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• Deno.run not working with —allow-net flag

  29 janvier 2021, par Rishi Raj

  I'm trying to use Deno.run to execute an ffmpeg subprocess, followed the deno doc here (https://doc.deno.land/https/github.com/denoland/deno/releases/latest/download/lib.deno.d.ts#Deno.run)

  



  const ffmpeg = Deno.run({ cmd: ['--allow-run', '/usr/local/bin/ffmpeg', '-i','-',

   // video codec config: low latency, adaptive bitrate
   '-c:v', 'libx264', '-preset', 'veryfast', '-tune', 'zerolatency',

   // audio codec config: sampling frequency (11025, 22050, 44100), bitrate 64 kbits
   '-c:a', 'aac', '-ar', '44100', '-b:a', '64k',

   //force to overwrite
   '-y',

   // used for audio sync
   '-use_wallclock_as_timestamps', '1',
   '-async', '1',

   //'-filter_complex', 'aresample=44100', // resample audio to 44100Hz, needed if input is not 44100
   //'-strict', 'experimental',
   '-bufsize', '1000',
   '-f', 'flv', 
   // allow run flag
  rtmpUrl]
 }); 


  



  And I get the following error. I'm passing the --allow-run flag as the first argument, is there something that I'm missing here ?

  



  error: Uncaught PermissionDenied: access to run a subprocess, run again with the --allow-run flag


  


• 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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  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.

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• Dreamcast SD Adapter and DreamShell

  31 décembre 2014, par Multimedia Mike — Sega Dreamcast

  Nope ! I’m never going to let go of the Sega Dreamcast hacking. When I was playing around with Dreamcast hacking early last year, I became aware that there is such a thing as an SD card adapter for the DC that plugs into the port normally reserved for the odd DC link cable. Of course I wanted to see what I could do with it.

  The primary software that leverages the DC SD adapter is called DreamShell. Working with this adapter and the software requires some skill and guesswork. Searching for these topics tends to turn up results from various forums where people are trying to cargo-cult their way to solutions. I have a strange feeling that this post might become the unofficial English-language documentation on the matter.

  Use Cases
  What can you do with this thing ? Undoubtedly, the primary use is for backing up (ripping) the contents of GD-ROMs (the custom optical format used for the DC) and playing those backed up (ripped) copies. Presumably, users of this device leverage the latter use case more than the former, i.e., download ripped games, load them on the SD card, and launch them using DreamShell.

  However, there are other uses such as multimedia playback, system exploration, BIOS reprogramming, high-level programming, and probably a few other things I haven’t figured out yet.

  Delivery
  I put in an order via the dc-sd.com website and in about 2 short months, the item arrived from China. This marked my third lifetime delivery from China and curiously, all 3 of the shipments have pertained to the Sega Dreamcast.

  
  

  

  Click for larger image

  
  

  I thought it was very interesting that this adapter came in such complete packaging. The text is all in Chinese, though the back states “Windows 98 / ME / 2000 / XP, Mac OS 9.1, LINUX2.4”. That’s what tipped me off that they must have just cannibalized some old USB SD card readers and packaging in order to create these. Closer inspection of the internals through the translucent pink case confirms this.

  Usage
  According to its change log, DreamShell has been around for a long time with version 1.0.0 released in February of 2004. The current version is 4.0.0 RC3. There are several downloads available :

  1. DreamShell 4.0 RC 3 CDI Image
  2. DreamShell 4.0 RC 3 + Boot Loader
  3. DreamShell 4.0 RC 3 + Core CDI image

  Option #2 worked for me. It contains a CDI disc image and the DreamShell files in a directory named DS/.

  Burn the CDI to a CD-R in the normal way you would burn a bootable Dreamcast disc from a CDI image. This is open-ended and left as an exercise to the reader, since there are many procedures depending on platform. On Linux, I used a small script I found once called burncdi-dc.sh.

  Then, copy the contents of the DS/ folder to an SD card. As for filesystem, FAT16 and FAT32 are both known to work. The files in DS/ should land in the root of the SD card ; the folder DS/ should not be in the root.

  Plug the SD card into the DC SD adapter and plug the adapter in the link cable port on the back of the Dreamcast. Then, boot the disc. If it works, you will see this minor corruption of the usual Sega licensing screen :

  
  
  

  Then, there will be a brief white-on-black text screen that explains the booting process :
  

  
  
  

  Then, there will be the main DreamShell logo :

  
  
  

  Finally, you will land on the DreamShell main desktop :

  
  
  

  Skepticism
  At first, I was supremely skeptical of the idea that this SD adapter could perform speedily enough to play games reasonably. This was predicated on the observation that my DC coder’s cable that I used to use for homebrew development could not transfer faster than 115200 bits/second, amounting to about 11 kbytes/sec. I assumed that this was a fundamental limitation of the link port.

  In fact, I ripped a few of my Dreamcast discs over a decade ago and still have those rips lying around. So I copied the ISO image of Resident Evil : Code Veronica — the game I personally played most on the DC — to the SD card (anywhere works) and used the “ISO loader” icon seen on the desktop above to launch the game.

  It works :

  
  
  

  The opening FMV plays at full speed. Everything loads as fast as I remember. I was quite surprised.

  Digression : My assumptions about serial speeds have often been mistaken. 10 years ago, I heard stories about how we would soon be able to watch streaming video on our cell phones. I scoffed because I thought the 56K limitation of dialup modems was some sort of fundamental speed-of-light type of limitation for telephony bandwidth, wired or wireless.

  The desktop menu also includes a ‘speedtest’ tool that profiles the write and read performance of your preferred storage medium. For my fastest SD card (a PNY 2 GB card) :

  
  
  

  This is probably more representative of the true adapter bandwidth as reading and writing is a good deal faster through more modern interfaces on PC and Mac with this same card.

  Look at the other options on the speedtest console. Hard drive ? Apparently, it’s possible, but it requires a good deal more hardware hacking than just purchasing this SD adapter.

  Ripping
  As you can see from the Resident Evil screenshot, playing games works quite nicely. How about ripping ? I’m pleased to say that DreamShell has a beautiful ripping interface :

  
  
  

  Enter a name for the disc (or read the disc label), select the storage medium, and let it, well, rip. It indicates which track it’s working on and the Sega logo acts as a progress bar, shading blue as the track rip progresses.

  I’m finally, efficiently, archiving that collection of Sega Dreamcast demo discs ; I’m hoping they’ll eventually find a home at the Internet Archive. How is overall ripping performance ? Usually about 38-40 minutes to rip a full 900-1000 MB. That certainly beats the 27-28 hours that were required when I performed the ripping at 11 kbytes/sec via the DC coders cable.

  All is well until I get a sector reading error :

  
  
  

  That’s when it can come in handy to have 3 DC consoles (see ?! not crazy !).

  Other Uses
  There’s a file explorer. You can browse the filesystem of the SD card, visual memory unit, or the CD portion of the GD-ROM (would be more useful if it accessed the GD area). There are FFmpeg files included. So I threw a random Cinepak file and random MPEG-1 file at it to see what happens. MPEG-1 didn’t do anything, but this Cinepak file from some Sierra game played handily :

  
  
  

  If you must enter strings, it helps to have a Dreamcast keyboard (which I do). Failing that, here’s a glimpse of the onscreen keyboard that DreamShell equips :

  
  
  

  Learning to use it is a game in itself.

  There is an option of installing DreamShell in the BIOS. I did not attempt this. I don’t know if it’s possible (not like there’s a lot of documentation)– perhaps a custom BIOS modchip is needed. But here’s what the screen looks like :

  
  
  

  There is also a plain console to interact with (better have a physical keyboard). There are numerous file manipulation commands and custom system interaction commands. I see one interesting command called ‘addr’ that looks useful for dumping memory regions to a file.

  A Lua language interpreter is also built in. I would love to play with this if I could ascertain whether DreamShell provided Dreamcast-specific APIs.

  Tips And Troubleshooting
  I have 3 Dreamcast consoles, affectionately named Terran, Protoss, and Zerg after the StarCraft II stickers with which they are adorned. Some seem to work better than others. Protoss seemed to be able to boot the DreamShell disc more reliably than the others. However, I was alarmed when it couldn’t boot one morning when it was churning the previous day.

  I think the problem is that it was just cold. That seemed to be the issue. I put in a normal GD-ROM and let it warm up on that disc for awhile and then DreamShell booted fine. So that’s my piece of cargo-culting troubleshooting advice.