, no issues here.

  



  However, when I try to add the timer via fluent-ffmpeg's drawtext filter to an already generated video, I run into the following issue.

  



  Here's what I have so far :

  



  ffmpeg('video.mp4')
    .on('error', function(err, stdout, stderr) {
      console.log("ffmpeg stdout:\n" + stdout);
      console.log("ffmpeg stderr:\n" + stderr);
    })
    .videoCodec('libx264')
    .format('mp4')
    .fps(fps)
    .complexFilter([
        {
            filter: 'drawtext',
            options: {
                fontsize: 15,
                timecode: '00\:00\:00\:00',  //<--- Issue is most likely here
                fontsize: 32,
                fontcolor: 'white',
                boxcolor: 'black',
                box: 1
            }
        }
    ]).save('out.mp4');


  



  From what I found online I am quite convinced that my problem is with the timecode input format. Here's my error log :

  



  ffmpeg stderr:
ffmpeg version 3.4.2 Copyright (c) 2000-2018 the FFmpeg developers
  built with Apple LLVM version 9.0.0 (clang-900.0.39.2)
  configuration: --prefix=/usr/local/Cellar/ffmpeg/3.4.2 --enable-shared --enable-pthreads --enable-version3 --enable-hardcoded-tables --enable-avresample --cc=clang --host-cflags= --host-ldflags= --disable-jack --enable-gpl --enable-libass --enable-libfdk-aac --enable-libfontconfig --enable-libfreetype --enable-libmp3lame --enable-libopus --enable-libvorbis --enable-libvpx --enable-libx264 --enable-libx265 --enable-libxvid --enable-opencl --enable-videotoolbox --disable-lzma --enable-nonfree
  libavutil      55. 78.100 / 55. 78.100
  libavcodec     57.107.100 / 57.107.100
  libavformat    57. 83.100 / 57. 83.100
  libavdevice    57. 10.100 / 57. 10.100
  libavfilter     6.107.100 /  6.107.100
  libavresample   3.  7.  0 /  3.  7.  0
  libswscale      4.  8.100 /  4.  8.100
  libswresample   2.  9.100 /  2.  9.100
  libpostproc    54.  7.100 / 54.  7.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'video.mp4':
  Metadata:
    major_brand     : isom
    minor_version   : 512
    compatible_brands: isomiso2avc1mp41
    encoder         : Lavf57.83.100
  Duration: 00:00:01.03, start: 0.000000, bitrate: 585 kb/s
    Stream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuv420p, 640x1136 [SAR 923:924 DAR 130:231], 573 kb/s, 60 fps, 60 tbr, 15360 tbn, 120 tbc (default)
    Metadata:
      handler_name    : VideoHandler
[Parsed_drawtext_0 @ 0x7f91aa700700] Both text and text file provided. Please provide only one
[AVFilterGraph @ 0x7f91aa700440] Error initializing filter 'drawtext' with args 'fontsize=32:timecode=00:00:00:00:fontcolor=white:boxcolor=black:box=1'
Error initializing complex filters.
Invalid argument


  



  Specifically this :

  



  [Parsed_drawtext_0 @ 0x7f91aa700700] Both text and text file provided. Please provide only one


  



  When I run what should be the equivalent to my code in shell, it works perfectly :

  



  ffmpeg -i video.mp4 \
       -vf drawtext="fontsize=15:timecode='00\:00\:00\:00':rate=60:fontsize=32:fontcolor='white':\
           boxcolor=0x000000AA:box=1" \
       -f mp4 out.mp4


  



  I already spent a whole day trying to find any previous solutions to this problem, or documentation online regarding the proper format of drawtext's timecode option within node.js with no luck. It seems most of the information out there is for bash/shell use. I need to do this programmatically on a server per request, and I just can't find the right example to solve this.

  



  Any help to resolve this would be appreciated.

  


• Clickstream Data : Definition, Use Cases, and More

  15 avril 2024, par Erin

  Gaining a deeper understanding of user behaviour — customers’ different paths, digital footprints, and engagement patterns — is crucial for providing a personalised experience and making informed marketing decisions. 

  In that sense, clickstream data, or a comprehensive record of a user’s online activities, is one of the most valuable sources of actionable insights into users’ behavioural patterns. 

  This article will cover everything marketing teams need to know about clickstream data, from the basic definition and examples to benefits, use cases, and best practices. 

  What is clickstream data ? 

  As a form of web analytics, clickstream data focuses on tracking and analysing a user’s online activity. These digital breadcrumbs offer insights into the websites the user has visited, the pages they viewed, how much time they spent on a page, and where they went next.

  

  Your clickstream pipeline can be viewed as a “roadmap” that can help you recognise consistent patterns in how users navigate your website. 

  With that said, you won’t be able to learn much by analysing clickstream data collected from one user’s session. However, a proper analysis of large clickstream datasets can provide a wealth of information about consumers’ online behaviours and trends — which marketing teams can use to make informed decisions and optimise their digital marketing strategy. 

  Clickstream data collection can serve numerous purposes, but the main goal remains the same — gaining valuable insights into visitors’ behaviours and online activities to deliver a better user experience and improve conversion likelihood. 

  Depending on the specific events you’re tracking, clickstream data can reveal the following : 

  • How visitors reach your website 
  • The terms they type into the search engine
  • The first page they land on
  • The most popular pages and sections of your website
  • The amount of time they spend on a page 
  • Which elements of the page they interact with, and in what sequence
  • The click path they take 
  • When they convert, cancel, or abandon their cart
  • Where the user goes once they leave your website

  As you can tell, once you start collecting this type of data, you’ll learn quite a bit about the user’s online journey and the different ways they engage with your website — all without including any personal details about your visitors.

  Types of clickstream data 

  While all clickstream data keeps a record of the interactions that occur while the user is navigating a website or a mobile application — or any other digital platform — it can be divided into two types : 

  • Aggregated (web traffic) data provides comprehensive insights into the total number of visits and user interactions on a digital platform — such as your website — within a given timeframe 
  • Unaggregated data is broken up into smaller segments, focusing on an individual user’s online behaviour and website interactions 

  One thing to remember is that to gain valuable insights into user behaviour and uncover sequential patterns, you need a powerful tool and access to full clickstream datasets. Matomo’s Event Tracking can provide a comprehensive view of user interactions on your website or mobile app — everything from clicking a button and completing a form to adding (or removing) products from their cart. 

  On that note, based on the specific events you’re tracking when a user visits your website, clickstream data can include : 

  • Web navigation data : referring URL, visited pages, click path, and exit page
  • User interaction data : mouse movements, click rate, scroll depth, and button clicks
  • Conversion data : form submissions, sign-ups, and transactions 
  • Temporal data : page load time, timestamps, and the date and time of day of the user’s last login 
  • Session data : duration, start, and end times and number of pages viewed per session
  • Error data : 404 errors and network or server response issues 

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  Clickstream data benefits and use cases 

  Given the actionable insights that clickstream data collection provides, it can serve a wide range of use cases — from identifying behavioural patterns and trends and examining competitors’ performance to helping marketing teams map out customer journeys and improve ROI.

  

  According to the global Clickstream Analytics Market Report 2024, some key applications of clickstream analytics include click-path optimisation, website and app optimisation, customer analysis, basket analysis, personalisation, and traffic analysis. 

  

  The behavioural patterns and user preferences revealed by clickstream analytics data can have many applications — we’ve outlined the prominent use cases below. 

  Customer journey mapping 

  Clickstream data allows you to analyse the e-commerce customer’s online journey and provides insights into how they navigate your website. With such a comprehensive view of their click path, it becomes easier to understand user behaviour at each stage — from initial awareness to conversion — identify the most effective touchpoints and fine-tune that journey to improve their conversion likelihood. 

  Identifying customer trends 

  Clickstream data analytics can also help you identify trends and behavioural patterns — the most common sequences and similarities in how users reached your website and interacted with it — especially when you can access data from many website visitors. 

  Think about it — there are many ways in which you can use these insights into the sequence of clicks and interactions and recurring patterns to your team’s advantage. 

  Here’s an example : 

  It can reveal that some pieces of content and CTAs are performing well in encouraging visitors to take action — which shows how you should optimise other pages and what you should strive to create in the future, too. 

  Preventing site abandonment 

  Cart abandonment remains a serious issue for online retailers : 

  According to a recent report, the global cart abandonment rate in the fourth quarter of 2023 was at 83%. 

  That means that roughly eight out of ten e-commerce customers will abandon their shopping carts — most commonly due to additional costs, slow website loading times and the requirement to create an account before purchasing. 

  In addition to cart abandonment predictions, clickstream data analytics can reveal the pages where most visitors tend to leave your website. These drop-off points are clear indicators that something’s not working as it should — and once you can pinpoint them, you’ll be able to address the issue and increase conversion likelihood.

  Improving marketing campaign ROI 

  As previously mentioned, clickstream data analysis provides insights into the customer journey. Still, you may not realise that you can also use this data to keep track of your marketing effectiveness. 

  Global digital ad spending continues to grow — and is expected to reach $836 billion by 2026. It’s easy to see why relying on accurate data is crucial when deciding which marketing channels to invest in. 

  You want to ensure you’re allocating your digital marketing and advertising budget to the channels — be it SEO, pay-per-click (PPC) ads, or social media campaigns — that impact driving conversions. 

  When you combine clickstream e-commerce data with conversion rates, you’ll find the latter in Matomo’s goal reports and have a solid, data-driven foundation for making better marketing decisions.

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

  Start for free

  No credit card required

  Delivering a better user experience (UX) 

  Clickstream data analysis allows you to identify specific “pain points” — areas of the website that are difficult to use and may cause customer frustration. 

  It’s clear how this would be beneficial to your business : 

  Once you’ve identified these pain points, you can make the necessary changes to your website’s layout and address any technical issues that users might face, improving usability and delivering a smoother experience to potential customers. 

  Collecting clickstream data : Tools and legal implications 

  Your team will need a powerful tool capable of handling clickstream analytics to reap the benefits we’ve discussed previously. But at the same time, you need to respect users’ online privacy throughout clickstream data collection.

  

  Generally speaking, there are two ways to collect data about users’ online activity — web analytics tools and server log files.

  Web analytics tools are the more commonly used solution. Specifically designed to collect and analyse website data, these tools rely on JavaScript tags that run in the browser, providing actionable insights about user behaviour. Server log files can be a gold mine of data, too — but that data is raw and unfiltered, making it much more challenging to interpret and analyse. 

  That brings us to one of the major clickstream challenges to keep in mind as you move forward — compliance.

  While Google remains a dominant player in the web analytics market, there’s one area where Matomo has a significant advantage — user privacy. 

  Matomo operates according to privacy laws — including the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), making it an ethical alternative to Google Analytics. 

  It should go without saying, but compliance with data privacy laws — the most talked-about one being the GDPR framework introduced by the EU — isn’t something you can afford to overlook. 

  The GDPR was first implemented in the EU in 2018. Since then, several fines have been issued for non-compliance — including the record fine of €1.2 billion that Meta Platforms, Inc. received in 2023 for transferring personal data of EU-based users to the US.

  Clickstream analytics data best practices 

  

  As valuable as it might be, processing large amounts of clickstream analytics data can be a complex — and, at times, overwhelming — process. 

  Here are some best practices to keep in mind when it comes to clickstream analysis : 

  Define your goals 

  It’s essential to take the time to define your goals and objectives. 

  Once you have a clear idea of what you want to learn from a given clickstream dataset and the outcomes you hope to see, it’ll be easier to narrow down your scope — rather than trying to tackle everything at once — before moving further down the clickstream pipeline. 

  Here are a few examples of goals and objectives you can set for clickstream analysis : 

  • Understanding and predicting users’ behavioural patterns 
  • Optimising marketing campaigns and ROI 
  • Attributing conversions to specific marketing touchpoints and channels

  Analyse your data 

  Collecting clickstream analytics data is only part of the equation ; what you do with raw data and how you analyse it matters. You can have the most comprehensive dataset at your disposal — but it’ll be practically worthless if you don’t have the skill set to analyse and interpret it. 

  In short, this is the stage of your clickstream pipeline where you uncover common sequences and consistent patterns in user behaviour. 

  Clickstream data analytics can extract actionable insights from large datasets using various approaches, models, and techniques. 

  Here are a few examples : 

  • If you’re working with clickstream e-commerce data, you should perform funnel or conversion analyses to track conversion rates as users move through your sales funnel. 
  • If you want to group and analyse users based on shared characteristics, you can use Matomo for cohort analysis. 
  • If your goal is to predict future trends and outcomes — conversion and cart abandonment prediction, for example — based on available data, prioritise predictive analytics.

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  Organise and visualise your data

  As you reach the end of your clickstream pipeline, you need to start thinking about how you will present and communicate your data. And what better way to do that than to transform that data into easy-to-understand visualisations ? 

  Here are a few examples of easily digestible formats that facilitate quick decision-making : 

  • User journey maps, which illustrate the exact sequence of interactions and user flow through your website 
  • Heatmaps, which serve as graphical — and typically colour-coded — representations of a website visitor’s activity 
  • Funnel analysis, which are broader at the top but get increasingly narrower towards the bottom as users flow through and drop off at different stages of the pipeline 

  Collect clickstream data with Matomo 

  Clickstream data is hard to beat when tracking the website visitor’s journey — from first to last interaction — and understanding user behaviour. By providing real-time insights, your clickstream pipeline can help you see the big picture, stay ahead of the curve and make informed decisions about your marketing efforts. 

  Matomo accurate data and compliance with GDPR and other data privacy regulations — it’s an all-in-one, ethical platform that can meet all your web analytics needs. That’s why over 1 million websites use Matomo for their web analytics.

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

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

  .matomo.cloud

  I accept the terms and conditions and data processing agreement (DPA)

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  
  

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• How to Increase Conversions With Form Analysis

  30 janvier 2024, par Erin

  Forms are one of the most important elements of your website. They are also one of the most difficult elements to analyse and improve. 

  Unlike a webpage, forms aren’t all that easy to analyse with standard web analytics tools. You need to learn how to conduct form analysis if you want to improve your forms’ conversion rates and increase revenue. 

  In this article, we’ll explain what form analysis is and why conducting a thorough form analysis is so important. 

  What is form analysis ?

  Form analysis is a process that measures the effectiveness of your forms. Form analysis uses several tools and techniques like a form analytics platform, heatmaps, and session recordings to collect user data and understand how visitors behave when filling in forms. 

  The goal is to improve the design and effectiveness of your forms, reducing abandonment rate and encouraging more users to submit them. 

  There are plenty of reasons visitors could be having trouble with your forms, from confusing form fields to poor design and lengthy verification processes. Form analytics can help you pinpoint why your form’s conversion rate is so low or why so many users abandon your form halfway through filling it in. 

  Why is form analysis important ?

  Website forms have some of the highest bounce rates and abandonments of any website element. By analysing your forms, you can achieve the following outcomes :

  

  Reduce form abandonment

  When it’s tough enough to get users to start filling in your form, the last thing you want them to do is abandon it halfway through. But that’s probably what your users are doing more than you’d like to think. 

  Why are they abandoning it ? Even if you’re humble enough to admit you didn’t create the greatest form the world’s ever seen, it can still be incredibly difficult to pin down why users give up on your form.

  That’s unless you conduct a form analysis. By analysing metrics and user behaviour, you can pinpoint and rectify the issues that cause users to abandon your form. 

  Improve the user experience

  Best practices will only take you so far. How users behave when filling in a form on your website may be completely different to how they behave on another site. That’s why you need to use form analysis to understand how users behave specifically on your website — and then use that information to optimise the design, layout, and content of the form to better suit them. 

  If one field is regularly left empty, for example, you can delete it. If users spend several minutes filling out a form with a high abandonment rate, you could shorten it. 

  The goal isn’t to make the best form ever but to make the best form for your audience. 

  Increase conversions

  Ultimately, form analysis helps you improve your form’s most important metric : conversions. Reducing your abandonment rate will naturally lead to more completions, but so will taking advantage of other optimisation opportunities that only become clear with form analysis. This can include optimisations like :

  • Moving the form higher up on the page
  • Shortening the form
  • Changing the heading and CTAs
  • Renaming field labels 

  A thorough form analysis process can ensure your forms generate as many conversions as possible. 

  Why do users abandon forms ?

  Are you already suffering from high form abandonment rates ? Don’t worry, you’re not alone. Marketers regularly make the same mistakes when creating forms that cause users to give up halfway through completion.

  Here are some of the most common reasons for form abandonment :

  • There are too many steps. If you’re telling users they’ve just completed step 2 of 12, you can bet they won’t bother finishing your form. 
  • They ask for too much information. No one wants to fill out a long form, and often, users won’t have the information on hand if you ask for too much. Just look at the rate left blank from the Unneeded Fields report in the screenshot below :

  

  • The form is confusing. Unclear form fields or directions can put users off. 
  • All the fields are free text and time-consuming. Filling out forms with long text fields takes too much time. To speed things up, use dropdown options in the fields, but keep the options to a minimum. This not only helps users finish the form faster but also makes it easier to analyse the data later because it keeps the data format consistent so you can organise the information more efficiently. 
  • Users don’t trust the form. This is a particular problem on checkout pages where users are entering sensitive information.

  How to conduct form analysis

  You need to collect user behaviour data to effectively analyse your forms. But a lot of traditional website analytics tools won’t have the required functionality. 

  Matomo is different. Our web analytics solution offers comprehensive web analytics as well as additional features like Heatmaps, Session Recordings, A/B Testing, and Form Analytics to provide all the functionality you need. 

  Now if you don’t use Matomo, you can try it free for 21 days (no credit card required) to see if it’s the right tool for you.

  Whether you use Matomo or not is up to you. But, once you have a suitable tool in place, just follow the steps below to conduct a form analysis. 

  Check your analytics

  Tracking and analysing specific form metrics should be the first place you start. We recommend collecting data on the following metrics :

  • Form starter rate : the percentage of visitors who actually start to fill in your form
  • Completion rate : the percentage of visitors who complete the form
  • Form abandonment rate : the percentage of users who gave up filling in your form
  • Time spent completing your form : the average length of time users spend on your form

  Let’s look at these metrics are in Matomo’s Form Analytics :

  

  The dashboard shows an overview of these metrics over a given period, allowing you to see at a glance whether there are issues you need to rectify. 

  Next, deep dive into the performance of each form to see things like :

  • Drop off fields
  • Unused fields
  • Entry field
  • Most corrected fields 

  You can even use Matomo’s visitor log to see who’s behind every submission.

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  Use a heatmap

  A heatmap is a colour-based graphical representation of data. A heatmap will show what users to do on your website, including : 

  • How far they scroll
  • Which buttons they click on
  • Where they focus their attention

  When used on a webpage with a form, you’ll be able to see how often users interact with your form based on the heatmap colour, with warmer colours representing greater engagement levels.

  Let’s look at a heatmap in Matomo :

  

  This heatmap is showing us how far down users have scrolled. It’s clear that only 63% of visitors are reaching the point above our call to action to see all features. We might want to consider moving that call to action up in order to get more engagement. 

  A heatmap is a great way to see whether your form’s placement gets the level of attention you want from visitors and to what extent visitors interact with your field.

  Record user sessions

  Session replays go even further than heatmaps, recording a real-life user interacting with your site. It’s like looking over a visitor’s shoulder while they use your site.

  

  With Matomo, you can record any sessions where the user takes a certain action (like starting to fill in a form), allowing you to build a rich library of qualitative data. 

  You can then replay a recorded session at your leisure to understand exactly how users interact with your forms.

  Segment users

  If you really want to understand how visitors use your forms, then it’s essential to segment your data. 

  You can segment all Form Analytics reports by over 100 pre-built segments in Matomo.

  

  One way to segment your data is by comparing the average time on form of those who completed the form with those who abandoned it. 

  If users abandon a form quickly, that could indicate your form is irrelevant to this audience or too long. If users spend a lot of time on the form, however, it’s probably safe to assume that it is relevant but there is something wrong with the form itself. 

  Looking at the Field Timings report will help you pinpoint which field visitors are spending the most time on and causing frustration. 

  

  The Field Timings example report in Matomo above, it’s evident that the “Overview of your needs” field takes up the most time (avg. time spent is 1 min 40s). To improve this, we might want to change it to a dropdown field. This way, users can quickly select options, and if necessary, provide additional details.

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  Another way is to segment data by traffic source and compare each source’s conversion rate. This will show whether one traffic source converts better than another or if one source isn’t interested in your form at all.

  How to optimise web forms

  Want to implement what you’ve learnt from your form analysis ? Follow these steps to optimise your existing web forms. 

  Define your form’s purpose

  The first step in optimising your existing web forms is to give a clear and definitive purpose to every single one. 

  When you have a defined goal, creating a form users will complete is much easier. After all, if you don’t know why people should fill in one of your forms, how would a visitor possibly know ?

  Take a look at one of our forms below :

  

  The purpose of this form is to get users to sign up for a free trial of our web analytics platform, and every element works towards that goal :

  • The headline directs the user to take action
  • The copy explains that it’s a free trial that doesn’t require credit card details
  • The green call-to-action button reinforces the action and benefit 
  • There is validation to support this under the form – “Trusted on over 1 million websites in over 190+ countries”

  Our clear instructions leave users no doubt about why they should fill in the form or what will happen. 

  Choose the right type of form

  You can use several forms on your website, each with different designs, form fields, and goals.

  For example :

  • Registration forms are fairly minimalist and designed to collect the least amount of data possible. 
  • Contact forms are concise so that it’s easy for potential customers to reach your team. 
  • Checkout forms balance a need to collect important data with a streamlined design that doesn’t put users off.
  • Lead generation forms are compelling and usually include qualifying questions so sales teams can score leads.

  Make sure you are using the right type of form to avoid abandonments and other issues. For example, requiring users to fill in a lengthy lead generation-style form when you want them to sign up for a free trial will probably kill your conversion rate. 

  Test form elements

  If your form analysis has shed light on one or two issues, you can use A/B or multivariate testing to trial new elements or designs and see how they compare.

  There’s no shortage of elements you can test, including the form’s :

  • Headline
  • Placement
  • Design
  • CTA button
  • Colour-scheme
  • Length
  • Form fields

  

  Matomo makes it easy to create and run A/B tests on your website’s forms. 

  Move your form above the fold

  One of the simplest ways to optimise your web form is to move it above the fold — that’s the section of the screen users see when they load your page. 

  Why ? Well, the more people who see your form, the more people will fill it in. And when it’s above the fold, users can’t help but see it.

  Conclusion

  Forms are one of the most important elements on your website, so why not treat them as such and regularly run a thorough form analysis ? By doing so, you’ll identify ways to optimise your form, improve the user experience, and improve conversions. 

  Matomo is the best platform for conducting form analysis. Our combination of web analytics, Form Analytics, Session Recordings, and Heatmaps means you have all the tools you need to learn exactly how visitors interact with your forms. 

  See just how powerful Matomo’s tools are by starting a free 21-day trial, no credit card required. 

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

  .matomo.cloud

  I accept the terms and conditions and data processing agreement (DPA)

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  
  

  Start improving your websites now